6,617 Cognitive AI Researcher jobs in the United States

Job Description

CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.

** Specific responsibilities for the Machine Learning Engineer position include: **

• Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
• Deconstructing client needs into data-driven processes/models and analytical measures.
• Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
• Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
• Productionizing ML systems with a focus on optimization and scalability to satisfy clients’ requirements.
• Growing CapTech’s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.

Qualifications:
Qualifications

• Bachelor's degree or equivalent combination of education and experience.
• Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
• Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
• Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
• Proficiency with containerization (e.g., Docker) and microservices.
• Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
• Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
• Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
• Knowledge of DevOps and automation best practices.
• Knowledge of statistics and statistical modeling methods.
• Knowledge of model management and model versioning best practices.

Additional Information

We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we’ve launched extended benefits to help meet our employees’ needs.

• Learning & Development – Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
• Modern Health –A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life’s ups and downs
• Carrot Fertility –Inclusive fertility and family-forming coverage for all paths to parenthood – including adoption, surrogacy, fertility treatments, pregnancy, and more – and opportunities for employer-sponsored funds to help pay for care
• Fringe –A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them – ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
• Employee Resource Groups – Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
• Philanthropic Partnerships – Opportunities to engage in partnerships and pro-bono projects that support our communities.
• 401(k) Matching – Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness — each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.

#LI-LM1

Eluvio uses a wide range of machine learning and deep learning techniques within its content fabric. This position offers an internship opportunity for students with excellent academic records pursuing graduate degrees in computer science, data science, or related fields (or advanced undergraduates) to work in our office with our software engineering team on ML, DL and data science solutions.

Responsibilities

• Work with the Eluvio Machine Learning and Data Science Team
• Build production level machine learning models on large-scale datasets to increase the intelligence of video/audio content
• Provide data-driven recommendations and actionable insights on problems such as content understanding/augmentation/location
• Develop multi-functional learning pipelines
• Collaborate with product and engineering teams to implement models at scale

Requirements

Desired Qualifications

• MSc or PhD student in Computer Science & Engineering/Statistics/Math/Physics, or Advanced Undergraduate
• Deep classroom experience in data science or machine learning or prior internship
• Comfortable with Python or R
• Knowledge of machine/deep learning algorithms (e.g. gradient boosting, CNNs, sequence models) and frameworks/libraries (e.g., Tensorflow, PyTorch, Sci kit-learn)
• Knowledge of computer vision and natural language processing
• Great communication skills, organized, able to multitask and be a team player
• Ability to balance attention to detail with agile execution

Benefits

Paid internship

Job Description
Senior Research Scientist - AI/ML & Signal Processing
Location: Great Baddow (Hybrid, 2 days onsite per week)
Salary: Up to £70,000 + benefits
We are seeking a Senior Research Scientist to join a growing Data and Decision Support capability within a leading global technology and defence organisation. This role is focused on developing novel AI/ML algorithms and statistical signal processing technique.

ZIPC1_UKTJ

Our client is seeking an ambitious and talented Data Science Intern to join their innovative team. This is a fully remote, paid internship opportunity, perfect for students pursuing a degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field. You will have the chance to apply theoretical knowledge to real-world problems, gain hands-on experience with machine learning models, and contribute to exciting projects. This role offers invaluable exposure to a professional data science environment, with opportunities to learn from experienced mentors and expand your technical skill set. The focus will be on developing, training, and deploying machine learning algorithms to solve complex business challenges.

Responsibilities:

• Assist in data collection, cleaning, and pre-processing from various sources.
• Develop, train, and evaluate machine learning models for predictive analytics, classification, and regression tasks.
• Implement feature engineering techniques to improve model performance.
• Explore and visualize data to identify patterns, trends, and anomalies.
• Collaborate with senior data scientists to understand project requirements and objectives.
• Document code, methodologies, and findings thoroughly.
• Assist in the deployment and monitoring of machine learning models in production environments.
• Participate in team meetings and contribute to discussions on data-driven insights and solutions.
• Research and experiment with new machine learning algorithms and techniques.
• Present findings and project progress to the team.
• Learn and utilize various data science tools and platforms, including Python libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch), SQL, and cloud environments.
• Contribute to building robust and scalable data pipelines.

