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Tensorflow Pytorch Jobs in Connecticut (NOW HIRING)

Prophecy Technologies

AI / GenAI Engineer

Hartford, CT · On-site

$104K - $141K/yr

... tools: - TensorFlow - PyTorch - Transformers - LangChain - LangGraph - Autogen - LlamaIndex • Experience with NLP techniques (text generation, summarization, understanding) • Experience with ...

Commonfund

AI/ML Development Analyst

Norwalk, CT · On-site

$100K - $150K/yr

Experience with ML frameworks as TensorFlow, PyTorch, or Scikit-learn * Strong analytical, problem-solving, and debugging skills. * Ability to work independently and collaboratively in a fast-paced ...

Infosys

AI Engineer

Hartford, CT · On-site

TensorFlow, PyTorch, LangChain • Expertise In Generative AI, Including RAG (Retrieval-Augmented Generation), AI Agents / Agentic frameworks, Prompt Engineering • Bachelor's degree or foreign ...

Infosys

AI Engineer

Hartford, CT · On-site

TensorFlow, PyTorch, LangChain • Expertise in Generative AI, including: RAG (Retrieval-Augmented Generation), AI Agents / Agentic frameworks, Prompt Engineering • Bachelor's degree or foreign ...

Gartner

Lead AI Engineer (ML Ops)

Stamford, CT · Hybrid

$109K - $143K/yr

Advanced programming skills in Python, with deep familiarity in ML frameworks (TensorFlow, PyTorch, Scikit-learn). * Proficient in leveraging cloud platforms (AWS, Azure, GCP) and their native AI/ML ...

Gartner

Lead AI Engineer (ML Ops)

Stamford, CT · Hybrid

$109K - $144K/yr

Advanced programming skills in Python, with deep familiarity in ML frameworks (TensorFlow, PyTorch, Scikit-learn). * Proficient in leveraging cloud platforms (AWS, Azure, GCP) and their native AI/ML ...

Infosys

AI Engineer

Hartford, CT · On-site

TensorFlow, PyTorch, LangChain Expertise in Generative AI, including: RAG (Retrieval-Augmented Generation) AI Agents / Agentic frameworks Prompt Engineering Proficiency with Microsoft Azure AI ...

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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 Connecticut? For Tensorflow Pytorch jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Connecticut look for? The top searched job categories for Tensorflow Pytorch jobs in Connecticut are:
What cities in Connecticut are hiring for Tensorflow Pytorch jobs? Cities in Connecticut with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you
Infographic showing various Tensorflow Pytorch job openings in Connecticut as of June 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 69% In-person, 6% Hybrid, and 25% Remote job distribution.

AI Developer

Kanak Elite Services Inc

Conantville, CT • On-site

Contractor

Posted 14 days ago

Job description

Hello There,

My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of AI Developer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com .

Job Description

Position           : AI Developer
Location          : Greenwich, CT Hybrid (Need local candidate)
Duration         : 6+ Months
Interview        : ONSITE INTERVIEW IS A MUST

Description

  • The AI Developer will develop, and implement AI-based solutions that support clients digital and data initiatives. The role involves hands-on development using AWS services (such as Amazon Bedrock, SageMaker, Lambda, and S3) and AI technologies including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering.
  • You will collaborate with data engineering and application development teams to build intelligent, scalable, and secure AI solutions integrated into enterprise systems

Key Responsibilities

  • Develop and maintain AI and machine learning models using AWS Bedrock, SageMaker, and Python-based frameworks.
  • Good to have experience on building AI Agents.
  • Implement and optimize data pipelines, embeddings, and vector search integrations for RAG-based applications.
  • Support deployment, monitoring, and lifecycle management of AI models following MLOps best practices.
  • Work closely with cross-functional teams to integrate AI components into applications and workflows.
  • Assist in evaluating and adopting emerging AI tools and frameworks to improve system performance.
  • Maintain code quality, documentation, and adherence to security and scalability standards.

Qualifications

  • Bachelor’s degree in Computer Science, Data Science, Engineering or related field.
  • 3–5 years of experience in software or AI development.
  • Proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
  • Hands-on experience with AWS cloud services (Bedrock, SageMaker, Lambda, API Gateway).
  • Knowledge of LLMs, embeddings, and vector databases (Pinecone, FAISS, etc.).
  • Understanding of SQL/NoSQL databases and data integration techniques.
  • Strong problem-solving and communication skills.