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Tensorflow Pytorch Jobs in Iowa (NOW HIRING)

Kellton

Imaging Data Scientist

Johnston, IA

$75/hr

... PyTorch/TensorFlow), including detection/segmentation/classification for scientific or industrial imaging. * Proven ability to productionize models: Git/GitLab, code reviews, CICD basics, experiment ...

Tractor Zoom

Be Seen First

Senior Data Scientist

Des Moines, IA · On-site

$120K - $145K/yr

Proven experience deploying, testing, and monitoring models at an enterprise level utilizing different frameworks (e.g. sklearn, PyTorch, Tensorflow, etc.) * Design and build agentic workflows that ...

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

AI Developer

American technologies consulting

West Des Moines, IA • On-site

Contractor

Posted 8 days ago

Job description

Job Overview

We are seeking a skilled AI Developer to design, build, and deploy autonomous AI agents from scratch. This role involves creating intelligent systems that can perceive environments, make decisions, and execute actions in real-world or simulated scenarios. You will leverage machine learning, Python, and specialized frameworks like LangChain and LangGraph to develop scalable AI agents for applications such as automation, robotics, virtual assistants, or multi-agent simulations.

Key Responsibilities
  • Architect and implement AI agents from the ground up using frameworks such as LangChain for chaining LLMs and tools, and LangGraph for stateful, graph-based agent workflows, including perception modules (e.g., using computer vision or NLP), decision-making logic (e.g., via reinforcement learning or planning algorithms), and action execution components.
  • Develop and train machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn to enable agent learning and adaptation, integrating with LangChain/LangGraph for advanced agent orchestration.
  • Integrate AI agents with external systems, APIs, databases, and environments (e.g., simulation tools like OpenAI Gym or real-world interfaces), ensuring seamless tool usage and memory management via LangChain components.
  • Optimize agents for performance, scalability, and robustness, including handling edge cases, ethical considerations, and safety protocols within graph-structured agent designs.
  • Collaborate with cross-functional teams (e.g., data scientists, software engineers) to iterate on agent designs based on feedback and testing.
  • Conduct experiments, simulations, and evaluations to refine agent behaviors and ensure reliability in production.
  • Document code, architectures, and methodologies for reproducibility and team knowledge sharing.
  • Stay current with advancements in AI agent technologies, such as large language models (LLMs), multi-agent systems, and emerging frameworks like LangChain and LangGraph.
Required Skills and Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • Proficiency in Python programming, with strong experience in ML libraries (e.g., TensorFlow, PyTorch, NumPy, Pandas) and agent-specific tools (e.g., LangChain, LangGraph, AutoGen, RLlib, Hugging Face Transformers).
  • Hands-on experience building AI agents from scratch using LangChain for tool integration and agent chains, LangGraph for multi-step reasoning and state management, including reinforcement learning, state machines, graph-based planning, or evolutionary algorithms.
  • Solid understanding of data structures, algorithms, software engineering principles, and version control (e.g., Git).
  • Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying agents, and tools like Docker/Kubernetes for containerization.
  • Strong problem-solving skills, with the ability to debug complex systems and work in agile, fast-paced environments.
  • Excellent communication skills to articulate technical designs and collaborate effectively.
Preferred Qualifications
  • Experience with specialized domains like natural language processing (NLP), computer vision, robotics (e.g., ROS), or game AI, integrated with LangChain/LangGraph.
  • Knowledge of big data tools (e.g., Spark, Hadoop) or databases (SQL/NoSQL) for handling large-scale agent data.
  • Prior work with multi-agent systems, ethical AI, or real-time applications using advanced frameworks.
  • Contributions to open-source AI projects or a portfolio demonstrating agent-building expertise (e.g., GitHub repos showcasing LangChain/LangGraph implementations).