113 Junior AI Ml Engineer jobs in Oakdale

Job Description:

Ryan Companies seeks to hire an AI/ML Engineer to join a newly formed team of experts in our Minneapolis headquarters. This will be a hybrid role, 3 or 4 days in the office, to support a collaborative environment to support a wide range of Ryan Companies business. We are looking for 2 to 5 years of experience. We welcome new insights and input on what capabilities the team can bring and how the team develops.

The AI Engineer would report to the Director of AI, and be at the forefront of our AI initiatives across the business. This role will be responsible for driving the development, research, and application of machine learning, and generative AI solutions targeted at solving key business challenges and opportunities.

The AI Engineer will be directly involved in advancing Ryan's data maturity and continual progress as a data-driven decision-making Real Estate Development, Construction, Design, and Management organization.

Responsibilities

• AI Model Development : Design, develop, and deploy AI/ML models and applications to solve complex business challenges.

• Initiative Leadership : Lead the development and execution of strategic AI initiatives and contribute to the strategic direction of Ryan's AI roadmap.

• Data Preparation : Collect, clean, and preprocess datasets to ensure quality for training and fine-tuning AI models.

• Application Development : Write scalable, efficient, and maintainable code for AI applications using languages like Python or Java.

• Model Deployment : Implement and maintain AI models in production environments, ensuring system stability, scalability, and performance.

• Cost Management : Understand and manage cost frameworks for production AI applications and solutions.

• Culture Building : Actively participate in fostering Ryan's data culture and promoting data-driven decision-making.

Required Experience

• 3+ years of experience in developing and deploying AI/ML solutions on cloud platforms such as Azure, AWS or Google Cloud Platform (GCP).

• Proven experience developing and deploying custom Retrieval-Augmented Generation (RAG) applications for tasks such as document analysis, image recognition, and semantic search.

• Hands-on experience with large language models (LLMs), including fine-tuning and customization for specific use cases.

• Strong knowledge of cloud infrastructure, data pipelines, and preprocessing techniques for AI/ML.

• Demonstrated success in scaling AI-driven applications from concept to production environments.

• Familiarity with vector databases and data integration methods.

• Experience building AI agents for enterprise applications.

• Bachelor's degree in Computer Science, Data Science, or a related field, or equivalent work experience.

To be Successful

• Strong problem-solving skills and the ability to communicate effectively with both technical and non-technical audiences.

• Eagerness to learn the business of construction, real estate, and design to create impactful and valuable AI solutions.

• Ability to work collaboratively in a team environment with diverse skill sets.

• Resourceful, entrepreneurial, and innovative mindset, with a drive to tackle ambiguous challenges effectively.

• Commitment to staying updated on AI/ML trends and leveraging them to deliver business value.

• Understanding of ethical and responsible AI principles and practices

Technical Skills

• Proficient in Python and SQL

• Proficient in NLP

• Familiar with Computer vision

• Experience with ETL

• Experience with APIs and Data Integrations

• Experience integrating AI insights into BI platforms.

Eligibility:

• Positions require verification of employment eligibility to work in the U.S.

Compensation:

The base salary range is $95,000-$137,000 annually. The salary base rate may vary within the anticipated range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include commission and/or an incentive program.

Benefits

• Competitive Salary

• Medical, Dental and Vision Benefits

• Retirement and Savings Benefits

• Flexible Spending Accounts

• Life Insurance

• Educational Assistance

• Paid Time Off (PTO)

• Parenting Benefits

• Long-term Disability

• Ryan Foundation - charitable matching funds

• Paid Time for Volunteer Events

Ryan Companies is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Non-Solicitation Notice to Recruitment Agencies:

Ryan Companies kindly requests that recruitment agencies and third-party recruiters do not submit unsolicited resumes or candidate information to any Ryan Companies employee or office. Ryan Companies will not be responsible for any fees or expenses associated with unsolicited submissions. If recruitment services are required, we will reach out directly to agencies on our approved vendor list. We appreciate your understanding and cooperation.

Since 2010 Synergisticit has helped Jobseekers get employed in the tech job market by providing candidates the requisite skills, experience, and technical competence to outperform at interviews and at clients. Here at SynergisticIT We just don't focus on getting you a tech Job we make careers.
In this Job market also, our candidates are able to achieve multiple job offers and $100k + salaries.
please check the below links to see the success outcomes and salaries of our candidates .




