What Jobs are available for Data Science in San Jose?

Data Science Manager, GenAI - SFL Scientific
Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.
Recruiting for this role ends 11/30/2025.
Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to:
+ Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
+ Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
+ Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
+ Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
+ Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
+ Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
+ Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
+ Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
+ Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles
The TeamOur Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications
Required:
+ Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
+ 6+ years of experience working in data science, data engineering, software engineering, or MLOps
+ 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
+ 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
+ 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
+ 4+ years of experience managing teams and delivering complex and critical projects
+ Live within commuting distance to one of Deloitte's consulting offices
+ Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
+ Limited immigration sponsorship may be available
Preferred:
+ Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
+ Experience with developing and testing GenAI solutions
+ Experience in a client-facing role or internal AI product development role
+ Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
Information for applicants with a need for accommodation: wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $130,800 to $241,000.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.

Data Science Manager, Healthcare & Life Sciences - SFL Scientific
Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific, a Deloitte Business practice brings together several key capabilities to architect integrated programs that transform our clients' businesses.
We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare and life sciences.
Recruiting for this role ends on 11/30/2025.
Work You'll Do
As a Data Science Manager at SFL Scientific, a Deloitte Business, you will manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases.
Successful candidates will be an expert in using state-of the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications in healthcare, diagnostics, hospital operations, and more. Join us to expand your technical career through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.
+ Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
+ Engage and guide healthcare clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
+ Lead for an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for clinical and non-clinician applications
+ Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
+ Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
+ Mentor, motivate and coach junior data scientists on technical best practices and inspire professional development
The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications:
+ Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
+ 6+ years of experience working in data science, data engineering, software engineering, or MLOps
+ 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision, to graph models
+ 6+ years of experience in core programming languages and data science packages (Python, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.)
+ 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
+ 4+ years of experience managing teams and delivering complex and critical projects
+ Live within commuting distance to one of Deloitte's consulting offices
+ Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
+ Limited immigration sponsorship may be available
Preferred Qualifications:
+ Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
+ Experience with developing and testing GenAI solutions for healthcare or life sciences
+ Experience in a client-facing role
+ Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations
Information for applicants with a need for accommodation: wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $130,800 to $241,000.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.

Our client is a leader in resource extraction and is seeking a highly accomplished Senior Lead Data Scientist specializing in Mining Analytics to join their innovative team in San Jose, California, US . This hybrid role offers a dynamic work environment, combining focused remote work with essential in-office collaboration and strategic planning. You will lead the development and implementation of advanced data-driven solutions to optimize mining operations, improve resource efficiency, and enhance safety protocols. Your expertise in machine learning, statistical modeling, and big data technologies will be critical in uncovering insights from vast datasets and driving significant improvements across the mining lifecycle.

Responsibilities:

• Lead the design, development, and deployment of machine learning models and advanced analytics solutions for mining operations.
• Analyze large and complex datasets related to geological surveys, operational efficiency, equipment performance, and safety.
• Identify key performance indicators (KPIs) and develop dashboards and reports to track progress and inform decision-making.
• Collaborate with geologists, engineers, and operations managers to understand business needs and translate them into data science projects.
• Mentor and guide a team of data scientists and analysts, fostering a culture of innovation and technical excellence.
• Evaluate and implement new data science tools and techniques relevant to the mining industry.
• Ensure the quality, accuracy, and integrity of data used for analysis and model development.
• Communicate complex analytical findings and recommendations to technical and non-technical stakeholders.
• Stay current with the latest advancements in data science, artificial intelligence, and their applications in the mining sector.
• Contribute to the strategic direction of data analytics within the organization.

Qualifications:

• Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 8-10 years of experience in data science, with a significant portion focused on applied analytics in industrial or mining environments.
• Proven leadership experience in managing data science teams and projects.
• Expertise in programming languages such as Python or R, and proficiency with data manipulation libraries (e.g., Pandas, NumPy).
• Strong experience with machine learning algorithms (supervised and unsupervised), statistical modeling, and data mining techniques.
• Proficiency with big data technologies and platforms (e.g., Spark, Hadoop).
• Experience with SQL and NoSQL databases.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data science services.
• Excellent communication, presentation, and interpersonal skills.
• Ability to work effectively in a hybrid team environment and manage multiple projects concurrently.
• Understanding of mining processes and challenges is a strong asset.

This is an exceptional opportunity to apply cutting-edge data science techniques to drive transformation in the mining industry. If you are a results-oriented leader passionate about leveraging data to solve complex problems, we encourage you to apply.

