Senior Machine Learning Engineer, EvenUp

• We value depth, ownership, and a desire to push boundaries in applied ML. You should be excited to take initiative on problems that don't have clear answers
• 5+ years of experience in applied machine learning or data science
• MS or PhD in CS, ECE, Statistics, or related field with a research focus in ML / NLP / Generative AI
• Strong background in NLP and model development with LLMs or transformer-based architectures
• Proficiency in Python and frameworks like PyTorch or TensorFlow
• Experience with at least some of the following:
• Production ML systems and pipelines
• Retrieval and RAG system design
• Prompt engineering & LLM context optimization
• LLM fine-tuning (LoRA, QLoRA, instruction tuning)
• Vector stores, semantic search, and embeddings
• Model evaluation, A/B testing, and offline experimentation
• Knowledge graphs and structured data integration
• Distributed data processing (Spark, Ray, etc.)

Desirable

• As a Senior Machine Learning Engineer, you'll lead high-impact initiatives across model development, deployment, and research-to-production workflows. You’ll work with a proprietary legal dataset, partner closely with legal domain experts, and shape the next generation of AI systems in one of the most meaningful application domains for AI
• What you’ll do:
• Design, build, and optimize Document AI systems that understand and reason over complex legal and medical documents
• Lead development in:
• Information Extraction: entity recognition, relationship extraction, structure parsing using both classical and LLM-based methods
• Information Retrieval: semantic search, hybrid retrieval, learning-to-rank models
• RAG Systems: advanced prompting (chain-of-thought, self-consistency), multi-hop reasoning
• LLM Adaptation: instruction fine-tuning, parameter-efficient techniques (LoRA/QLoRA), and domain adaptation
• Translate ambiguous product requirements into scalable, production-grade ML systems
• Mentor junior MLEs and contribute to best practices across modeling, experimentation, and deployment
• Partner with cross-functional teams including legal SMEs, product managers, and software engineers to iterate quickly and deliver business value