Staff Machine Learning Engineer

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

📋 Description

• Manage the feature store, including the tools necessary for defining, backfilling, and serving features.

• Utilize the feature store as the foundation for model training and deployment.

• Develop and enhance automated platforms for ML training and deployment.

• Create self-service tools and capabilities for feature registration, training jobs, model promotion, and monitoring.

• Standardize reproducible and schedulable training and retraining processes supported by feature-store data.

• Scale batch scoring and low-latency online inference with autoscaling, resource isolation, and cost management.

• Expand monitoring capabilities for data drift, feature drift, prediction quality, and serving health.

• Establish and lead the adoption of standards concerning model and feature versioning, lineage, testing, and documentation.

• Collaborate with data scientists and backend engineers to enhance platform adoption and expedite deployment.

⛳️ Requirements

• Extensive hands-on experience as a platform or software engineer in the field of ML.

• Proven experience with platforms that support multiple models in production across various teams.

• Familiarity with feature stores and model deployment platforms such as Databricks Feature Store, Feast, Tecton, or similar alternatives.

• Strong understanding of CI/CD processes for ML, including tools like GitHub Actions, Jenkins, Azure Pipelines, or comparable systems.

• Experience with model registries and infrastructure as code using Terraform.

• Cloud proficiency in AWS or Azure specific to ML deployment.

• Knowledge of Kubernetes and workflow orchestration.

• Strong skills in batch and real-time serving, along with understanding autoscaling, latency, and cost trade-offs.

• Experience in developing self-service tools that are widely adopted by data scientists.

• Proven ability to work with backend engineers to deploy models effectively.

• Capability to gather requirements, propose solutions, and drive projects to completion even in ambiguous situations.

• Adequate knowledge of model development and common algorithms to collaborate technically with data scientists.

• Familiarity with PySpark, Databricks, and Evidently AI is a plus.

🏝️ Benefits

• Equity

• Bonus

• WFH office reimbursement

• Flexible health plans at every premium level

• Substantial health-plan subsidies

• Paid global onsites twice yearly

• Growth opportunities based on contributions

• Virtual-first teamwork