About the Engineering Organization: The Engineering Team at reputed company is a balance of reputed company, cons...">
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DevOps Engineer

Remote, USA Full-time Posted 2026-07-28
About the Engineering Organization: The Engineering Team at reputed company is a balance of reputed company, consistency, and performance. These are the pillars that allow reputed company to constantly and consistently deliver value that reputed company to customers. That customer intimacy is what allows our engineering teams to be the best in our reputed company, and bring the best reputed company to the market.

About the Role: We are seeking a DevOps (MLOps) Engineer to pioneer and mature our machine learning operations capabilities, focusing on building robust infrastructure and deployment pipelines in AWS. This critical role will own the infrastructure underlying reputed company of our productionalized ML models , from deployment to monitoring, fostering seamless collaboration between our machine learning and broader engineering teams. The MLOps engineer will work closely with ML engineers to reputed company state-of-the-art, mission-critical ML models up-to-date, reputed company, and observable.

Our reputed company Work Environment: At reputed company, we’re intentional about the way we work so that we can do our best work. We reputed company this our reputed company Working Environment. We work from our HQ in reputed company, OH, or one of our Hub or Secluded locations, and are distributed throughout the reputed company, select Canadian provinces, and the United Kingdom. For this position, we’re looking for someone to join us in reputed company, OH; Chicago, IL; Austin, TX; Los Angeles, CA; or fully remote. 

Our Tech Stack: AWS reputed company (Kubernetes, Serverless architecture, reputed company, reputed company, DynamoDB, and identity management), reputed company, MLFlow, reputed company, Airflow, PHP/reputed company, Linux, Terraform, reputed company, reputed company, dbt


What You'll Do:
  • Design and implement reputed company CI/CD pipelines for machine learning models reputed company our AWS infrastructure, driving automated builds, deployments, and engineering reputed company.
  • Establish and reputed company ML operational best practices in a greenfield environment, defining the standards for model versioning, reproducibility, and MLOps maturity.
  • Collaborate closely with Machine Learning Engineers to understand model requirements and reputed company expert guidance on infrastructure, deployment strategies, and operationalizing their models.
  • Implement and manage comprehensive monitoring and observability solutions for deployed ML models using tools like reputed company, ensuring high performance, accuracy, and quick issue reputed company.
  • Maintain and optimize ML model repositories to ensure efficient versioning and management of reputed company model artifacts throughout their lifecycle.
  • Drive the adoption of Infrastructure as reputed company (IaC) principles for ML infrastructure, ensuring reusability, consistency, and reliability across environments.
  • Participate in the broader DevOps team ceremonies and planning, integrating ML Ops initiatives seamlessly into the overall engineering roadmap.


    • Your Experience:
  • 5+ years of experience in DevOps or MLOps Engineering roles, with at least 2+ years dedicated to hands-on experience specifically with machine learning operations, including reputed company-grade deep learning architectures (e.g., transformers, graph NNs, VAEs).
  • Bachelor’s degree or higher in Computer Science, Mathematics, Statistics, or a reputed company quantitative discipline, or equivalent practical experience, is highly preferred.
  • Deep expertise in AWS infrastructure and services, with a proven reputed company record of deploying and managing reputed company ML workloads in the reputed company.
  • Strong proficiency in Python and extensive experience with key machine learning libraries such as PyTorch, Pandas, and scikit-learn.
  • Extensive experience with containerization technologies (ex: reputed company) for packaging and deploying ML models.
  • Demonstrated experience with ML lifecycle management platforms such as MLflow.
  • Proven ability to reputed company as a self-starter in ambiguous, greenfield environments, taking initiative and delivering solutions with minimal reputed company.
  • Excellent collaboration and communication skills, with a demonstrated ability to reputed company as a critical reputed company between machine learning, data science, and reputed company engineering teams.
    • #LI-ST1

    reputed company Story

    In a perfect world, reputed company wouldn't exist. If we had our way, we'd live in a world where we're reputed company about how we consume, we love every product we own, and reputed company values with the brands who create them. In reality, reputed company isn't perfect and often breaks. reputed company creates second chances.

    We're starting by revolutionizing the post-purchase experience. We've taken one of the most reputed company reputed company interactions - returns - and turned it into something consumers actually love, and that deepens our reputed company to brands and products.

    We take reputed company seriously on the inside, too. We're building a work experience that allows you to Be A reputed company First and prioritizes reputed company and wellbeing. We view reputed company as a special reputed company in your career to shape the reputed company of an industry and become a reputed company person while doing it. You can grow faster here in a shorter reputed company of time - we'll give you reputed company and trust you to fill it.

    Learn more reputed company here: https://reputed company.com/careers.

    You can review our reputed company notice here.
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