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Contract Tensorflow Jobs in Massachusetts (NOW HIRING)

ICONSTAFF

Machine Learning Engineer

Cambridge, MA · On-site +1

Spun out of MIT and backed by DoD contracts, we are building breakthrough AI and autonomy solutions ... Proficiency with PyTorch or TensorFlow. * Strong coding skills in Python or C++ (ideally both)

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

This includes defining the data contracts for model inputs/outputs and implementing the MLOps ... Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar

Xometry

Staff Machine Learning Engineer

Waltham, MA · On-site

This includes defining the data contracts for model inputs/outputs and implementing the MLOps ... Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar

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All JobsContract Tensorflow JobsContract Tensorflow Jobs in Massachusetts

Contract Tensorflow information

What is the difference between Contract Tensorflow vs Contract Machine Learning Engineer?

AspectContract TensorflowContract Machine Learning Engineer
Required CredentialsProficiency in TensorFlow, Python, ML conceptsProficiency in ML frameworks, Python, data analysis
Work EnvironmentProject-based, remote or on-site, tech companiesProject-based, tech or research firms, collaborative teams
Employer & Industry UsageTech companies, startups, AI-focused firmsTech companies, consulting firms, research institutions
Search & Comparison IntentUnderstanding TensorFlow-specific roles, contract workBroader ML roles, contract opportunities in ML

Contract Tensorflow roles focus specifically on implementing and optimizing models using TensorFlow, requiring expertise in this framework. Contract Machine Learning Engineer positions encompass a wider range of ML tools and techniques, often including TensorFlow but also other frameworks. Both roles are project-based, typically in tech environments, but Contract Tensorflow is more specialized in deep learning with TensorFlow.

What jobs use Contract Tensorflow?

Jobs that use Contract TensorFlow typically include machine learning engineer, data scientist, AI developer, and research scientist roles. These positions involve developing, training, and deploying machine learning models using TensorFlow, often requiring skills in Python, deep learning, and cloud platforms. Contract roles may be project-based or temporary, focusing on specific AI or data analysis tasks.

What are popular job titles related to Contract Tensorflow jobs in Massachusetts?

For Contract Tensorflow jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Contract Tensorflow jobs in Massachusetts look for?

The top searched job categories for Contract Tensorflow jobs in Massachusetts are:

What cities in Massachusetts are hiring for Contract Tensorflow jobs?

Cities in Massachusetts with the most Contract Tensorflow job openings:

Contract Tensorflow jobs near you

Contract Research Scientist, Computational Biology & AI/ML

Boston, MA • On-site

Commonwealth Sciences, Inc.
Recruiting and Staffing Services • 1 - 10 employees
Learn more about Commonwealth Sciences, Inc.external

$38.25 - $48/hr

Other

Posted 8 days ago

Job description

Position located in Boston, MA


Responsibilities:


  • Develop and apply machine learning and computational modeling approaches to accelerate therapeutic discovery across oligonucleotide and biologic platforms.
  • Build predictive and generative models to support antibody engineering, including antibody–antigen interaction modeling, sequence analysis, structural prediction, and de novo protein design.
  • Apply AI/ML techniques to identify and rank promising ASO candidates based on sequence characteristics, target accessibility, exon-skipping activity, and other relevant biological parameters.
  • Develop computational strategies for optimizing antibodies, antigens, ADCs, oligonucleotides, and other emerging therapeutic modalities against multiple design objectives.
  • Create scalable, reproducible workflows spanning data preparation, feature generation, model development, training, evaluation, and implementation.
  • Integrate sequence, structural, biochemical, and experimental datasets from internal programs, published literature, and external sources to improve model performance and biological insight.
  • Investigate and incorporate relevant molecular descriptors, including sequence motifs, thermodynamic properties, structural accessibility, secondary structure, binding characteristics, and other predictive features.
  • Establish rigorous model evaluation, benchmarking, and validation strategies and work closely with laboratory scientists to test computational predictions experimentally.
  • Assess emerging AI/ML methodologies, commercial platforms, open-source packages, and protein/oligonucleotide modeling technologies for potential integration into discovery workflows.
  • Develop well-structured, maintainable code and computational documentation that enables scientists across multidisciplinary teams to effectively use and interpret modeling tools.
  • Communicate computational findings, model performance, and design recommendations to scientists and project teams and contribute to data-driven therapeutic development strategies.


Requirements:


  • PhD in Computational Biology, Computational Chemistry, Machine Learning, Bioengineering, Chemical Engineering, Biomedical Engineering, or a closely related quantitative discipline, with at least 3 years of relevant industry experience.
  • Demonstrated experience applying computational methods to protein, antibody, DNA, RNA, or oligonucleotide design, preferably within a drug discovery or biotechnology environment.
  • Strong understanding of antibody engineering and computational approaches for analyzing antibody–antigen sequence, structure, binding, and interaction properties.
  • Experience developing or applying advanced machine learning methodologies, including deep neural networks, transformers, graph-based models, protein language models, generative models, or related approaches.
  • Hands-on experience using AI/ML to solve biological or molecular design problems, including predictive modeling, sequence analysis, structure prediction, or optimization.
  • Knowledge of oligonucleotide therapeutics, ASOs, RNA biology, exon skipping, siRNA, PMO/gapmer chemistry, or related modalities is highly desirable.
  • Strong programming capabilities in Python, with experience in one or more additional languages such as R or SQL.
  • Proficiency with modern machine learning and scientific computing frameworks such as PyTorch, TensorFlow, scikit-learn, JAX, or comparable technologies.
  • Experience working with large biological datasets and integrating sequence, structural, experimental, and literature-derived information for computational modeling.



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