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Tensorflow Pytorch Jobs in Massachusetts (NOW HIRING)

Eisneramper Llp

AI Solution Architect

Boston, MA · On-site +1

$68.50 - $90.25/hr

TensorFlow, PyTorch, Scikit-learn, Transformers * Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper:

Lindsay & Brownell

AI Solution Architect

Boston, MA · On-site +1

$68.50 - $90.25/hr

TensorFlow, PyTorch, Scikit-learn, Transformers * Vector Databases: Azure Cosmos DB, Pinecone, or Weaviate * DevOps & MLOps: Azure DevOps, GitHub Actions, Docker, Kubernetes About EisnerAmper:

Axon

Senior Machine Learning Scientist

Boston, MA

$99K - $135K/yr

Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar. * Solid grounding in software engineering fundamentals, data structures, and algorithms.

Adidev Technologies Inc

ML/AI Engineers

Boston, MA · Remote

Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks Experience putting ML/AI into production, and ability to talk through best practices and pitfalls. How ...

Humana

VP, Applied AI Solutions

Boston, MA · Remote

Strong understanding of AI technologies, frameworks, and tools (e.g., TensorFlow, PyTorch, etc.). * Excellent leadership, communication, and interpersonal skills, with the ability to influence at all ...

Conga

Staff Data Scientist (AI/ML)

Boston, MA · On-site

Deep expertise in Python and frameworks such as TensorFlow, PyTorch, Scikit-learn, Pandas, and LangChain. * Advanced knowledge of machine learning algorithms, statistical modeling, experimentation ...

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Tensorflow Pytorch information

What are the key skills and qualifications needed to thrive as a Deep Learning Engineer specializing in TensorFlow and PyTorch, and why are they important?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.
What are popular job titles related to Tensorflow Pytorch jobs in Massachusetts? For Tensorflow Pytorch jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Massachusetts look for? The top searched job categories for Tensorflow Pytorch jobs in Massachusetts are:
What cities in Massachusetts are hiring for Tensorflow Pytorch jobs? Cities in Massachusetts with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you
Infographic showing various Tensorflow Pytorch job openings in Massachusetts as of June 2026, with employment types broken down into 84% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.
Research Technology Specialist - Human Nutrition Research Center on Aging

Research Technology Specialist - Human Nutrition Research Center on Aging

Tufts University

Boston, MA • On-site

$79K - $119K/yr

Full-time

Posted 21 days ago

Key responsibilities

  • Design, implement, and maintain reproducible data pipelines for research studies in nutrition, aging, and health span.

  • Support the integration, cleaning, harmonization, and analysis of complex datasets, including clinical, dietary, behavioral, wearable, sensor, imaging, metabolomic, microbiome, genetic, epigenetic, and other biomarker data.

  • Develop and apply computational, statistical, and machine learning approaches to identify patterns of individual variability in response to diet, lifestyle, and environmental exposures.

