VP, AI Engineering
1Password
Senior MLOps Engineer
OpenBright
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $175,000 - $225,000 per year
Job Level
Senior
Tech Stack
AWSDockerPython
About the role
- Design, build, and own the end-to-end MLOps infrastructure on AWS, with a heavy emphasis on scalable data engineering and reliable, cost-efficient ML systems.
- Implement and manage high-throughput, event-driven ML workflows (S3, Lambda, SQS, Step Functions, Batch) to support both data-centric pipelines and model execution.
- Develop and maintain robust CI/CD pipelines for model deployment and promotion, enforcing best practices for Git, semantic versioning, and multi-branch release strategies.
- Orchestrate complex data pipelines for the ingestion, processing, and updating of embeddings in vector databases (e.g., Qdrant, ChromaDB).
- Establish and manage systems for training phase management and experiment tracking (e.g., MLflow, SageMaker Experiments) and evaluate modern model serving tools (e.g., BentoML).
- Implement comprehensive security measures, including least-privilege access control (IAM) and secure credential management for models and APIs.
- Collaborate with data science teams to translate prototypes (including LLMs and standalone APIs) into production-grade services with clear monitoring strategies for production model health.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related technical field.
- 5+ years of professional experience in MLOps, DevOps, or a senior Data Engineering role with a focus on operationalizing machine learning models.
- Expert-level proficiency in Python for pipeline automation and scripting, including extensive experience with the AWS SDK (Boto3) and Bash.
- Deep, hands-on experience with core AWS services, including S3, Lambda, SageMaker, IAM, and a solid understanding of networking within VPCs.
- Proven experience building and deploying containerized applications (Docker), especially for serving ML models and LLM-based APIs.
- Deep familiarity with Git workflows (branching, merging, rebasing) and experience implementing CI/CD pipelines using tools like GitHub Actions or AWS CodePipeline.
- Demonstrated experience in designing and orchestrating complex, data-engineering-heavy pipelines, from data ingestion through to production inference.
Benefits
- Fast-paced startup environment where your ideas can quickly become reality
- Opportunity to wear multiple hats and grow beyond your job description
- Remote-first culture with home office support
- Comprehensive health benefits (Medical, Dental, Vision, HSA)
- 401(k) plan and life insurance
- Flexible time off and 12 weeks parental leave
- Professional development reimbursement
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
MLOpsdata engineeringAWSPythonBashDockerGitCI/CDevent-driven workflowsdata pipelines
Certifications
Bachelor's degree in Computer ScienceBachelor's degree in Engineering
