Senior Machine Learning Operations Engineer
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Requirements
• We’re looking for a builder - someone who has personally designed and productionized ML infrastructure before. • Experience architecting and deploying ML systems in production environments • Deep familiarity with ML lifecycle automation (training, CI/CD, deployment, monitoring) • Strong AWS experience, particularly within ML pipelines (SageMaker preferred) • Proven experience building infrastructure-as-code solutions (Terraform) • Experience productionizing ML workflows end-to-end, not just optimizing existing systems • Strong Python proficiency • Experience integrating ML workloads with data platforms and event-driven systems • Solid SQL skills and familiarity working with Snowflake • Experience implementing feature stores or model registries • Familiarity with data orchestration tools (Airflow, Prefect, Dagster) • Experience with ML observability tooling (Datadog, Prometheus) • Experience in regulated or financial data environments • Experience optimizing ML workloads for cost and scale • Exposure to Snowpark, Bedrock, or LLM orchestration frameworks • What Will Make You Successful • You’ve built ML infrastructure from the ground up or led a major re-architecture • You’re comfortable working in ambiguity and defining standards where none exist • You think in systems and care about reliability, governance, and scalability • You collaborate well with data scientists and engineers to turn prototypes into production systems • You take ownership and move quickly without sacrificing quality • Built’s salary range for this position is $140,000 - $210,000 USD per year. The pay range is designed to accommodate upward mobility in the role, therefore it encompasses the full span of proficiency levels for this role and we believe that the midpoint of the range is competitive in the market. Salary is just one component of Built's total compensation package for employees. Your total rewards package at Built will include equity, top-notch medical, dental and vision coverage, an unlimited PTO policy, and other benefits. • Travel Requirement: Teammates must be able to travel at minimum twice per year to Nashville, TN or another designated location for company-wide events (e.g., "Connect Week"). Additional travel may be required based on business needs and role responsibilities. • Travel Requirement:
Responsibilities
• You’ll build and operationalize the infrastructure that allows machine learning to run reliably in production. • Architect and implement Built’s foundational ML Ops platform from scratch • Define and deploy reusable patterns for model training, deployment, monitoring, and retraining • Build CI/CD pipelines for ML lifecycle automation, including versioning and experimentation tracking • Stand up a feature store integrated with Snowflake and AWS to support structured and unstructured data • Implement model registry and governance standards to ensure reproducibility, auditability, and rollback capability • Integrate ML workloads into our event-driven architecture (Kafka, Kinesis) • Develop observability frameworks to monitor drift, performance, latency, and model quality in production • Automate ML infrastructure using Terraform and AWS-native tooling (SageMaker, Lambda, ECS, Batch, Step Functions) • Establish security and compliance standards across ML assets, including data lineage and access control • Mentor engineers on ML Ops patterns and deployment best practices • This role is hands-on and foundational. You’ll be shaping how machine learning operates at Built for years to come.
Benefits
• The rare opportunity to radically disrupt a $1.5T industry • Competitive benefits including: uncapped vacation, health, dental & vision insurance • 401k with match and expedited vesting • Robust compensation package, including equity in the form of stock options • Flexible working hours, paid family leave, ERGs & Mentorship opportunities • Learning grant program to support ongoing professional development • Built brings together passionate people who are driven in a variety of disciplines, each bringing their unique perspective to everything they do. • We’re committed to building a safe, inclusive workplace where every employee can succeed, and we recruit, hire, and promote fairly - without bias based on race, color, religion, sex, sexual orientation, gender identity, marital status, veteran status, or any other characteristic protected by law.Greenhouse Data Disclosure • Greenhouse Data Disclosure • When you apply to a job on this site, the personal data contained in your application will be collected by Built Technologies (“Controller”). Your personal data will be processed for the purposes of managing Controller’s recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results thereto, and as is otherwise needed in the recruitment and hiring processes. Your personal data will be shared with Greenhouse Software, Inc., a cloud services provider located in the United States of America and engaged by Controller to help manage its recruitment and hiring process on Controller’s behalf. Your personal data will be retained by Controller as long as Controller determines it is necessary to evaluate your application for current or future employment. You have the right to request access to your personal data, to request that your personal data be rectified or erased, and to request that processing of your personal data be restricted. You also have to right to data portability. • If you would like to contact Controller to ask questions surrounding processing of your personal data or to make a request, you can send an email to [email protected]. California residents: Please note that Controller does not sell your personal data or share it with third parties outside of Greenhouse Software, Inc.
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