Our client is seeking a highly skilled and experienced Lead Geologist with expertise in remote sensing and advanced data analysis to join their globally distributed team. This is a fully remote position, allowing you to work from anywhere within the specified time zone compatibility for collaboration. The role is pivotal in leveraging satellite imagery, aerial photography, and other geospatial data sources to identify, assess, and characterize mineral and energy resources. The Lead Geologist will be responsible for developing innovative analytical workflows, managing large geological datasets, and contributing to strategic exploration initiatives.

Responsibilities:

• Develop and implement advanced remote sensing techniques and data processing workflows for geological applications.
• Analyze diverse geospatial datasets, including optical, radar, and hyperspectral imagery, as well as LiDAR and geophysical data.
• Identify and interpret geological features and structures indicative of mineral and energy deposits.
• Create detailed geological maps, models, and reports based on remote sensing and integrated data analysis.
• Collaborate with a global team of geologists, geophysicists, and data scientists to support exploration and resource assessment projects.
• Manage large geological and geospatial databases, ensuring data integrity and accessibility.
• Stay abreast of the latest advancements in remote sensing technologies, geospatial software, and geological interpretation methodologies.
• Contribute to the strategic planning of exploration programs and target generation.
• Mentor junior geologists and data analysts, providing technical guidance and support.
• Present findings and recommendations to project stakeholders and executive leadership.
• Ensure compliance with data management and environmental best practices.
• Utilize advanced programming and scripting skills for data automation and analysis.

Qualifications:

• M.S. or Ph.D. in Geology, Earth Science, or a related field with a strong emphasis on remote sensing and geospatial analysis.
• Minimum of 8 years of professional experience in geological exploration or resource assessment, with a significant focus on remote sensing data integration and interpretation.
• Demonstrated expertise in processing and analyzing various types of satellite and aerial imagery (e.g., Landsat, Sentinel, Planet, UAV).
• Proficiency with industry-standard geospatial software (e.g., ArcGIS, QGIS, ERDAS Imagine, ENVI) and remote sensing toolkits.
• Strong programming skills in languages such as Python (with libraries like GDAL, Rasterio, NumPy, Pandas) and/or R.
• Experience with geological modeling software and techniques.
• Knowledge of mineralogy, structural geology, and exploration geology principles.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills, with the ability to effectively communicate complex technical information.
• Proven ability to work independently and collaboratively in a remote team environment.
• Experience with cloud-based geospatial platforms is a plus.

This fully remote role offers a competitive salary, comprehensive benefits, and the opportunity to contribute to impactful geological discoveries from anywhere.

Job Description
Insight Global is seeking a team of experienced, driven Machine Learning Engineer to join an established health technology company sitting in San Jose, CA. This is a full-time, permanent role with competitive salary, bonus, and comprehensive benefits.
In this role you'll need:
Deep Learning Frameworks: Hands-on experience with PyTorch (main focus) and familiarity with TensorFlow.
Large-Scale Model Training: Exposure to advanced training techniques like Distributed Data Parallel (DDP), Fully Sharded Data Parallel (FSDP), ZeRO, and model parallelism (pipeline/tensor). Experience with distributed training is a strong plus.
Model Optimization: Skilled in improving model performance through techniques like quantization (PTQ, QAT, AWQ, GPTQ), pruning, knowledge distillation, KV-cache tuning, and using efficient attention mechanisms like Flash Attention.
Scalable Model Serving: Understanding of how to deploy models at scale, including autoscaling, load balancing, streaming, batching, and caching. Comfortable working alongside platform engineers to build robust serving pipelines.
Data & Storage Systems: Proficient with both SQL and NoSQL databases, vector databases (e.g., FAISS, Milvus, Pinecone, pgvector), and data formats like Parquet and Delta. Familiar with object storage systems.
Code Quality: Writes efficient, clean, and maintainable code with a focus on performance.
End-to-End ML Lifecycle: Solid grasp of the full machine learning workflow-from data collection and model training to deployment, inference, optimization, and evaluation.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: and Requirements
-3-5 years in ML/AI engineering roles owning training and/or serving in production at scale.
-Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements.
-Experience collaborating across Research, Platform/Infra, Data, and Product functions.
-Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master's preferred (or equivalent industry experience).
-Strong systems/ML engineering with exposure to distributed training and inference optimization.

