Senior Machine Learning Engineer

EvenUp EvenUp · Vertical AI · San Francisco, CA · Hybrid · Data Science

Senior Machine Learning Engineer to build and deploy production ML systems for a legal tech platform, focusing on NLP, information retrieval, and generative AI, covering the full ML lifecycle from data to deployment and monitoring.

What you'd actually do

  1. Design, build, and own production ML systems across the full lifecycle - problem framing, data strategy, training, evaluation, deployment, and monitoring.
  2. Architect scalable data pipelines that handle structured, unstructured, and embeddings-based data for training and inference.
  3. Build reusable frameworks and infrastructure for model development, evaluation, and benchmarking.
  4. Partner with data scientists and product managers to translate ambiguous business problems into concrete ML system designs.
  5. Apply and productionize state-of-the-art techniques across NLP, information retrieval, and generative AI where the problem calls for it.

Skills

Required

  • Python
  • distributed systems
  • API design
  • full ML lifecycle ownership
  • mentoring engineers
  • technical judgment

Nice to have

  • NLP
  • LLMs
  • generative AI
  • embeddings
  • fine-tuning (LoRA or other PEFT)
  • prompt engineering
  • vector databases (Pinecone, Weaviate, FAISS, Milvus, Elasticsearch/OpenSearch)
  • orchestration frameworks (LangChain, LlamaIndex)
  • evaluation methodologies for generative AI
  • RAG benchmarks
  • hallucination reduction
  • factual grounding
  • high-growth startup environment
  • legal tech
  • healthcare
  • regulated domains

What the JD emphasized

  • 5+ years building and deploying machine learning systems in production
  • Experience owning the full ML lifecycle, not just model training in isolation
  • A track record of turning ambiguous problems into scoped, shippable solutions

Other signals

  • production ML systems
  • full lifecycle
  • NLP, information retrieval, and generative AI
  • evaluation strategies
  • scalability and efficiency