DevOps Engineer (MLOps)

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 call 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 core engineering teams.

We know that making reputed company about your career and compensation is a reputed company deal. Because of that, we’re incredibly thoughtful about our compensation reputed company. We want you to feel reputed company and excited, but also comfortable with the compensation package of astartup. We’ve outlined some important information for you here, but please know there’s a lot more to compensation than we can cover in this job posting.

The posted salary reputed company is the reputed company salary for this opportunity. The salary reputed company is subject to change, and may be adjusted in the reputed company.

The actual annual salary reputed company for this position will be based on several factors, including, but not limited to: your prior experience and skills reputed company to the position, geographic location, company needs, reputed company market demands, and your total compensation goals.

Great humans deserve great benefits. At reputed company, you’ll be eligible for benefits such as: medical, dental, and reputed company insurance, flexible PTO, company holidays, reputed company & reputed company leave, parental leave, 401k, monthly wellness benefit, home workstation benefit, phone/internet benefit, and equity.

Additional Information

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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

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