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Hugging Face Jobs in Springfield, MA (NOW HIRING)

Prophecy Technologies

AI/ML Engineer

Hartford, CT · On-site

Hugging Face Transformers. * Solid understanding of deep learning architectures and modern NLP/LLM concepts (tokenization, attention/transformers, fine-tuning approaches). * Experience building rapid ...

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How much do hugging face jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for hugging face in Springfield, MA is $15.44, according to ZipRecruiter salary data. Most workers in this role earn between $12.98 and $18.27 per hour, depending on experience, location, and employer.

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

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Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Springfield, MA as of June 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution, with an average salary of $32,038 per year, or $15.4 per hour.

AI/ML Engineer

Prophecy Technologies

Hartford, CT • On-site

Full-time

Posted 29 days 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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