We regularly interact with the Top Tech companies to give our candidates a competitive advantage visit the below videos exhibiting at Oracle Cloud World/Oracle Java one (Las Vegas) -2023/2022 and at Gartner Data Analytics Summit (Florida)-2023









All Positions are open for all visas and US citizens
We at Synergisticit understand the problem of the mismatch between employer's requirements and Employee skills and that's why since 2010 we have helped 1000's of candidates get jobs at technology clients like Apple, google, Paypal, Western Union, Client, visa, Walmart lab s etc to name a few.
Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
Who Should Apply Recent Computer Science/Engineering /Mathematics/Statistics or Science Graduates or People looking to switch careers or who have had gaps in employment and looking to make their careers in the Tech Industry.
We assist in filing for STEM extension and also for H1b and Green card filing to Candidates
We want Data Science/Machine learning/Data Analyst and Java Full stack candidates
For data Science/Machine learning Positions
REQUIRED SKILLS
Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
Project work on the technologies needed
Highly motivated, self-learner, and technically inquisitive
Experience in programming language Java and understanding of the software development life cycle
Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools
Excellent written and verbal communication skills
Preferred skills: NLP, Text mining, Tableau, PowerBI, Databricks, Tensorflow
REQUIRED SKILLS For Java /Full stack/Software Positions
Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
Highly motivated, self-learner, and technically inquisitive
Experience in programming language Java and understanding of the software development life cycle
Project work on the skills
Knowledge of Core Java, Javascript, C++, or software programming
Spring boot, Microservices, Docker, Jenkins, Github, Kubernates, and REST API's experience
Excellent written and verbal communication skills
If you get emails from our Job Placement team and are not interested please email them or ask them to take you off their distribution list and make you unavailable as they share the same database with the client servicing team and only connect with candidates who are matching client requirements.
No phone calls, please. Shortlisted candidates would be reached out. No third-party or agency candidates or c2c candidates

Job Description

About the job

Location: On-site Cambridge, MA (Eastern Time / UTC -4)
Start date: ASAP
Languages: English (required)

This role is on-site in in the Cambridge, Massachusetts area. Relocation is considered for the right candidate who is not currently based in Cambridge, Massachusetts . Please inquire for more details during the interview process.

We are hiring at Pragmatike to expand our team and drive the growth of our internal projects.

Our focus is on developing cutting-edge solutions in Cloud Computing, Blockchain, and Artificial Intelligence, while fostering a culture of collaboration and innovation. Joining us means being part of a passionate team where your ideas and skills directly contribute to shaping tomorrow's technologies.

If you're passionate about applied AI and enjoy solving real problems in a fast-paced environment, wed love to meet you.

Responsabilities:

• Design, implement, and fine-tune machine learning models for production-grade use cases.

• Curate and manage datasets used in training, validation, and evaluation.

• Work closely with engineers to integrate ML models into larger systems and monitor their performance in production.

• Ensure that AI solutions are efficient, maintainable, and aligned with business objectives.

• Maintain thorough documentation for reproducibility and team collaboration.

Required qualifications:

• Solid hands-on experience with AI/ML systems from development to deployment.

• Proficient in Python ; familiarity with TypeScript or Go for integration tasks is a plus.

• Strong command of tools and frameworks such as PyTorch , Transformers , Llama-factory , VLLM , Megatron-LM , and CUDA .

• Comfortable working with cloud environments (AWS , GCP , or Azure ) and containerized deployments (Docker , Kubernetes ).

• Strong communication and team collaboration skills.
  
  

Preferred qualifications:

• Experience deploying models at scale in production environments.

• Familiarity with CI/CD and DevOps workflows for ML applications.

• Previous experience in high-paced, innovation-driven environments (e.g., startups).

• Background in systems-level optimization for machine learning workloads.

Why join us?

• Work on impactful AI systems with real-world applications.

• Join a focused, collaborative engineering team based in Boston/Cambridge.

• Be part of a company where your ideas and code go into productionnot just into slide decks.

• Competitive salary, equity options, and strong benefits (Insurance, 401K, moving expenses)

• Continuous learning environment with room to grow technically and professionally.

Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

The AI/ML Engineer will play a key role within the AI Center of Excellence (CoE), focusing on building, scaling, and maintaining robust ML and GenAI operational infrastructure. This position is responsible for developing and automating end-to-end machine learning pipelines, deploying models into production, and ensuring their performance and stability over time. The ideal candidate is a hands-on engineer with strong experience in MLOps, LLMOps, and cloud-native tools, and a passion for reliable, scalable, and efficient AI systems.

ACCOUNTABILITIES: (The primary functions, scope and responsibilities of the role)

Engineering and Operations:

• Develop, deploy, and maintain production-grade ML/GenAI pipelines using AWS cloud-native and open-source MLOps tools.
• Automate model training, evaluation, testing, deployment, and monitoring workflows.
• Implement LLMOps practices for prompt versioning, model tracking, and continuous evaluation of GenAI systems.
• Integrate ML systems with CI/CD pipelines and infrastructure-as-code tools.
• Support model inference at scale via APIs, containers, and microservices.
• Work closely with data engineering to ensure high-quality, real-time, and batch data availability for ML workflows.
• Ensure high availability, reliability, and performance of AI services in production environments.
• Maintain robust monitoring and observability on AWS, Snowflake, SalesForce and Oracle ecosystems.
• Implement feature stores and data versioning systems to ensure reproducible ML experiments and deployments.
• Deploy and optimize vector databases and embedding models for semantic search and RAG applications.
• Configure GPU enabled cloud infrastructure and implement monitoring solutions to optimize resource utilization, costs and performance for ML training and inference workloads.
• Establish automated model validation, testing, and rollback procedures for safe production deployments.

Tooling and Infrastructure:

• Build and manage model registries, feature stores, and metadata tracking systems.
• Leverage containerization (e.g., Docker) and orchestration (e.g,Kubernetes, Airflow, Kubeflow) for scalable deployment. Implement role-based access control, auditing, and governance for ML infrastructure.
• Manage cost-effective cloud infrastructure using AWS.
• Build and maintain data quality monitoring systems with automated alerting for data drift and anomalies.
• Implement cost optimization strategies including auto-scaling, spot instances, and resource right-sizing for ML workloads.

Collaboration and Support:

• Partner with data engineers, data scientists, ML engineers, architects, software engineers, infrastructure and security teams to support scalable and efficient AI/ML workflows.
• Contribute to incident response, performance tuning, and continuous improvement of ML pipelines.
• Provide guidance and documentation to promote reproducibility and best practices across teams.
• Work as part of an agile development team and participate in planning and code reviews.

Knowledge of:

• Cloud-native AI/ML development with AWS.
• MLOps/LLMOps frameworks and lifecycle tools on AWS.
• Monitoring and observability platforms on AWS.
• ML model deployment strategies (e.g., batch, real-time, streaming).
• Feature stores and data versioning tools on AWS and Snowflake
• Model serving frameworks like AWS Sagemaker and AWS Bedrock for scalable inference deployment.
• Vector databases and embedding deployment (e.g., Pinecone, Weaviate, FAISS, pgvector) for LLM and RAG applications.
• LLMOps-specific tools including prompt management platforms and LLM serving optimization on AWS.
• Docker registries and artifact management.

Required Skills and Abilities:

• Strong Python programming and scripting skills.
• Hands-on experience deploying and managing ML/GenAI models in production.
• Experience with Docker, Kubernetes, and workflow orchestration tools like Airflow or Kubeflow.
• Proficiency in infrastructure-as-code tools (e.g., Terraform, CloudFormation).
• Ability to debug, troubleshoot, and optimize AI/ML pipelines and systems.
• Comfortable working in agile teams and collaborating cross-functionally.
• Proven ability to automate processes and build reusable ML operational frameworks.
• Experience with A/B testing frameworks and canary deployments for ML models in production environments.
• Knowledge of GPU resource management and optimization for training and inference workloads.
• Understanding data pipeline quality monitoring, drift detection, and automated retraining triggers.
• Experience with secrets management, role-based access control, and secure credential handling for ML systems.

Education and/or Experience:

• Bachelor's degree in computer science, Engineering, or a related field (master's preferred).
• 2-3 years of experience in ML engineering, DevOps, or MLOps roles.
• Demonstrated experience managing production AI/ML workloads and systems.

