Machine Learning Engineer, Marketplace

What You'll Build

• Ranking and matching systems that determine which candidates and opportunities are surfaced
• Models for recommendation, personalization, and marketplace optimization
• Retrieval, scoring, and decision pipelines operating at global scale
• Feedback loops that learn from downstream hiring outcomes, not just top-of-funnel engagement
• Real-time and batch inference systems embedded in product-critical workflows

Example Problems

• Improve candidate-job matching using embeddings, structured attributes, and behavioral signals
• Optimize ranking toward long-term hiring outcomes under delayed and incomplete labels
• Design models that balance marketplace objectives such as fill rate, quality, speed, and conversion
• Build systems for candidate allocation, opportunity routing, and liquidity optimization
• Develop evaluation and experimentation frameworks that connect model performance to business results

What We're Looking For

• Strong track record of shipping ML systems into production
• Experience with ranking, recommendation, search, matching, or marketplace problems
• Good judgment on model design, objective functions, evaluation, and tradeoffs
• Comfort working across the full applied ML stack: data, features, training, inference, and iteration
• Strong engineering fundamentals and a bias toward simple, robust systems

Tech Stack

• Python
• Go
• embeddings
• fine-tuning
• RAG
• Kafka
• Postgres
• Redis
• Elasticsearch
• Kubernetes
• Terraform

Benefits

• Bi-annual performance bonus structure
• Generous equity grant vested over 4 years
• Up to $15k Relocation bonus
• $10K housing bonus (if you live within 0.5 miles of our office)
• $1.5K monthly stipend for meals
• Free Equinox membership
• $200 monthly laundry reimbursement
• $200 monthly personal wellness reimbursement
• Health, Dental, Vision insurance