Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and optimizing models and systems for the Piai claims-intelligence platform with an accent on production ML lifecycles, data pipelines, and generative AI. Focus on architecting scalable pipelines, implementing evaluation strategies for LLMs, and productionizing state-of-the-art NLP techniques.

Location: Hybrid (3 days/week) in San Francisco, USA or Toronto, Canada

Salary: $196,000 – $265,000 (SF) / CA$148,000 – CA$200,000 (Toronto)

Company

AI-powered vertical SaaS company focused on closing the justice gap for personal injury lawyers and victims.

What you will do

• Design and own production ML systems across the full lifecycle from problem framing to deployment and monitoring.
• Architect scalable data pipelines for structured, unstructured, and embeddings-based data.
• Build reusable frameworks and infrastructure for model development, evaluation, and benchmarking.
• Productionize state-of-the-art techniques across NLP, information retrieval, and generative AI.
• Define and implement evaluation strategies including quality metrics, human-in-the-loop review, and automated benchmarks.
• Mentor other engineers and contribute technical judgment to hiring and calibration.

Requirements

• 5+ years of experience building and deploying machine learning systems in production.
• Strong software engineering fundamentals in Python, distributed systems, and API design.
• Experience owning the full ML lifecycle, beyond just model training.
• Track record of turning ambiguous problems into scoped, shippable solutions.
• Experience mentoring other engineers and influencing technical direction.
• Ability to work hybrid (3 days/week) in the San Francisco or Toronto office.

Nice to have

• Experience with NLP, LLMs, generative AI, fine-tuning (LoRA/PEFT), or prompt engineering.
• Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus, etc.) or orchestration frameworks (LangChain, LlamaIndex).
• Experience with generative AI evaluation methodologies, such as RAG benchmarks and hallucination reduction.
• Experience in a high-growth startup environment.
• Background in legal tech, healthcare, or other high-stakes regulated domains.

Culture & Benefits

• Comprehensive medical, dental, and vision insurance plans for employees and families.
• Flexible paid time off, sick leave, and paid parental leave.
• 401(k) for US-based employees and RRSP for Canada-based employees.
• Home office stipend and a local in-person meet-up program.
• Collaborative environment backed by top VCs in a fast-growing vertical SaaS space.