Our client, a world leader in AI-driven technology solutions, is looking for a highly experienced and innovative Principal Machine Learning Engineer to join their fully remote, high-impact team. This role is crucial for driving the development and deployment of sophisticated machine learning models that power our next-generation products and services. You will be at the forefront of designing, building, and optimizing large-scale ML systems, tackling challenging problems with state-of-the-art techniques. This position requires a deep understanding of machine learning algorithms, data science, and software engineering best practices. As a remote-first employee, you will have the autonomy to work from anywhere in the US, collaborating with a globally distributed team of top-tier engineers and researchers through advanced digital platforms.

Key Responsibilities:

• Design, develop, and implement scalable machine learning models and algorithms for various applications, including predictive analytics, natural language processing, computer vision, and reinforcement learning.
• Lead the end-to-end lifecycle of machine learning projects, from data acquisition and preprocessing to model training, evaluation, deployment, and monitoring.
• Architect and build robust, production-ready ML pipelines and infrastructure to support large-scale data processing and model inference.
• Collaborate with product managers and software engineers to identify opportunities for leveraging ML and integrate ML solutions into existing products.
• Conduct thorough research on state-of-the-art ML techniques and evaluate their applicability to business challenges.
• Optimize model performance, inference speed, and resource utilization for production environments.
• Mentor junior engineers and contribute to the technical growth of the ML team.
• Develop and maintain high-quality, well-documented code and maintainable ML systems.
• Stay current with the latest advancements in the field of machine learning and artificial intelligence.
• Communicate complex technical concepts and findings effectively to both technical and non-technical audiences.

Qualifications:

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, Data Science, or a related quantitative field.
• A minimum of 8 years of professional experience in machine learning engineering or data science, with a strong focus on building and deploying production ML systems.
• Proven expertise in a wide range of ML algorithms and techniques (e.g., deep learning, supervised/unsupervised learning, time series analysis, etc.).
• Proficiency in programming languages such as Python, and deep learning frameworks like TensorFlow, PyTorch, or Keras.
• Strong experience with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark, Dask).
• Experience with MLOps principles and tools for model deployment, monitoring, and management (e.g., Docker, Kubernetes, MLflow).
• Excellent understanding of data structures, algorithms, and software engineering best practices.
• Strong analytical and problem-solving skills with the ability to tackle complex, ambiguous problems.
• Exceptional communication and leadership skills.
• Experience with large-scale data processing and database technologies is a plus.

This is a remote role, empowering you to contribute significantly to groundbreaking AI innovations from **San Jose, California, US**, and anywhere across the United States.

Our client, a pioneering force in scientific research and development, is actively seeking a talented Senior Machine Learning Engineer to join their fully remote, groundbreaking team. This role is at the forefront of innovation, developing cutting-edge AI solutions that drive scientific discovery and advance complex research initiatives. You will be instrumental in designing, implementing, and deploying sophisticated machine learning models and algorithms that tackle some of the most challenging problems in scientific fields. Working remotely, you'll collaborate with a globally distributed team of brilliant researchers and engineers, contributing to projects with significant real-world impact.

Responsibilities:

• Design, develop, and implement advanced machine learning models and algorithms for various scientific applications, including but not limited to data analysis, predictive modeling, and simulation.
• Clean, preprocess, and analyze large-scale scientific datasets to extract meaningful insights and prepare them for model training.
• Train, evaluate, and optimize machine learning models to ensure accuracy, efficiency, and scalability.
• Develop robust and production-ready ML pipelines, ensuring seamless integration with existing research infrastructure.
• Collaborate closely with domain experts, researchers, and other engineers to understand project requirements and translate them into effective ML solutions.
• Stay abreast of the latest advancements in machine learning, deep learning, and relevant scientific domains, and propose innovative approaches.
• Contribute to the development of AI-powered tools and platforms that accelerate research and discovery.
• Document research findings, methodologies, and code thoroughly.
• Participate in code reviews, knowledge sharing sessions, and contribute to the team's technical growth.
• Troubleshoot and debug ML systems, identifying and resolving performance bottlenecks.

