Lead Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the execution of the long-term technical strategy for pricing machine learning tools and workflows.

• Collaborate with researchers to outline platform requirements encompassing data readiness, feature engineering, model fitting, serving, diagnostics, and monitoring.

• Develop feature pipelines and feature stores, facilitate reproducible model training and orchestration, manage model registries and versioning, automate validation, and ensure model serving, production observability, and supporting tools.

• Automate comprehensive workflows utilizing large language model technology and agentic data science workflow automation.

• Take ownership of the implementation of significant platform capabilities from design to production.

• Decompose complex problems, oversee dependencies, influence design choices, and drive delivery among multiple engineers.

• Coordinate the software development lifecycle across the team.

• Mentor and assist engineers through technical advice and constructive feedback.

• Uphold standards for reliability, observability, reproducibility, and correctness across platform systems.

• Write and review code, propel execution, and maintain dependable production systems that serve customers.

⛳️ Requirements

• Over 8 years of experience in software engineering.

• Proven history of building and deploying production machine learning platforms and large-scale data processing systems.

• Practical experience with feature pipelines or feature stores, reproducible model training and orchestration, model registries and versioning, automated validation, or model serving.

• Strong foundation in system design and distributed systems.

• Experience in developing reliable, scalable production services and data pipelines.

• Familiarity with the machine learning lifecycle and engineering considerations for training, evaluating, deploying, and operating models in production.

• Experience in designing and managing systems that demand reliability, observability, reproducibility, and correctness.

• Capability to take vague technical projects, break them into actionable tasks, manage dependencies, and facilitate delivery among multiple engineers.

• Proven experience collaborating closely with Data Scientists or researchers.

• Experience in mentoring engineers, guiding technical design, and enhancing engineering quality.

• Proficient in Python and contemporary machine learning and data tooling.

• Outstanding communication skills with engineers, researchers, product teams, and cross-functional stakeholders.

• Preferred: knowledge of machine learning models, improvements in research velocity, training-serving consistency, model lineage, reproducibility, model-versioning, and experience in regulated or data-intensive environments, as well as familiarity with LLM or agentic systems.

• Applicants must appear on camera for virtual interviews.

🏝️ Benefits

• Competitive bonus structure.

• Equity offering.

• Flexibility to work from any location that suits you within the US.

• Reasonable accommodations available throughout the hiring process.