SENIOR RESEARCH ENGINEER

Harnham

New York, NY

Contract

Senior

125k-135k

5 days ago

Job Description

About the Role

The Senior Research Engineer will contribute across the full software development lifecycle, focusing on building and deploying advanced ML solutions such as LLM, NLP, and RAG applications. The role involves collaborating with research scientists, maintaining high-quality code, and exploring innovative AI/ML approaches within a dynamic team environment in Manhattan on a contract basis with a pay rate of $60-$65 per hour.

Key Responsibilities

Develop and deliver: Contribute across the full software development lifecycle, writing clean, tested, maintainable code.
Productionize ML solutions: Build and deploy LLM, NLP, and RAG applications, ensuring scalability, monitoring, and versioning.
Collaborate with researchers: Partner with research scientists to translate problem statements into deployable ML solutions.
Maintain quality and performance: Conduct code reviews, monitor models, prevent degradation, and ensure logging and documentation are in place.
Agile teamwork: Work in 2-week sprints with daily standups, collaborating with product managers, engineers, and scientists.
Communicate effectively: Break down complex technical concepts for both technical and non-technical audiences.
Experiment and innovate: Explore agentic workflows, prompt engineering, and emerging AI/ML approaches.

Requirements

Bachelor's degree in Computer Science, related field, or equivalent experience.
5+ years of software engineering experience, including 2+ years in ML product development.
1+ year specifically in NLP tasks (NER, document analysis, information extraction, retrieval, classification).
Experience deploying ML/LLM solutions into production.
Strong proficiency in Python and modern development stacks.
Solid understanding of software engineering best practices, CI/CD, testing, DevOps, and SDLC.
Familiarity with cloud environments and scalable data pipelines.
Strong communication and collaboration skills; ability to work across teams of engineers and researchers.
Self-starter with proven ability to drive projects forward without micromanagement.

Nice to Have

Hands-on experience with LLM frameworks (e.g., LangChain, LangGraph) and FastAPI.
Experience with RAG pipelines and agent-based workflows.
Knowledge of ModelOps/MLOps principles.
Familiarity with classical NLP as well as generative AI.
Additional programming languages (Java, Scala, Rust, Typescript, etc.) a plus.

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