• Experience with LLMOps and GenAI pipeline monitoring.
• Cloud certifications in AWS, Azure, or GCP.
• Experience supporting AI applications in regulated industries (e.g.,healthcare, finance).
• Contributions to open-source MLOps tools or infrastructure projects.
• Experience with edge deployment and model optimization techniques (quantization, pruning, distillation).
• Knowledge of compliance frameworks (SOC2, GDPR, HIPAA) and security best practices for AI/ML systems.
• Experience with real-time streaming data pipelines (Kafka, Kinesis) and event-driven ML Architectures.

The AI/ML Engineer will play a key role within the AI Center of Excellence (CoE), focusing on building, scaling, and maintaining robust ML and GenAI operational infrastructure. This position is responsible for developing and automating end-to-end machine learning pipelines, deploying models into production, and ensuring their performance and stability over time. The ideal candidate is a hands-on engineer with strong experience in MLOps, LLMOps, and cloud-native tools, and a passion for reliable, scalable, and efficient AI systems.

ACCOUNTABILITIES: (The primary functions, scope and responsibilities of the role)

Engineering and Operations:

• Develop, deploy, and maintain production-grade ML/GenAI pipelines using AWS cloud-native and open-source MLOps tools.
• Automate model training, evaluation, testing, deployment, and monitoring workflows.
• Implement LLMOps practices for prompt versioning, model tracking, and continuous evaluation of GenAI systems.
• Integrate ML systems with CI/CD pipelines and infrastructure-as-code tools.
• Support model inference at scale via APIs, containers, and microservices.
• Work closely with data engineering to ensure high-quality, real-time, and batch data availability for ML workflows.
• Ensure high availability, reliability, and performance of AI services in production environments.
• Maintain robust monitoring and observability on AWS, Snowflake, SalesForce and Oracle ecosystems.
• Implement feature stores and data versioning systems to ensure reproducible ML experiments and deployments.
• Deploy and optimize vector databases and embedding model s for semantic search and RAG applications.
• Configure GPU enabled cloud infrastructure and implement monitoring solutions to optimize resource utilization, costs and performance for ML training and inference workloads.
• Establish automated model validation, testing, and rollback procedures for safe production deployments.

Tooling and Infrastructure:

• Build and manage model registries, feature stores, and metadata tracking systems.
• Leverage containerization (e.g., Docker) and orchestration (e.g,Kubernetes, Airflow, Kubeflow) for scalable deployment. Implement role-based access control, auditing, and governance for ML infrastructure.
• Manage cost-effective cloud infrastructure using AWS.
• Build and maintain data quality monitoring systems with automated alerting for data drift and anomalies.
• Implement cost optimization strategies including auto-scaling, spot instances, and resource right-sizing for ML workloads.

Collaboration and Support:

• Partner with data engineers, data scientists, ML engineers, architects, software engineers, infrastructure and security teams to support scalable and efficient AI/ML workflows.
• Contribute to incident response, performance tuning, and continuous improvement of ML pipelines.
• Provide guidance and documentation to promote reproducibility and best practices across teams.
• Work as part of an agile development team and participate in planning and code reviews.

Knowledge of:

• Cloud-native AI/ML development with AWS.
• MLOps/LLMOps frameworks and lifecycle tools on AWS.
• Monitoring and observability platforms on AWS.
• ML model deployment strategies (e.g., batch, real-time, streaming).
• Feature stores and data versioning tools on AWS and Snowflake
• Model serving frameworks like AWS Sagemaker and AWS Bedrock for scalable inference deployment.
• Vector databases and embedding deployment (e.g., Pinecone, Weaviate, FAISS, pgvector) for LLM and RAG applications.
• LLMOps-specific tools including prompt management platforms and LLM serving optimization on AWS.
• Docker registries and artifact management.

Required Skills and Abilities:

• Strong Python programming and scripting skills.
• Hands-on experience deploying and managing ML/GenAI models in production.
• Experience with Docker, Kubernetes, and workflow orchestration tools like Airflow or Kubeflow.
• Proficiency in infrastructure-as-code tools (e.g., Terraform, CloudFormation).
• Ability to debug, troubleshoot, and optimize AI/ML pipelines and systems.
• Comfortable working in agile teams and collaborating cross-functionally.
• Proven ability to automate processes and build reusable ML operational frameworks.
• Experience with A/B testing frameworks and canary deployments for ML models in production environments.
• Knowledge of GPU resource management and optimization for training and inference workloads.
• Understanding data pipeline quality monitoring, drift detection, and automated retraining triggers.
• Experience with secrets management, role-based access control, and secure credential handling for ML systems.

