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Tensorflow Jobs in Connecticut (NOW HIRING)

Prophecy Technologies

AI/ML Engineer

Hartford, CT · On-site

PyTorch or TensorFlow; Hugging Face Transformers. * Solid understanding of deep learning architectures and modern NLP/LLM concepts (tokenization, attention/transformers, fine-tuning approaches)

Iberdrola

Lead Architect - Generative AI

Orange, CT · On-site

$59.25 - $81/hr

Proficiency in Python for AI/ML workflows, including libraries like TensorFlow, PyTorch, Hugging Face, and LangChain. * Strong command of Java for backend development, microservices, or integrating ...

Iberdrola

Lead Architect - Generative AI

Orange, CT · On-site

$59.25 - $81/hr

Proficiency in Python for AI/ML workflows, including libraries like TensorFlow, PyTorch, Hugging Face, and LangChain. * Strong command of Java for backend development, microservices, or integrating ...

Pwc

AI & GenAI Data Scientist-Senior Associate

Hartford, CT · On-site

$77K - $202K/yr

... TensorFlow and Scikit-Learn to enhance model performance - Conducting complex data analysis to inform strategic decision-making - Leveraging natural language processing and text analytics for ...

New

Catalyst Labs

ML Engineer

Stamford, CT · On-site

... TensorFlow. • Familiarity with cloud environments and infrastructure (preferably AWS). • Strong understanding of data pipeline design, real-time inference, and model monitoring. • Excellent ...

Catalyst Labs

ML Engineer

Greenwich, CT · On-site

... TensorFlow. • Familiarity with cloud environments and infrastructure (preferably AWS). • Strong understanding of data pipeline design, real-time inference, and model monitoring. • Excellent ...

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 ...

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 ...

Munich Re

Senior Data Scientist

Hartford, CT · On-site

Experience with deep learning frameworks (TensorFlow, Keras, PyTorch, etc.) * Experience with Bayesian programming languages/frameworks such as Stan, or PyMC3 is a plus Knowledge and Skills: * Hands ...

Munich Re

Senior Data Scientist

Hartford, CT · On-site

Experience with deep learning frameworks (TensorFlow, Keras, PyTorch, etc.) * Experience with Bayesian programming languages/frameworks such as Stan, or PyMC3 is a plus Knowledge and Skills: * Hands ...

Munich RE

Senior Data Scientist

Hartford, CT · On-site

Experience with deep learning frameworks (TensorFlow, Keras, PyTorch, etc.) * Experience with Bayesian programming languages/frameworks such as Stan, or PyMC3 is a plus Knowledge and Skills: * Hands ...

Munich Re

Data Scientist

Hartford, CT · On-site

Experience with deep learning frameworks (TensorFlow, Keras, PyTorch, etc.) is a plus * Experience with Bayesian programming languages/frameworks such as Stan, or PyMC3 is a plus Knowledge and Skills:

Munich Re

Data Scientist

Hartford, CT · On-site

Experience with deep learning frameworks (TensorFlow, Keras, PyTorch, etc.) is a plus * Experience with Bayesian programming languages/frameworks such as Stan, or PyMC3 is a plus Knowledge and Skills:

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Tensorflow information

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$35.7K

$116.8K

$186.9K

How much do tensorflow jobs pay per year?

As of Aug 9, 2026, the average yearly pay for tensorflow in Connecticut is $116,759.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,700.00 and $129,400.00 per year, depending on experience, location, and employer.

What is a TensorFlow?

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.

What does a TensorFlow developer do?

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 jobs use TensorFlow?

Jobs that use TensorFlow include machine learning engineer, data scientist, AI researcher, and deep learning engineer. These roles involve developing 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 are the key skills and qualifications needed to thrive in the TensorFlow position?

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 Connecticut? The most popular types of Tensorflow jobs in Connecticut are:
What are popular job titles related to Tensorflow jobs in Connecticut? For Tensorflow jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Tensorflow jobs in Connecticut look for? The top searched job categories for Tensorflow jobs in Connecticut are:
What cities in Connecticut are hiring for Tensorflow jobs? Cities in Connecticut with the most Tensorflow job openings:
Tensorflow jobs near you
Infographic showing various Tensorflow job openings in Connecticut as of August 2026, with employment types broken down into 33% Internship, 44% Full Time, and 23% Contract. Highlights an 100% In-person job distribution, with an average salary of $116,759 per year, or $56.1 per hour.

AI/ML Engineer

Prophecy Technologies

Hartford, CT • On-site

Full-time

Re-posted 12 hours ago

Job description

Role Overview:
We are seeking an AI/ML Engineer with hands-on experience building, fine-tuning, and deploying LLM-based solutions. This role involves working on Natural Language Processing (NLP) and Generative AI (GenAI) use cases such as classification, summarization, and retrieval-augmented generation (RAG), in partnership with product and engineering teams to deliver scalable, secure, and measurable outcomes.
Key Responsibilities:
  • Design, build, and fine-tune NLP/LLM solutions for business use cases (e.g., classification, summarization, Q&A).
  • Develop efficient, well-documented Python code for training, inference, and evaluation pipelines.
  • Build RAG applications using embeddings, vector databases, and prompt engineering techniques.
  • Integrate LLM applications into services/APIs and ensure performance, reliability, and scalability.
  • Establish model evaluation, monitoring, and governance practices (quality, safety, bias, drift).
  • Collaborate with data engineering and platform teams on data pipelines, deployments, and CI/CD.

Required Skills:
  • 6+ years of overall experience in software development focusing on AI/ML engineering.
  • 2+ years of hands-on experience with deep learning for NLP/GenAI.
  • Strong Python proficiency, including writing production-quality, testable, maintainable code.
  • Experience with deep learning frameworks and libraries: PyTorch or TensorFlow; Hugging Face Transformers.
  • Solid understanding of deep learning architectures and modern NLP/LLM concepts (tokenization, attention/transformers, fine-tuning approaches).
  • Experience building rapid prototypes and APIs using FastAPI/Flask and/or Streamlit.

Qualifications:
  • 6+ years of overall experience in software development focusing on AI/ML engineering.
  • 2+ years of hands-on experience with deep learning for NLP/GenAI.
  • Strong Python proficiency.
  • Experience with PyTorch or TensorFlow; Hugging Face Transformers.
  • Solid understanding of deep learning architectures and modern NLP/LLM concepts.
  • Experience building rapid prototypes and APIs using FastAPI/Flask and/or Streamlit.

Preferred Skills:
  • Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or similar).
  • Experience with vector databases and embedding workflows (e.g., FAISS, Pinecone, Weaviate, Chroma, Azure AI Search).
  • Experience deploying and scaling ML/LLM workloads on cloud platforms (Azure preferred; GCP/AWS acceptable).
  • Familiarity with agentic architectures and multi-agent patterns (e.g., AutoGen or similar).
  • Healthcare domain knowledge and/or experience building solutions in regulated environments.

Standard Technical Skills:
  • MLOps & Deployment: Model packaging and serving, CI/CD, containers (Docker), orchestration (Kubernetes), experiment tracking (MLflow), model registry, monitoring/observability.
  • LLM Evaluation: Offline/online evaluation, prompt/version management, automated testing, hallucination and factuality checks, retrieval evaluation, human-in-the-loop review.
  • Software Engineering: Git, code reviews, unit/integration testing (pytest), REST APIs, basic system design, performance optimization.
  • Security & Compliance: Secure coding, secrets management, PII/PHI handling, access control; familiarity with responsible AI principles is a plus.

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