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Tensorflow Jobs in Minnesota (NOW HIRING)

OATI

AI Engineer

Bloomington, MN · On-site

$100K - $150K/yr

Develop and implement machine learning models using popular frameworks (e.g., TensorFlow, PyTorch) to analyze and extract meaningful insights from power system data. * Participate in the full ...

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Tensorflow information

See Minnesota salary details

$36.7K

$120.2K

$192.5K

How much do tensorflow jobs pay per year?

As of Jun 26, 2026, the average yearly pay for tensorflow in Minnesota is $120,211.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,500.00 and $133,200.00 per year, depending on experience, location, and employer.

What kind of jobs use TensorFlow?

Jobs that use TensorFlow typically include machine learning engineer, data scientist, AI researcher, and deep learning engineer. These roles involve developing, training, and deploying neural network models, often requiring programming skills in Python and knowledge of machine learning frameworks. TensorFlow is widely used in industries such as technology, healthcare, finance, and automotive for tasks like image recognition, natural language processing, and predictive analytics.

What is a TensorFlow job?

A TensorFlow job typically involves developing, training, and deploying machine learning models using TensorFlow, an open-source AI framework. Responsibilities may include data preprocessing, building neural networks, optimizing model performance, and integrating models into applications. These roles are common in industries like healthcare, finance, and autonomous systems, requiring skills in Python, deep learning, and TensorFlow's ecosystem.

Which 3 jobs will survive AI?

TensorFlow professionals, data scientists, and AI engineers are likely to continue thriving as AI advances, since their roles involve developing, training, and maintaining machine learning models. These jobs require specialized skills in programming, mathematics, and understanding of AI frameworks, making them less susceptible to automation. Continuous learning and certification in AI tools can help ensure job security in this evolving field.

What job makes $10,000 a month without a degree?

In the field of TensorFlow and machine learning, roles such as freelance AI developer, data scientist, or machine learning engineer can earn $10,000 or more per month with strong skills and experience, often without a formal degree. These positions typically require proficiency in programming, deep learning frameworks, and project portfolios, and may involve remote work or contract-based projects.

What are typical daily responsibilities for someone working in a TensorFlow Developer role?

As a TensorFlow Developer, your day-to-day responsibilities often include designing and building machine learning models, preprocessing data, conducting model training and evaluation, and deploying models to production environments. You may also work closely with data scientists, software engineers, and product managers to identify use cases, define project requirements, and optimize system performance. Regular tasks can involve using tools for data visualization, debugging, and performance tuning, as well as keeping up with the latest advancements in machine learning techniques. Collaboration and clear communication are key, as projects often require input and feedback from multiple technical and non-technical stakeholders.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in TensorFlow, deep learning, and data science. These roles usually involve leadership, extensive experience, and may include stock options or bonuses, with compensation reflecting expertise and impact on business outcomes.

What are the key skills and qualifications needed to thrive in the Tensorflow position, and why are they important?

To thrive in a TensorFlow Developer role, you need strong programming skills in Python, deep learning knowledge, and hands-on experience with TensorFlow and related AI frameworks. Familiarity with tools like Keras, TensorBoard, and cloud platforms such as Google Cloud is often required, and TensorFlow Developer certifications are highly valued. Excellent problem-solving, communication, and teamwork skills help professionals navigate complex projects and collaborate effectively with cross-functional teams. These skills and qualities ensure the successful design, deployment, and optimization of machine learning models in real-world applications.

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 Tensorflow jobs in Minnesota? For Tensorflow jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Tensorflow jobs in Minnesota look for? The top searched job categories for Tensorflow jobs in Minnesota are:
Tensorflow jobs near you
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

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