Education and/or Experience:

• Bachelor's degree in computer science, Engineering, or a related field (master's preferred).
• 2-3 years of experience in ML engineering, DevOps, or MLOps roles.
• Demonstrated experience managing production AI/ML workloads and systems.

• Experience with LLMOps and GenAI pipeline monitoring.
• Cloud certifications in AWS, Azure, or GCP.
• Experience supporting AI applications in regulated industries (e.g.,healthcare, finance).
• Contributions to open-source MLOps tools or infrastructure projects.
• Experience with edge deployment and model optimization techniques (quantization, pruning, distillation).
• Knowledge of compliance frameworks (SOC2, GDPR, HIPAA) and security best practices for AI/ML systems.
• Experience with real-time streaming data pipelines (Kafka, Kinesis) and event-driven ML Architectures.

Our client is a digital consumer product. They're building social features using LLMs and Machine Learning to add to user experience. We're looking for a Principal Machine Learning Engineer to build AI features for the family.

Qualifications:

• A confident craftsperson who possesses problem-solving tools and can discuss multiple approaches while preferring the best approach given the constraints.
• A scientific artist and artistic scientist who can navigate complexity and bring clarity to intricate problems while appreciating simplicity as the highest sophistication.
• A pragmatic optimizer who identifies the need for change, articulates it, and drives incremental improvements toward ambitious goals.
• An advocate for team collaboration and open communication.
• Possesses comprehensive knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and advanced NLP techniques.
• Significant experience in AI/ML engineering with a strong data science background.
• Demonstrated ability in designing and training LLMs.
• Expertise in Databricks/Apache Spark for large-scale data processing in AI/ML applications.
• Proficiency with AWS Bedrock and Comprehend.
• Demonstrated leadership in AI/ML solutions in a commercial environment.
• Proficiency in programming languages such as R, Python, and Java, with a focus on data exploration and processing.
• Proven ability to lead and inspire teams of senior engineers and data scientists.
• Effective individual contributor within a collaborative team environment.
• Strong analytical, problem-solving, and communication skills.

• Collaborate with the Data team to transform Data Lakehouse potential into actionable insights and services that enhance user experiences.
• Shape AI/ML strategies, particularly in LLMs, to drive business outcomes and establish data science principles.
• Implement technologies in AWS and Databricks for handling and processing large datasets for advanced language model training.
• Lead data science practices, including model selection and training methodology.
• Build, train, manage, and host LLMs using Data Lakehouse data.
• Optimize AI system performance through testing and tuning, leveraging data science and Databricks methodologies.
• Ensure ethical standards and data privacy compliance in AI solutions.
• Provide specialized AI/ML expertise to guide the development and optimization of AI features.
• Stay updated on the latest AI/ML and data science trends, especially in LLMs and AWS, Databricks/Apache Spark technology.

• Full Medical Coverage: OFW covers 100% of premiums for employees and their families.
• 401k: Up to a 4% match with immediate vesting.
• 12 weeks of paid leave for all new parents.
• Learning & Development stipend for employees.
• Supportive and flexible working environment, allowing remote work from anywhere.

• Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
• Highly motivated, self-learner, and technically inquisitive
• Experience in programming language Java and understanding of the software development life cycle
• Knowledge of Core Java , javascript , C++ or software programming
• Spring boot, Microservices and REST API's experience
• Excellent written and verbal communication skills

• Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
• Highly motivated, self-learner, and technically inquisitive
• Experience in programming language Java and understanding of the software development life cycle
• Knowledge of Statistics, Python, data visualization tools
• Excellent written and verbal communication skills

At Provation, AI and machine learning are at the core of our innovation and success. We are seeking an experienced Senior AI/ML Engineer who will lead efforts to design, build, and maintain cutting-edge AI-driven solutions that enhance Provation’s products. The AI/ML Engineer will be responsible for developing scalable machine learning models, optimizing AI architectures, and ensuring seamless integration of AI solutions across various business functions.

Duties & Responsibilities:

• Lead the end-to-end development and deployment of advanced AI/ML models to support Provation’s product initiatives and platform capabilities.

• Implement best practices in AI/ML model development, including data preprocessing, feature engineering, model training, and optimization.

