TensorFlow

TensorFlow Engineer Jobs

99 jobs found

17d ago

Machine Learning Engineer/Scientist

Precise Systems Edgewood, MD

Edgewood, MD

17d ago

$77k - $115k/yr Full time Ai Ml Artificial Intelligence Data Science

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Job Description

Precise Systems is seeking a Machine Learning Engineer/Scientist to support chemical and biological defense projects by building and validating ML-driven insights for laboratory automation.

Responsibilities

Perform end-to-end work on machine learning model research, development, testing, and evaluation for chemical and biological datasets under guidance of senior professionals.
Support chemical and biological R&D efforts by applying data science to help develop modern solutions to outpace emerging threats.
Partner with interdisciplinary teams to design machine learning solutions for biological and chemical challenges.
Develop and apply state-of-the-art ML tools and algorithms to optimize DoD research efforts.
Conduct internal verification and validation of models and code to support real laboratory deployment readiness.
Create dashboards and/or graphical user interfaces that support laboratory automation for experimentation workflows.
Analyze biological or chemical data using Python and R to produce mathematical insights and improve system performance.
Use DevSecOps and MLOps to integrate machine learning processes into secure data pipelines used in laboratory settings.
Collaborate with academic and industry partners to test and refine algorithms and biological systems in varied environments.
Carry out ongoing research to keep models and analysis current with latest advancements.

Requirements

Master’s degree in Computer Science, Computer Engineering, Computational Biology, or Bioinformatics.
OR Bachelor’s degree in a relevant field with 5 years of experience in a laboratory and/or computational environment.
3 years of experience in a laboratory and/or computational environment.
Hands-on experience applying machine learning algorithms and data science techniques to physical science problems.
Proficiency in Python and other programming languages commonly used for machine learning and data analysis.
Familiarity with physical science and laboratory experience.
Proficiency with software development approaches such as agile, git, DevSecOps, and/or MLOps.
Advanced communication skills for working with interdisciplinary teams, government representatives, and industry partners.
Willingness to learn new technologies and take on new challenges.
Strong written and oral communication, excellent interpersonal skills, and proficiency in PC software packages for data analysis and visualization.

Technologies

Python
R
DevSecOps
MLOps
git
agile
TensorFlow
PyTorch
PC software packages

Preferred

Ph.D. in Computational Biology/Chemistry, Machine Learning, Physical Sciences, or a related field with 1 year of experience in a laboratory and/or computational environment.
Expertise in advanced ML frameworks (e.g., TensorFlow, PyTorch) applied to biological data.
Experience with bioinformatics tools and databases.
Experience performing wet laboratory experimentation to validate software and models.
Knowledge of automation systems and robotics for laboratory workflows.
Collaboration experience with academic and industry partners on synthetic biology and machine learning projects.

Compensation

Salary range: $76,709.46 - $115,064.18 (annualized USD).
Compensation determined by education, experience, skills, competencies, and contract-specific requirements.
Salary is one component of Precise Systems’ total compensation package.

Benefits

Health insurance
Life and accidental death and dismemberment coverage
Disability insurance
Retirement plans
Holiday pay
Employee-managed leave
Professional growth opportunities

Location: Edgewood, MD (onsite)

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18d ago

Machine Learning Engineer

Cognizant New York, NY

New York, NY

18d ago

$110k - $135k/yr Full time Agentic Ai Ai Agent Ai Agent Platform

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Job Description

Cognizant is hiring a Machine Learning Engineer (Agentic AI) for a hybrid role in New York, NY. This position focuses on building and improving agentic AI systems and machine learning solutions that work reliably in production environments, while partnering across Data Science, Product, Engineering, and DevSecOps.

The anticipated annual salary is $110,000 to $135,000, depending on experience, qualifications, geographic location, skills, and other job-related factors. The role may also be eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to plan terms.

You will also have access to health and wellbeing support, retirement savings with company contributions (subject to plan provisions), paid time off, and professional development opportunities, including training and certification.

What you’ll do

Design, develop, deploy, and optimize machine learning models and Agentic AI systems to address real-world business challenges.
Collaborate with Data Science, Product, Engineering, and DevSecOps teams to deliver scalable, secure, production-ready AI solutions.
Build and maintain cloud-native AI applications, including data ingestion pipelines, memory frameworks, and model-serving architectures.
Apply MLOps and AgentOps best practices such as automated testing, CI/CD or CI/CD/CT pipelines, monitoring, observability, and model governance.
Drive continuous improvement by evaluating emerging technologies and applying engineering best practices across AI development projects.