This internship is designed to provide a comprehensive learning experience in a supportive and challenging remote setting. You should have a strong foundation in programming (preferably Python), a solid understanding of statistical concepts, and a keen interest in machine learning. Familiarity with data visualization tools and basic knowledge of cloud platforms are a plus. While the role is fully remote, effective communication and collaboration skills are essential for success within the team. This opportunity is ideal for gaining practical experience in **Las Vegas, Nevada, US**, without the need for physical relocation.

Job Title: Senior Machine Learning Engineer, GenAI Location: On-Site, Houston, TX if you are located in Houston, TX. We also consider exceptional candidates for remote work flexibility (if you are not located in Houston, TX area) .

Employment Type: Full-Time

Compensation : $135,000-$165,000 USD



ALTEA Healthcare is a leading healthcare organization committed to revolutionizing the delivery of outpatient/post-acute care. We are seeking a mid-level and a senior or lead-level Machine Learning Engineer to join our team. The ideal candidate will have a strong background in developing and deploying scalable GenAI solutions. As an important member of the AI team, this person will contribute significantly to designing, implementing, and deploying various AI/ML product features to improve care delivery and quality for post-acute patients.



Responsibilities:

Develop and deploy production-ready AI/ML models, with a focus on scalability and monitoring across a broad range of applications within healthcare

Write efficient, maintainable, and scalable Python code

Collaborate with machine learning scientists, data engineers, front end, back-end developers to write production-ready code

Set up and maintain end-to-end pipelines including data ingress, egress, model inference, and model retraining

Design, implement, and maintain production-grade FastAPI services to serve and integrate ML models securely and at scale.

Incorporate feedback from cross-functional teams and refine the ML-driven applications through quick iteration cycles

Maintain best software engineering and MLOps practices within the healthcare industry

Document the system architecture, design decisions, and codebase to facilitate future maintenance and enhancements



Additional responsibilities for the senior/lead level:

Technical leadership: brings technical mastery for most challenging technical problems, go-to person for technical help, guardrail for optimized system design and process flow

Best practices: create, maintain, and advocate for best practices via documentation

Ownership – Enable others: Step in when there are blockers, proactively unblock projects, educate and level-up team members

Ability to translate clinical and business requirements into technical specifications, collaborating closely with clinicians and product stakeholders.



Key Responsibilities and Qualifications:

Proven experience in deploying, scaling, integrating, and maintaining generative AI applications.

Strong understanding and experience in software engineering and MLOps best practices

Experience with unit testing and regression testing to ensure quality and stability.

Preferred : Experience working with Azure DevOps, Azure App Services, and Azure Functions.

Preferred : Experience with fine-tuning and pre-training language models and embedding models.

Preferred: Experience architecting large-scale ML systems integrated with enterprise healthcare data sources (EHRs, clinical workflows, APIs).

Preferred: Experience designing and maintaining evaluation frameworks, including dataset drift detection, error analysis, and healthcare-specific metrics to ensure model reliability and safety.

Note: This role is specifically focused on the deployment and integration of generative AI applications. It is not intended for data scientists, individuals primarily focused on building dashboards, or those with experience limited to traditional ML models and model development.



Other Requirements:

Bachelor’s or Master’s degree in Engineering, Computer Science, or equivalent experience

At least 2 years of relevant experience as an ML Engineer or software engineer

Experience with RAG and multi-agent systems

Experience writing production-ready code, troubleshooting and bug fixing

Strong proficiency in LangChain, vectorDB and cloud platforms (Azure)

Experience with MLOps, monitoring, and CI/CD

Experience with transformer-based models, NLP, LLM models, preferably for biomedical/healthcare applications

Strong interest in healthcare, with preferred experience working with healthcare data

Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines

Self-starter and growth mindset

For the senior/lead level: experience leading projects from concept to deployment



Job Type: Full-time

Pay: Competitive pay, benefits, and extremely valuable startup stock options

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.

Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).

Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.

Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.

Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).

Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.



Qualifications:

~3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.

~ Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.

~ Hands-on experience deploying ML models into production environments.

~ Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.

~ Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.

~ Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.

~ Passion for leveraging AI to improve patient outcomes and healthcare delivery.

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.

Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).

Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.

Contribute hands-on to engineering across the company’s technical stack: Python/Django, Vue, Kubernetes, and GCP.

Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).

Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.



Qualifications:

~3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.

~ Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.

~ Hands-on experience deploying ML models into production environments.

~ Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.

~ Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.

~ Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.

~ Passion for leveraging AI to improve patient outcomes and healthcare delivery.

Onshore-Junior Developer
Work Location: DATA SCIENCE AND MACHINE LEARNING-GACOR
Location: Sandy Springs, GA
Interview: Online

Work Mode: Hybrid

Job Description: Machine Learning Engineer – MLOps, VertexAI, LLMs, GenAI, ML Model Management
We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems.

You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business.

Under general supervision, works on software development assignments within a specific software functional area or product line
Conducts unit testing on the module
Involved in execution and reporting for system integration testing and regression testing

Mandatory Skills:

Expertise in programming languages like Python, SQL
Solid understanding of best MLOps practices and concepts for deploying enterprise-level ML systems
Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.)
Understanding of model evaluation metrics, model monitoring tools and practices
Experienced with GCP tools like BigQueryML, MLOps, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes etc.
Solid written and verbal communication skills and ability to prepare detailed technical documentation of new and existing applications
Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining
Bachelor's Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience

Desired Skills:

Experience in Azure MLOPS
Familiarity with Cloud Billing
Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features
Experience working in an Agile environment, understanding of Lean Agile principles

Summer 2026 Data Science/Machine Learning Intern

Are you looking for real corporate experience at a Fortune 250 company? Do you want to make a valuable contribution to a business's success? Are you ready to join an energetic, collaborative team and experience an inclusive culture of belonging? If so, then this may be just the opportunity you've been searching for. Read on and see for yourself.

As an Intern at ADP, you will work alongside seasoned professionals who will guide and support you to enhance your professional skills while gaining relevant experience in a business environment. Even better: You will also participate in a variety of functional and leadership activities to enhance your personal and professional capabilities. Your objective: To learn as much as possible and gain relevant business experience during your time interning with us.

Ready to Make Your Mark? Apply now!

What You'll Do:

• Advanced Analytics & Predictive Modeling. You bring prior experience to the role of formulating problems, extracting & analyzing data from multiple systems, summarizing critical findings/insights, and developing a compelling visual representation of analyses with actionable recommendationsthis will set you up for success on Day 1. You will interact with developers, UX designers, product managers, and senior executives to understand problem domain, project requirements, user experience and demonstrate model performance and its business value.
• Own and Manage Projects. You will identify, design, develop, and implement advanced analytical projects.
• Limitless Possibilities. You will continue learning and discovering new ways to leverage ADP data to create new products and services and find more insights. You are passionate about learning and applying new techniques within data science that leads to innovation.
• Collaboration and Communication. You'll be part of a collaborative team, listening to needs, then finding and sharing solutions. You're comfortable and skilled at presenting to both peers and leadership on your projects and findings.

To Succeed in This Role:

• You have completed at least 3 years of a 4 year Bachelor's degree or 1 year of a 2 year Master's degree in a quantitative discipline.
• Prior experience in Java, C++, SQL; Distributed computing tools such as Apache Hadoop, Apache Hive, or Apache Spark; Oracle, MongoDB; Data visualization tools, such as Tableau, will give you extra comfort in this role to be successful.
• Self-Starter. You are high-reaching and unstoppable. You have a can't-stop-won't-stop attitude and an urge to persevere until you get it right.
• Insatiable Appetite to Learn. You're always learning, growing, questioning, and challenging "what's been done before."
• Agile Solution Seeker. You're a problem solver who always can find the right answer even in times of fast-paced change.