Tufts University rating

8.2

Company rating: 8.2 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

113th of 544 rated colleges and universities

Job description

Overview
The Jean Mayer USDA Human Nutrition Research Center on Aging (HNRCA) at Tufts University is an internationally recognized leader in the study of nutrition and its role in healthy aging. Our multidisciplinary research spans molecular biology, clinical trials, epidemiology, behavioral science, and data science. The HNRCA is committed to developing precision nutrition strategies that optimize health span and functional independence in diverse aging populations. Collaborating across academic, governmental, and industry sectors, the Center fosters innovation and translational impact through state-of-the-art research infrastructure and scientific expertise.
What You'll Do
This is a grant funded position and is not eligible for severance pay.
The Research Technology Specialist will provide technical, computational, and analytical expertise to support research at the intersection of precision nutrition, healthy aging, artificial intelligence, wearable technologies, and biomedical data science.
This position will contribute to data-rich research projects involving human studies, observational cohorts, lifestyle interventions, biomarker analytics, wearable and sensor-derived data, and high-dimensional omics datasets. The successful candidate will work closely with HNRCA scientists, trainees, and other collaborators to develop, implement, and refine computational tools that transform complex biological, behavioral, and environmental data into actionable scientific insights.
The role is intended for an individual who can bridge biomedical research and advanced analytics, contributing both hands-on technical implementation and scientific interpretation. The position will support federally funded and collaborative research initiatives focused on precision nutrition, aging, cardiometabolic health, functional resilience, and individualized responses to diet and lifestyle interventions
  • Design, implement, and maintain reproducible data pipelines for research studies in nutrition, aging, and health span.
  • Support the integration, cleaning, harmonization, and analysis of complex datasets, including clinical, dietary, behavioral, wearable, sensor, imaging, metabolomic, microbiome, genetic, epigenetic, and other biomarker data.
  • Develop and apply computational, statistical, and machine learning approaches to identify patterns of individual variability in response to diet, lifestyle, and environmental exposures.
  • Build, test, and deploy prototype tools for data collection, monitoring, signal processing, visualization, and decision support in human research studies. Help establish best practices for data documentation, reproducibility, code management, data security, and compliance with human-subject research requirements.
  • Analyze physiological, behavioral, spatial, or time-series data generated from wearable devices, mobile health tools, biosensors, GPS, accelerometers, continuous glucose monitors, or related platforms.
  • Contribute to predictive modeling efforts aimed at identifying biological or behavioral subgroups, risk trajectories, and individualized intervention responses.
  • Collaborate with faculty, trainees, statisticians, engineers, and biomedical researchers to ensure rigorous study design, appropriate data analysis, and meaningful interpretation of findings. Serve as a technical liaison between computational teams and biomedical investigators, helping translate research questions into analytical workflows and interpretable results.
  • Contribute to scientific manuscripts, conference abstracts, grant applications, progress reports, and presentations. Generate high-quality technical reports, dashboards, visualizations, and summaries to support publications, grant proposals, internal decision-making, and external presentations.

What We're Looking For
Basic Requirements:
Knowledge and experience typically acquired by:
  • Bachelor's Degree in biomedical engineering, computer science, data science, electrical engineering, bioinformatics, biostatistics, computational biology, applied mathematics, or a related quantitative or technical field.
  • 3 years of relevant experience in data analytics, computational research support, biomedical data science, digital health, human performance research, nutrition, aging, neuroscience, public health, or related fields.
  • Proficiency in Python and commonly used scientific computing and data science libraries, such as Pandas, NumPy, SciPy, scikit-learn, TensorFlow, PyTorch, Matplotlib, Seaborn, or related tools.
  • Experience working with complex, messy, or high-dimensional research datasets.
  • Familiarity with statistical modeling, machine learning, signal processing, or time-series analysis.
  • Ability to communicate technical findings clearly to both computational and non-computational scientific audiences.
  • Strong organizational skills and ability to work collaboratively across multidisciplinary teams.

Preferred Qualifications:
  • Master's Degree in biomedical engineering, computer science, data science, bioinformatics, biostatistics, computational biology, quantitative public health, nutrition science, or a related field.
  • Experience analyzing wearable sensor data, mobile health data, accelerometry, continuous glucose monitoring, physiological signals, GPS/location data, or other free-living behavioral data.
  • Experience with cloud computing, Git/GitHub, reproducible workflows, database management, REDCap, SQL, R, or workflow management tools.
  • Experience with multi-omics or biomarker datasets, including metabolomics, proteomics, microbiome, genomics, epigenomics, or lipidomics.
  • Experience contributing to peer-reviewed manuscripts, grant proposals, technical reports, or scientific presentations.
  • Familiarity with nutrition, aging biology, cardiometabolic health, frailty, resilience, cognitive aging, or health span research.
  • Familiarity with AI/ML applications in precision nutrition, digital health, public health, gerontology, or personalized medicine.
  • Ability to develop user-friendly visualizations, dashboards, or prototype research tools.
  • Knowledge of data governance, privacy, security, and regulatory considerations relevant to human-subject biomedical research.

Pay Range
Minimum $79,600.00, Midpoint $99,600.00, Maximum $119,500.00
Salary is based on related experience, expertise, and internal equity; generally, new hires can expect pay between the minimum and midpoint of the range.

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