What you bring

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent professional experience).
Experience designing, developing, deploying, and supporting machine learning applications in enterprise environments.
Strong programming skills in Python and SQL, with exposure to C++ preferred.
Experience with ML and deep learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
Solid software engineering fundamentals, including object-oriented programming, RESTful APIs, microservices, testing, version control, and system design.
Experience deploying ML solutions in cloud-based environments.
Familiarity with CI/CD and automated deployment practices, model versioning, and monitoring frameworks.
Knowledge of data engineering concepts including ETL, Spark/PySpark, distributed processing, and large-scale data environments.
Strong communication, problem-solving, and collaboration skills, including experience in Agile development environments.

Technologies you may work with

Python, SQL, C++, TensorFlow, PyTorch, scikit-learn, RESTful APIs, microservices, CI/CD pipelines, CI/CD/CT pipelines, MLOps, AgentOps, ETL, Spark, PySpark, MLFlow, Amazon SageMaker Pipelines, GitHub Actions, Jenkins, CloudBees, LLM development tools, AI-assisted software engineering platforms, relational databases, NoSQL databases, and graph databases.

Benefits and support

Medical, dental, and vision insurance
Health Savings Account (HSA) and Flexible Spending Accounts (FSA), where applicable
Company-paid life insurance and disability coverage
401(k) retirement savings plan with company contributions, subject to plan provisions
Paid time off, company holidays, and leave programs
Employee Assistance Program (EAP)
Wellbeing and mental health resources
Professional development, training, and certification opportunities
Career growth and internal mobility programs
Associate recognition and reward programs

Work model

Hybrid role requiring 3 days per week in a client or Cognizant office in New York, New York.

These can help you stand out

Experience developing Agentic AI applications and autonomous AI workflows
Familiarity with Agent Development Life Cycle (ADLC) methodologies and observability frameworks
Experience using LLM development tools and AI-assisted software engineering platforms
Knowledge of MLFlow, Amazon SageMaker Pipelines, GitHub Actions, Jenkins, CloudBees, or similar MLOps technologies
Understanding of model governance, explainability, drift detection, bias monitoring, and AI risk management practices
Experience working with relational, NoSQL, and graph databases
Knowledge of statistics, probability, linear algebra, predictive analytics, and machine learning optimization techniques
Passion for continuous learning and staying current with emerging AI technologies

Application details

Applications will be accepted until September 30, 2026.

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19d ago

AI Engineer

Microsoft Redmond, WA

Redmond, WA

19d ago

$83 - $94/hr Contract Ai Ml Artificial Intelligence Azure Machine Learning

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Job Description

Build and maintain AI and machine learning systems for embodied robotics research with simulation and robotic hardware.

Responsibilities

Fine-tune and improve sophisticated software implementation projects
Architect, design, and implement test automation infrastructure
Develop training and evaluation pipelines using Azure Machine Learning
Analyze and refine training datasets for robotic and AI applications
Create tools that support rapid deployment of novel algorithms in simulation and on hardware
Integrate robotic control and perception stacks with simulation frameworks
Adapt server and client code for new robotic or simulation APIs during system integration
Collect and convert demonstration data into correct formats for model training
Launch and monitor fine-tuning runs for vision-language-action and diffusion models

Requirements

5–7 years of related experience in AI engineering, machine learning, or robotics
Demonstrated experience integrating robotic control and perception stacks with simulation frameworks
Hands-on experience developing and maintaining training and evaluation pipelines
Experience working with robotic hardware or simulation environments in a research or production context
Master’s degree in Computer Science, Computer Engineering, or a related technical field (required)
PhD-level academic work or studies in a robotics lab (strongly preferred)
Python proficiency (5+ years)
PyTorch hands-on experience (2+ years)
ROS2 experience (1+ year)
Solid foundation in data structures, algorithms, and software design
Experience with machine learning frameworks such as TensorFlow or PyTorch
Familiarity with training robotic models including vision-language-action models, diffusion models, and reinforcement learning policies
Experience with simulation environments or robotic hardware for system integration
Experience performing in-depth troubleshooting and unit testing on new and legacy production systems
Strong problem diagnosis and resolution skills

Technologies

Azure Machine Learning
Python
PyTorch
ROS2
TensorFlow

Benefits

Medical, dental & vision
Hospital plans
401(k) Retirement Plan: pre-tax and Roth post-tax contributions available
Life Insurance: company paid Basic Life and AD&D; voluntary Life & AD&D for employee and dependents
Company paid short and long-term disability
Health & Dependent Care Spending Accounts (HSA & DCFSA)
Employee Assistance Program
Time Off/Leave: PTO, Allegis Group Paid Family Leave, Parental Leave

Job Details

Location: Redmond, WA (onsite)
Job type: Contract
Duration: 13 months
Weekly schedule: 40 hours
Status: Non-Exempt
Pay range: $83.50 - $94.50 per hour
Application deadline: Apply within 72 hours of the posting date to ensure consideration

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19d ago

AI Engineer

Chase Robotics and Ai Rocklin, CA

Rocklin, CA

19d ago

Up to $200k/yr Full time Ai Ml Artificial Intelligence Big Data

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Job Description

Chase Robotics and Ai is hiring an AI Engineer based in Rocklin, CA for a hybrid setup. In this role, you will design, build, and deploy advanced AI models and machine learning frameworks, with a focus on scalable data systems and production-ready integration across cloud environments.