• Work closely with Product Management, Data Scientists, and Engineering to evaluate, develop, and maintain innovative AI-powered solutions.

• Manage and scale data pipelines to support AI/ML workflows, ensuring efficient data availability for training and inference.

• Research and implement state-of-the-art AI/ML techniques, including deep learning, NLP, computer vision, and generative AI.

• Develop and manage MLOps workflows, ensuring model monitoring, retraining, and governance in production.

• Collaborate with DevOps and software engineering teams to deploy AI models in cloud environments including integration of AI/ML models with .NET microservices and Kubernetes

• Ensure compliance with security, ethical AI, and regulatory requirements (e.g., HIPAA, GDPR) when working with sensitive data.

• Develop and implement methods to measure the accuracy and effectiveness of AI solutions, ensuring continuous improvement and adherence to performance standards.

• Participate in Agile development processes, including daily stand-ups, sprint planning, and code reviews.

• Act as a thought leader by contributing to AI strategy, roadmap development, and innovation planning.

Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent experience.

• 5+ years of experience in AI/ML development with demonstrable impact on commercial software or products.

• Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

• Experience with generative AI and large language models (LLMs), including their development, deployment, and optimization.

• Hands-on experience in building and optimizing deep learning models for NLP, computer vision, or time-series forecasting.

• Experience working with cloud-based AI/ML platforms (Azure ML, Azure AI Foundry)

• Solid understanding of data structures, algorithms, and distributed computing.

• Deep understanding of MLOps tools and frameworks (MLflow, Kubeflow, Airflow, etc.).

• Experience with C# and .NET

• Experience deploying AI/ML models in containerized environments (Docker, Kubernetes) is a plus.

• Strong understanding of AI ethics, data privacy, and security considerations.

Fortive Corporation Overview

Fortive’s essential technology makes the world safer and more productive. We accelerate transformation in high-impact fields like workplace safety, build environments, and healthcare.

We are a global industrial technology innovator with a startup spirit. Our forward-looking companies lead the way in healthcare sterilization, industrial safety, predictive maintenance, and other mission-critical solutions. We’re a force for progress, working alongside our customers and partners to solve challenges on a global scale, from workplace safety in the most demanding conditions to advanced technologies that help providers focus on exceptional patient care.

We are a diverse team 10,000 strong, united by a dynamic, inclusive culture and energized by limitless learning and growth. We use the proven Fortive Business System (FBS) to accelerate our positive impact.

At Fortive, we believe in you. We believe in your potential—your ability to learn, grow, and make a difference.

At Fortive, we believe in us. We believe in the power of people working together to solve problems no one could solve alone.

At Fortive, we believe in growth. We’re honest about what’s working and what isn’t, and we never stop improving and innovating.

Fortive: For you, for us, for growth.

About Provation

Provation is a leading provider of healthcare software and SaaS solutions for clinical productivity, care coordination, quality reporting, and billing. Our purpose is to empower providers to deliver quality healthcare for all. Provation’s comprehensive portfolio spans the entire patient encounter, from pre-procedure through post-procedure, with solutions for physician and nursing documentation (Provation® MD, Provation® Apex, MD-Reports, Provation® endoPRO®, and Provation® MultiCaregiver), anesthesia documentation (#1 Best in KLAS Provation® iPro), patient engagement, surgical care coordination, quality reporting, and billing capture (Provation® SurgicalValet™), order set and care plan management (Provation® Order Set Advisor™ and Provation® Care Plans), and EHR embedded clinical documentation (Provation® Clinic Note). Provation has a loyal customer base, serving more than 5,000 hospitals, surgery centers, and medical offices, and 700 physician groups globally, including 19 of the top 20 U.S. hospitals. In 2021, Provation was acquired by Fortive Corporation, a Fortune 1000 company that builds essential technology and accelerates transformation in high-impact fields like workplace safety, engineering, and healthcare. For more information about our solutions, visit provationmedical.com and follow us on Twitter, Facebook, and LinkedIn. Our purpose at Provation is to empower providers to deliver quality healthcare for all. To deliver on this commitment, we’re guided by our core values – Provation has a culture of CARES:Community - We have a shared sense of improving healthcare, enriching the broader world we live in and serve. Accountability - We own it and get it done with integrity. Respect - We build diverse teams that collaborate and communicate with positive intent and trust. Excellence - We welcome new ideas as we innovate quality solutions. Service - We are passionate about putting customers first.

