Machine Learning Engineer

About the role

We are looking for a Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the workflows, infrastructure, and processes that enable ML to move from research into reliable production systems.

Responsibilities

• Build and maintain the workflows and infrastructure that support the end-to-end ML lifecycle
• Partner with researchers and ML practitioners to productionize models and enable faster iteration
• Design, build, and improve data pipelines and training pipelines
• Improve data processing, annotation workflows, and ML system efficiency
• Deploy and maintain the background systems that support model training and inference
• Build tooling and processes for monitoring model performance, system reliability, and operational health
• Improve the scalability, observability, and reproducibility of ML systems
• Optimize ML infrastructure for speed, reliability, and cost-efficiency
• Identify bottlenecks in the ML workflow and automate or streamline manual processes
• Help establish best practices around ML operations, deployment, and system performance

Requirements

• Proven (3+ years) of experience in machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments
• Experience supporting ML systems end to end, from model handoff through deployment and monitoring
• Strong experience building and owning data pipelines, training pipelines, or other production workflows that support ML
• Experience working closely with researchers, data scientists, or ML practitioners to productionize models
• Strong software engineering fundamentals and experience building production systems
• Experience with monitoring, debugging, and improving production ML or data systems
• A track record of improving reliability, scalability, speed, and/or cost efficiency in ML systems
• Comfort operating in a fast-moving, startup-style environment with a high degree of ownership

Qualifications

• Competitive salary and equity in a high-growth startup
• Flexible PTO, take what you need
• Medical, dental, and vision coverage
• Great startup culture, including company off-sites
• High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more

Benefits

• The work does not stop when a customer first onboards to our platform. It deepens over time. We partner with operators, listening and learning about real problems, and translate that into solutions that help them succeed in practice. We earn trust through consistent delivery.
• We keep the patient downstream of every decision
• If this sounds like you, we'd love to have a chat!

Pay

• Competitive salary and equity in a high-growth startup

Schedule

• Flexible PTO, take what you need