The work blends model development with large-scale data engineering, statistical analysis, and collaboration on applications such as natural language processing and generative AI solutions.

Responsibilities

Develop, train, and evaluate machine learning models using frameworks such as TensorFlow to support accurate and efficient outcomes for diverse applications.
Design and implement scalable big data systems with tools such as Hadoop, Spark, and ETL processes to handle large datasets effectively.
Use statistical modeling and analysis methods with R, SAS, and statistical analysis software to derive meaningful insights from complex data.
Integrate AI models into production by applying deployment strategies that prioritize robustness and scalability across AWS cloud platforms.
Collaborate with cross-functional teams to build NLP applications and generative AI solutions aimed at improving user engagement.
Run model training cycles focused on predictive modeling analysis, model evaluation, and continuous improvement.
Use SQL databases, data mining techniques, and database design principles to improve data storage and retrieval for analytics.

Requirements

Proven experience in machine learning and AI-driven analysis, including a strong understanding of AI implementation in real-world scenarios.
Hands-on experience with machine learning frameworks such as TensorFlow, Spark MLlib, or similar tools.
Familiarity with big data systems, including components in the Hadoop ecosystem such as HDFS and MapReduce, along with Spark for large-scale processing.
Programming experience in Python, Java, C, VBA, and Bash (Unix shell), plus additional knowledge of SQL for database management.
Experience with cloud-based machine learning services on AWS (or similar providers) is highly desirable.
Knowledge of NLP, predictive modeling analysis, statistical analysis tools, and model evaluation techniques.
Understanding of analytics workflows involving data mining, data integration via Talend, visualization using Looker, and considerations for data scalability.

Salary: USD 200,000 per year.

Technologies: TensorFlow, Hadoop, Spark, ETL, R, SAS, statistical analysis software, AWS, NLP, SQL, data mining techniques, database design principles, Spark MLlib, HDFS, MapReduce, Python, Java, C, VBA, Bash (Unix shell), Talend, Looker

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19d ago

Staff Machine Learning Engineer

PayPal Austin, TX

Austin, TX

19d ago

$179k - $265k/yr Full time Ai Ml Artificial Intelligence Cloud

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Job Description

The role focuses on leading the end-to-end work of advanced machine learning, from model design through production deployment, while working closely with data scientists, software engineering, and product partners. This position is based in Austin, TX and follows a hybrid work arrangement.

Location and Compensation

Primary Location: San Jose, California | $196,500.00 - $291,500.00 annually
Additional Location: Austin, Texas (hybrid) | $178,500 - $265,100 per year

Travel: 0%

Role Summary

Serve as a technical leader responsible for the design, development, and implementation of advanced machine learning models and algorithms to address complex business problems. Establish scalable machine learning pipelines, maintain high data quality standards, and support the deployment of models into production systems. Coordinate across disciplines to ensure models are integrated effectively into products and services.

Responsibilities

Lead the development and optimization of advanced machine learning models.
Oversee preprocessing and analysis for large datasets.
Deploy and maintain machine learning solutions in production environments.
Collaborate with cross-functional teams to integrate machine learning models into products and services.
Monitor and evaluate deployed model performance, then apply necessary adjustments.

Required Qualifications

5+ years of relevant experience and a Bachelor’s degree, or an equivalent combination of education and experience.
Extensive experience with machine learning frameworks including TensorFlow, PyTorch, or scikit-learn.
Expertise in cloud platforms including AWS, Azure, or GCP, along with tools for data processing and model deployment.

Technical Skills

Machine Learning: TensorFlow, PyTorch, scikit-learn
Cloud Platforms: AWS, Azure, GCP

Benefits

Comprehensive, choice-based programs supporting personal wellbeing across physical, emotional, and financial areas
Generous paid time off
Healthcare coverage for you and your family
Resources to create financial security
Support for mental health

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23d ago

Machine Learning Engineer

Molex Lisle, IL

Lisle, IL

23d ago

$170k - $250k/yr Full time Python Artificial Intelligence Azure Gpu Compute

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Job Description

Work onsite in Lisle, IL to accelerate engineering design cycles by delivering physics-informed machine learning surrogates on Azure.

