The Engineering Team at Loop focuses on agility, consistency, and performance to deliver value to customers.
The role of DevOps (MLOps) Engineer involves pioneering and maturing machine learning operations capabilities, with an emphasis on building robust infrastructure and deployment pipelines in AWS.
This position is responsible for the infrastructure supporting all productionalized ML models, from deployment to monitoring, and will facilitate collaboration between machine learning and engineering teams.
The MLOps engineer will work closely with ML engineers to ensure that ML models are up-to-date, scalable, and observable.
Loop offers a Blended Working Environment, allowing work from HQ in Columbus, OH, or other locations including Chicago, IL; Austin, TX; Los Angeles, CA; or fully remote.
The tech stack includes AWS Cloud (Kubernetes, Serverless architecture, Redis, Aurora, DynamoDB), Docker, MLFlow, Gitlab, Airflow, PHP/Laravel, Linux, Terraform, Datadog, Snowflake, and dbt.
Responsibilities include designing scalable CI/CD pipelines, establishing ML operational best practices, collaborating with ML engineers, implementing monitoring solutions, maintaining ML model repositories, driving Infrastructure as Code adoption, and participating in DevOps team planning.
Requirements:
Candidates must have 5+ years of experience in DevOps or MLOps Engineering roles, with at least 2+ years focused on machine learning operations and enterprise-grade deep learning architectures.
A Bachelor’s degree or higher in Computer Science, Mathematics, Statistics, or a related quantitative discipline, or equivalent practical experience is highly preferred.
Deep expertise in AWS infrastructure and services is required, with a proven track record of deploying and managing scalable ML workloads in the cloud.
Strong proficiency in Python and extensive experience with machine learning libraries such as PyTorch, Pandas, and scikit-learn is necessary.
Candidates should have extensive experience with containerization technologies like Docker for packaging and deploying ML models.
Demonstrated experience with ML lifecycle management platforms such as MLflow is essential.
The ability to thrive as a self-starter in ambiguous environments and deliver solutions with minimal oversight is required.
Excellent collaboration and communication skills are necessary to bridge machine learning, data science, and core engineering teams.
Benefits:
Loop offers a competitive salary range of $123,200 - $184,800 per year, with adjustments based on experience, location, and market demands.
Employees are eligible for medical, dental, and vision insurance.
Flexible PTO, company holidays, sick & safe leave, and parental leave are provided.
A 401k plan is available for employees.
Additional benefits include a monthly wellness benefit, home workstation benefit, phone/internet benefit, and equity options.