We Are an Equal Opportunity Employer. Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at

Pay Range

The salary range for this position (in local currency) is 100,700.00 - 186,900.00

The salary range for this position (in local currency) is 100,700.00 - 186,900.00

We are an Equal Opportunity Employer

Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at

At Resideo, we’re building the future of the smart home—intelligent, adaptive, and deeply aware of its environment. As part of our AI Team , you’ll help deliver real-world machine learning systems that power next-generation experiences across security, energy, and automation.

We’re looking for a Principal AI/ML Engineer with a secure foundation in AI/ML and applied experience in computer vision and/or large language models to lead the design and deployment of models that run across edge devices, cloud platforms, and connected products. This is not a pure research role—it’s about translating deep learning advances into performant, production-grade systems that run at scale.

You’ll work on a range of problems including object detection, video summarization, activity recognition, sensor fusion, and lightweight inference, blending vision and broader AI techniques to unlock valuable product features.

JOB DUTIES:

• Architect, build, and optimize AI pipelines that span from embedded vision models to cloud-based analytics.

• Design and deploy deep learning models for object detection, event recognition, behavior classification, and other real-time inference tasks.

• Contribute to multi-modal AI efforts involving video, image, audio, sensor data, and context-driven inference.

• Collaborate with engineering teams across firmware, cloud, and mobile to deliver integrated and efficient AI experiences.

• Lead rapid prototyping of intelligent features, guiding experimentation and de-risking technical approaches.

• Tune models for performance across cost, latency, accuracy, and power—particularly on embedded and edge devices.

• Stay informed on relevant advances in AI (e.g., vision transformers, sensor fusion, embedded ML), and help identify where new techniques can bring product impact.

• Mentor junior engineers and provide technical leadership across project teams.

YOU MUST HAVE:

• 5+ years experience developing and deploying production-grade AI/ML solutions, with at least 2+ years in computer vision or Large Language Models domains.

• Proficiency in deep learning frameworks like PyTorch or TensorFlow, and strong Python programming skills.

WE VALUE:

• Experience with vision models (e.g., YOLO, EfficientDet, MobileNet, ResNet) as well as general ML.

• Proven ability to balance experimentation with delivery—translating research into customer-facing functionality.

• Practical understanding of vision pipelines, video analytics, and false alarm reduction.

• Experience integrating AI models into embedded systems, mobile apps, or smart devices.

• Comfort working across the AI stack—from data preparation and model training to deployment and observability

• Familiarity with LLMs, agentic workflows, etc

WHAT'S IN IT FOR YOU:

• Opportunity to have a direct impact on high-scale projects and products selling to millions of homes and businesses worldwide.

• Play a key role in driving a world where people are healthy, happy, safe, and secure through innovative AI and IoT solutions.

• Full ownership of a dynamic tech stack and the chance to work with cutting-edge technologies.

• Collaborate with high-performing, cross-functional teams in an agile and intellectually stimulating environment.

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Resideo is a $6.76 billion global manufacturer, developer, and distributor of technology-driven sensing and control solutions that help homeowners and businesses stay connected and in control of their comfort, security, energy use, and smart living. We focus on the professional channel, serving over 100,000 contractors, installers, dealers, and integrators across the HVAC, security, fire, electrical, and home comfort markets. Our products are found in more than 150 million residential and commercial spaces worldwide, with tens of millions of new devices sold annually. Trusted brands like Honeywell Home, First Alert, and Resideo power connected living for over 12.8 million customers through our Products & Solutions segment. Our ADI | Snap One segment spans 200+ stocking locations in 17 countries, offering a catalog of over 500,000 products from more than 1,000 manufacturers. With a global team of more than 14,000 employees, we offer the opportunity to make a real impact in a fast-growing, purpose-driven industry. Learn more at

At Resideo, we bring together diverse individuals to build the future of homes. Resideo is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status. For more information on applicable U.S. equal employment regulations, refer to the "EEO is the Law" poster, "EEO is the Law" Supplement Poster and the Pay Transparency Nondiscrimination Provision. Resideo complies with applicable equal employment laws in all countries where we do business. For more information on how we process your information in the job application process, please refer to Recruitment Privacy Notice. If you require a reasonable accommodation to apply for a job, please use Contact Us form for assistance.