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Tensorflow Pytorch Jobs in Missouri (NOW HIRING)

APC Integrated Services

AI Engineer

O Fallon, MO · On-site

$107K - $128K/yr

Proficiency in Python and Common AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) * Experience with data processing and analysis (SQL, Pandas, etc) * Understanding of APIs and system ...

Walmart

Principal, Data Scientist

Anderson, MO · On-site

$110K - $220K/yr

Strong expertise in Python and modern machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, or similar technologies. * Deep experience developing machine learning models ...

Walmart

Principal, Data Scientist

Noel, MO · On-site

$110K - $220K/yr

Strong expertise in Python and modern machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, or similar technologies. * Deep experience developing machine learning models ...

Walmart

Principal, Data Scientist

Cassville, MO · On-site

$110K - $220K/yr

Strong expertise in Python and modern machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, or similar technologies. * Deep experience developing machine learning models ...

Kohl's

$89K - $122K/yr

Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) * Experience working in Agile environments with an emphasis on iterative development and ...

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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 Missouri? For Tensorflow Pytorch jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Missouri look for? The top searched job categories for Tensorflow Pytorch jobs in Missouri are:
What cities in Missouri are hiring for Tensorflow Pytorch jobs? Cities in Missouri with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you
Senior AI/ML Scientist

Senior AI/ML Scientist

GLOBAL IT CON LLC

Saint Louis, MO • On-site

Other

Posted 17 days ago

Job description

Position: Senior AI/ML Scientist
Location: St. Louis, MO (Hybrid)
Type: Contract
Experience: 8 10+ Years

Job Summary

We are seeking a highly skilled Senior AI/ML Scientist to design, build, and scale machine learning systems that drive personalization, customer intelligence, and data-driven decision-making. The ideal candidate will work at the intersection of traditional machine learning, advanced statistical modeling, and emerging Generative AI and Agentic AI technologies to deliver impactful business solutions.

Key Responsibilities

Design, develop, and deploy production-grade propensity models, recommendation engines, and predictive machine learning solutions.

Lead applied research initiatives and perform rigorous statistical analysis to support model development and business strategy.

Build, train, and operationalize machine learning models on Google Cloud Platform (Google Cloud Platform) using services such as Vertex AI, BigQuery ML, Dataflow, and Cloud Run.

Develop and integrate Generative AI and Agentic AI capabilities into existing ML workflows and business applications.

Collaborate with data engineering teams to design feature stores, model training pipelines, and monitoring frameworks.

Translate complex business challenges into scalable machine learning solutions.

Present findings and recommendations to both technical and non-technical stakeholders.

Mentor junior data scientists and contribute to best practices across modeling, experimentation, and MLOps.

Required Qualifications

8 10+ years of experience in Machine Learning, Data Science, or related fields.

Advanced degree (Master's or PhD preferred) in Computer Science, Statistics, Machine Learning, Applied Mathematics, or a related quantitative discipline.

Strong experience building and deploying machine learning models in production environments.

Expertise in propensity modeling, recommendation systems, predictive analytics, and statistical analysis.

Hands-on experience with Google Cloud Platform (Google Cloud Platform), including Vertex AI, BigQuery, Dataflow, and Cloud Run.

Strong knowledge of Generative AI and Agentic AI concepts, including:

  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Agent Frameworks
  • Model Evaluation Techniques

Advanced Python programming skills.

Experience with machine learning frameworks such as:

  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Pandas
  • NumPy
Required Skills

Machine Learning
AI/ML Model Development
Recommendation Systems
Propensity Modeling
Statistical Analysis
Generative AI
Agentic AI
LLMs
RAG
Prompt Engineering
Python
TensorFlow / PyTorch
Google Cloud Platform (Google Cloud Platform)
Vertex AI
BigQuery
MLOps

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