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Particula · 1 month ago

AI/ML Engineer (LLMs & RAG)

United States

Full-time

Remote

Mid Level

Particula is a leading rating and monitoring platform for digital assets. The role involves designing, building, and shipping LLM-powered features for ratings and monitoring products, with a focus on AI-powered analysis and automated report generation.

Financial Services

Responsibilities

Build and maintain LLM-powered features end-to-end (prompting, RAG pipelines, structured extraction/classification such as entity extraction)

Develop data ingestion, cleaning and indexing pipelines for RAG, including n8n workflows for intake and enrichment (connectors, transformations, error handling, scheduling)

Contribute to lightweight model tuning and systematic evaluation

Establish evaluation and observability for RAG (dashboards, automated reporting, experiment tracking) to ensure reliability and factual grounding

Optimise prompts, retrieval and context strategies to improve accuracy, reduce hallucinations and control latency/cost

Work hand-in-hand with our ML/DevOps engineer to ensure smooth deployments, reliability and continuous improvement

Coordinate and provide technical guidance to a small offshore AI development team (clear specifications, code reviews, quality standards), with support from the Head of AI

Collaborate with product and engineering to scope and deliver incremental value in short, iterative releases

Qualification

PythonPyTorchAWSLLM toolingDockerGitCI/CDMLOpsEnglishGermanClear communicationCollaborative mindset

Required

Strong Python skills; experience with PyTorch or Transformers; familiarity with the Hugging Face ecosystem

Practical knowledge of LLM tooling (e.g. LangChain or LangGraph) and RAG concepts

Experience building on AWS, ideally including: Serverless functions (AWS Lambda) for orchestration, Elastic compute (EC2) for workloads, Foundation model services (Bedrock or SageMaker) for model hosting and tuning

Hands‑on with n8n; workflow automation experience is a plus

Containerisation with Docker; proficiency with Git and CI/CD

MLOps fundamentals: MLFlow for experiment/model tracking; evaluation frameworks (e.g. RAGAS)

Clear communication, collaborative mindset and focus on shipping

Languages: strong English; German is a plus. Applications in English or German are welcome

Education: Degree in Computer Science or equivalent preferred; equivalent practical experience acceptable