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Contract Tensorflow Jobs in Minnesota (NOW HIRING)

Collaborate with Data Engineering on feature pipelines and data contracts. * Own production health ... Python, TensorFlow, PyTorch, Docker, REST APIs

AI/ML Engineer Duration: 3-month contract (Could be extended for 6 months before conversion ... TensorFlow) Experience building and deploying end-to-end ML/AI systems Ability to take solutions ...

This remote contract-to-hire position will be originated in Eagan, MN. * SELECTED CANDIDATES ... TensorFlow, or Scikit-learn. * Expertise in deploying Python applications in Cloud service ...

Contract Tensorflow information

Which 5 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as contract TensorFlow roles involving AI model development, data science, software engineering, AI research, and machine learning engineering, are likely to persist. These roles demand specialized skills, continuous learning, and adaptability to evolving AI tools and frameworks.

What has replaced TensorFlow?

For a Contract TensorFlow role, there is no single direct replacement, but alternatives like PyTorch have gained popularity in machine learning and deep learning projects. Many organizations now adopt PyTorch or other frameworks depending on project requirements, and knowledge of multiple tools can be beneficial for such roles.

What kind of jobs use TensorFlow?

Jobs that use TensorFlow typically include machine learning engineer, data scientist, AI researcher, and deep learning developer roles. These positions involve developing, training, and deploying neural network models for tasks such as image recognition, natural language processing, and predictive analytics, often requiring knowledge of Python and related frameworks.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like Contract TensorFlow developers, tend to offer high salaries due to the specialized skills required, such as programming in Python and experience with frameworks like TensorFlow. Compensation varies based on experience, location, and project complexity, but generally, ML jobs are among the higher-paying roles in the tech industry.

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 are the most commonly searched types of Tensorflow jobs in Minnesota? The most popular types of Tensorflow jobs in Minnesota are:
What are popular job titles related to Contract Tensorflow jobs in Minnesota? For Contract Tensorflow jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Contract Tensorflow jobs? Cities in Minnesota with the most Contract Tensorflow job openings:
Infographic showing various Contract Tensorflow job openings in Minnesota as of June 2026, with employment types broken down into 4% Internship, 4% As Needed, 88% Full Time, and 4% Nights. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.
ML Engineer

ML Engineer

Centraprise

Minneapolis, MN • On-site

Contractor

Posted yesterday


Job description

Job Description:
  • Translate data science prototypes into production-grade ML services and pipelines.
  • Build training and inference code with reproducibility, versioning, and automated testing.
  • Implement scalable model serving (online/offline), batching, and latency/throughput optimization.
  • Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).
  • Collaborate with Data Engineering on feature pipelines and data contracts.
  • Own production health: drift detection, performance regression, rollback strategies, and incident response."
  • 5+ years software engineering with 2+ years shipping ML models to production.
  • Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
  • Experience with containers and orchestration (Docker/Kubernetes) and API development.
  • Understanding of ML system design (data leakage, training-serving skew, drift).
  • CI/CD and DevOps practices applied to ML workloads (MLOps).
  • Experience with feature stores, model registries, and model monitoring stacks.
  • GPU optimization and distributed training experience.
  • Experience with responsible AI toolkits and compliance requirements."
  • Python, TensorFlow, PyTorch, Docker, REST APIs