Senior Machine Learning Engineer

About This Role

This is a hands-on engineering role to design, build, and ship production machine learning systems that power real customer-facing products for a well-funded, early-stage Silicon Valley startup. The role involves technical ownership from problem framing to production impact, making architectural decisions, and building foundational systems.

Responsibilities

• Design, build, and deploy production-grade ML systems solving real-world problems
• Develop models for high-quality parsing and extraction across structured and semi-structured data, including HTML
• Select the right technical approach per problem, including fine-tuning, RAG, reinforcement learning, hybrid systems, or deterministic solutions
• Fine-tune and RL-train models as needed, iterating based on live performance
• Optimize systems for low latency and low cost without sacrificing quality
• Own the full ML lifecycle: data collection, feature engineering, training, evaluation, deployment, monitoring, and iteration
• Build scalable ML pipelines and low-latency inference systems suitable for production
• Collaborate closely with product and platform engineers to integrate ML into customer-facing applications
• Define best practices around experimentation, model versioning, evaluation, and monitoring

Requirements

• 10+ years of experience in machine learning, applied AI, or related engineering roles
• Strong fundamentals in machine learning, statistics, and algorithms
• Demonstrated experience deploying ML systems into production environments
• Deep hands-on experience with Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience with LLMs, embeddings, fine-tuning, RAG pipelines, and reinforcement learning
• Experience optimizing production systems for performance, latency, and cost
• Familiarity with modern ML infrastructure and data stacks, including cloud platforms, feature stores, vector databases, and orchestration tools
• Ability to operate effectively in fast-moving, ambiguous startup environments

Qualifications

• 10+ years of experience in machine learning, applied AI, or related engineering roles

Nice to Have

• Experience building parsing, extraction, or transformation systems
• Background in personalization, search, recommender systems, or NLP
• Early-stage startup experience or building systems from scratch
• Prior mentorship or technical leadership experience
• Experience working with privacy-sensitive or regulated data

Skills

* Required skills

Benefits