Full-Time Senior Machine Learning Engineer

• Retrieval & Relevance: Improve retrieval quality through scoring optimization and query normalization.
• Implement heuristics and relevance-tuning logic to enhance matching precision and recall.
• Design and evaluate hybrid retrieval workflows combining semantic and lexical search.
• Model Development & Evaluation: Build, fine-tune, and evaluate LLM-based agents.
• Develop pipelines to measure accuracy, precision, recall, and model reliability.
• Implement guardrails and fallback logic to ensure consistent, explainable results.
• Data Engineering & Infrastructure: Optimize data vectorization and ingestion jobs.
• Maintain ORM models and database migrations using SQLAlchemy + pgvector and Alembic.
• Ensure data schema consistency and efficient vector indexing with pgvector.
• Develop clean, scalable ETL/ELT workflows to support data enrichment and ML readiness.
• Operational Excellence: Create observability tools, logging, and metrics dashboards.
• Produce reviewer-friendly exports and analytical reports for QA and ops teams.
• Contribute to documentation and operational best practices for ML pipelines.

• Expert Python engineering skills.
• Deep PostgreSQL expertise.
• Proficiency in machine learning system design with emphasis on retrieval, RAG, or LLM-based architectures.
• Experience with LangChain, OpenAI/Azure OpenAI, or equivalent LLM frameworks.
• Strong testing and evaluation mindset.
• Hands-on experience with LLM agents and Retrieval-Augmented Generation (RAG) pipelines.

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