Qualifications:

• Master's or Ph.D. in Computer Science, Data Science, Statistics, Physics, Mathematics, or a related quantitative field.
• 5+ years of experience in machine learning engineering, with a proven track record of developing and deploying ML models in production environments.
• Expertise in programming languages such as Python, with extensive experience using ML libraries like TensorFlow, PyTorch, Scikit-learn, etc.
• Strong understanding of various ML algorithms (e.g., regression, classification, clustering, deep learning) and their applications.
• Experience with big data technologies and distributed computing frameworks (e.g., Spark, Hadoop).
• Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps practices.
• Excellent problem-solving skills and the ability to work independently and effectively in a remote setting.
• Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• A passion for scientific research and a desire to contribute to impactful discoveries.

If you are a driven ML expert looking to leverage your skills in a remote, cutting-edge research environment, this is the perfect opportunity for you.

Our client, a groundbreaking technology firm at the forefront of AI innovation, located in the heart of Silicon Valley – **San Jose, California, US**, is seeking an exceptional Senior Machine Learning Engineer. This is a unique opportunity to work on cutting-edge AI applications and contribute to the development of next-generation intelligent systems. You will be responsible for designing, implementing, and deploying advanced machine learning models and algorithms that solve complex real-world problems. The role involves extensive collaboration with data scientists, software engineers, and product managers to bring AI-powered features to life. We are looking for a candidate with a deep understanding of ML principles, strong programming skills in Python, and extensive experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Expertise in areas like deep learning, natural language processing, computer vision, or reinforcement learning is highly desirable. Your responsibilities will include data preprocessing, feature engineering, model training, evaluation, and optimization, as well as deploying models into production environments. You should be adept at translating business requirements into technical solutions and communicating complex technical concepts to non-technical stakeholders. This role offers a hybrid work arrangement, allowing for a blend of focused in-office collaboration and remote flexibility. The ideal candidate is a proactive problem-solver with a passion for pushing the boundaries of AI and a commitment to delivering high-quality, scalable solutions. Join a world-class team and make a significant impact in the rapidly evolving field of artificial intelligence. This position offers competitive compensation, extensive benefits, and opportunities for professional growth and innovation in **San Jose, California, US**.

Responsibilities:

• Design, develop, and implement state-of-the-art machine learning models and algorithms.
• Conduct research and stay abreast of the latest advancements in AI and ML.
• Build and maintain robust data pipelines for model training and evaluation.
• Deploy ML models into production environments and monitor their performance.
• Collaborate with cross-functional teams to define ML project requirements and deliverables.
• Optimize model performance for accuracy, efficiency, and scalability.
• Contribute to the development of MLOps practices and tools.
• Mentor junior engineers and share knowledge within the team.
• Communicate technical findings and recommendations to stakeholders.
• Troubleshoot and resolve issues related to ML systems.

Qualifications:

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
• 5+ years of professional experience in machine learning engineering.
• Proven experience developing and deploying production-level ML models.
• Expertise in Python and major ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong understanding of ML algorithms, statistical modeling, and data mining techniques.
• Experience with cloud platforms (AWS, GCP, Azure) and big data technologies.
• Familiarity with MLOps principles and tools is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work effectively in a hybrid work environment.

Our client is seeking a highly accomplished Principal Machine Learning Engineer to join their innovative team in San Jose, California, US . This leadership role will be instrumental in driving the development and deployment of cutting-edge machine learning models and AI solutions across our product suite. You will tackle complex challenges, from data acquisition and preprocessing to model training, evaluation, and productionization. The ideal candidate possesses a deep theoretical understanding of ML algorithms, a proven track record of building and deploying scalable ML systems, and a passion for pushing the boundaries of artificial intelligence. Responsibilities include designing and implementing advanced ML algorithms and frameworks; leading the development lifecycle for ML projects from conception to deployment; collaborating with software engineers and product managers to integrate ML capabilities into our offerings; conducting rigorous experimentation and statistical analysis to validate model performance; optimizing models for performance, scalability, and efficiency; mentoring junior engineers and contributing to the technical vision of the ML team; staying abreast of the latest research and trends in AI and ML; and contributing to our intellectual property through publications or patents. A Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field is required, along with 8+ years of experience in machine learning or a related field. Deep expertise in Python, along with common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn), is essential. Experience with large-scale data processing frameworks (e.g., Spark) and cloud ML platforms (e.g., AWS SageMaker, GCP AI Platform) is highly desirable. Strong understanding of software engineering best practices, including version control, CI/CD, and testing, is expected. Excellent communication and leadership skills are crucial for influencing technical direction and collaborating effectively across teams in this hybrid role.