Senior Research Engineer

Summary: The Senior Research Engineer role focuses on developing and delivering machine learning solutions, particularly in the areas of LLM, NLP, and RAG applications. The position requires collaboration with researchers to translate complex problems into deployable solutions while maintaining quality and performance through code reviews and monitoring. The engineer will work in an agile environment, communicating effectively with both technical and non-technical stakeholders. This role demands a strong background in software engineering and machine learning product development.

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.

Key Skills:

• 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.

Salary (Rate): £52.50 hourly

City: Manhattan

Country: USA

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: Senior

Industry: IT

Detailed Description From Employer:

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.

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Required Skills & Experience

• 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.

• 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.

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Preferred Skills & Experience

• 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.