Responsibilities

Design and train surrogate models, including neural networks, Gaussian processes, gradient-boosted trees, and GNNs/PINNs
Train on Azure GPU compute using ND/NC series resources
Apply physics-informed constraints to keep predictions physically valid, beyond purely statistical fit
Create model-uncertainty and confidence scoring to determine which candidate designs require full simulation validation
Retrain surrogate models as new simulation results become available
Deploy and manage model lifecycle using Azure ML endpoints and model registry
Monitor deployed models for drift on a rolling basis
Benchmark surrogate runtime versus full simulation to guide platform-level performance tuning
Partner with data scientists and MLOps teams to productionize and operationalize model workflows

Requirements

Extensive hands-on experience building, training, and deploying ML models in production (not limited to pretrained API usage)
10+ years building ML for physical or engineering systems, including surrogate modeling and physics-informed or scientific ML
Strong Python experience with PyTorch or TensorFlow
Understanding of engineering/physics fundamentals and relevant simulation data formats in your domain
Experience with Azure Machine Learning or a similar cloud ML platform
Familiarity with uncertainty quantification, including Bayesian approaches and ensembling

Technologies

Azure Machine Learning
Azure GPU compute (ND/NC series)
Python
PyTorch
TensorFlow
Azure ML endpoints
Model registry
Neural networks
Gaussian processes
Gradient-boosted trees
GNNs
PINNs
Bayesian approaches
Ensembling
GPU-heavy training

Benefits

Medical, dental, and vision coverage
Flexible spending and health savings accounts
Life insurance
ADD
Disability coverage
Retirement benefits
Paid vacation/time off
Educational assistance
May also include infertility assistance
Paid parental leave
Adoption assistance

Who You’ll Work With (Highlights)

Data scientists and MLOps teams

Who Will Put You Ahead

Direct experience with industry-standard EM or physics simulation tools
Geometric deep learning experience, including graph neural networks and mesh-based models for CAD data
Background in RF/high-speed electronics or interconnect design

Location: Lisle, IL 60532 (onsite)

Compensation: USD 170,000 - 250,000 per year

Experience: 10+ years

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23d ago

Applied AI/Machine Learning Engineer

Oddball McLean, VA

McLean, VA

23d ago

$150k - $200k/yr Full time Ai Ml Artificial Intelligence Data & Ai

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Job Description

Join Oddball to design, build, and deploy applied AI and machine learning capabilities that move from experimentation to real production impact. This hybrid role in McLean, VA supports modern ML and GenAI workflows across model development, evaluation, and iteration, with cross-functional collaboration to integrate AI into user-facing systems.

What you’ll do

Design, develop, and deploy machine learning and AI-powered features into production systems
Use supervised, unsupervised, and deep learning approaches with structured and unstructured data
Build and evaluate models for tasks including classification, ranking, prediction, NLP, and anomaly detection
Develop and integrate GenAI solutions such as LLM-based workflows, retrieval-augmented generation, and agents
Translate business and user needs into ML problem statements, metrics, and experiments
Implement data pipelines and feature engineering workflows for both training and inference
Evaluate performance while considering bias, drift, and reliability, then iterate based on results
Collaborate with software engineers to integrate models into APIs, services, and user-facing applications
Contribute to architecture decisions for model serving, scalability, and cost optimization
Document approaches, assumptions, and tradeoffs to support maintainability and knowledge sharing

Skills and experience

Strong foundation in machine learning concepts, including model selection, training, validation, and evaluation
Experience building and deploying ML models in real-world applications
Proficiency in Python and common ML libraries such as PyTorch, TensorFlow, and scikit-learn
Experience working with large language models, embeddings, and prompt-driven systems
Familiarity with data processing workflows and tools such as Pandas, SQL, Spark, or similar
Understanding of software engineering best practices including version control, testing, and code reviews
Ability to reason about tradeoffs between accuracy, latency, cost, and maintainability
Strong communication skills and comfort working in cross-functional teams
Performs other related duties as assigned

Bonus if you have

Experience in innovation, R&D, labs, or exploratory engineering teams
Experience deploying models to cloud platforms and managing inference at scale
Familiarity with MLOps practices such as model monitoring, CI/CD for ML, and experiment tracking
Experience contributing to architectural discussions or technical strategy

Technologies you may work with

Python, PyTorch, TensorFlow, scikit-learn, LLM-based workflows, retrieval-augmented generation, Pandas, SQL, Spark, APIs, and services.

Location

Hybrid/Remote, with occasional in-office collaboration
Candidates must be located in the DMV area (DC, Maryland, Virginia)
Work Location: Hybrid remote in McLean, VA 22102

Authorization and eligibility

Applicants must be authorized to work in the United States. In alignment with federal contract requirements, certain roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or a security clearance.