Machine Learning & Operations Engineer
OptiTrack•Atlanta, GA
•Remote
About The Position
OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning. This role sits at the intersection of machine learning engineering and infrastructure, focusing on automation of data validation pipelines, orchestration of large-scale experiments, and deployment of high-performance algorithms. This is a fully remote position, working cross-functionally with research and engineering teams.
Requirements
- 3+ years of experience in MLOps, ML infrastructure, Machine Learning, or related roles or relevant degree experience.
- Experience with Python and ML frameworks (PyTorch, TensorFlow, or similar)
- Experience building CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.)
- Hands-on experience with containerization (Docker) and orchestration
- Experience managing GPU workloads and distributed training systems
- Experience with cloud platforms (AWS, GCP, or Azure)
- Strong understanding of automation, infrastructure reliability, and data pipelines
- Ability to work with both European and US developers.
Nice To Haves
- Experience with motion capture or computer vision systems
- Familiarity with experiment tracking tools (MLflow, Weights & Biases, etc.)
- Background in distributed systems or high-performance computing
- Experience with workflow orchestration tools (Airflow, Argo, Prefect, Kubeflow)
- Infrastructure as Code experience (Terraform, Pulumi, CloudFormation)
- Experience with model optimization, inference acceleration, or edge deployment
- Experience building tracking algorithms for device localization using techniques like SLAM
- Strong problem-solving skills and attention to reproducibility
- Comfortable working in a remote, collaborative environment, with international team members
- Clear communicator who can bridge research and production engineering
- Passion for building scalable AI infrastructure
Responsibilities
- Design and maintain automated ML training pipelines.
- Build infrastructure for large-scale distributed experimentation.
- Develop CI/CD workflows tailored for machine learning systems.
- Orchestrate data ingestion, preprocessing, validation, and model versioning.
- Implement experiment tracking, hyperparameter tuning automation, and reproducibility systems.
- Optimize GPU/compute utilization across cloud and on-prem environments.
- Deploy, monitor, and maintain production ML models.
- Establish and enforce MLOps best practices including model registry, artifact management, and observability.
- Improve system reliability, performance, and security.
- Collaborate closely with ML researchers make new algorithms product ready.
- More typical DevOps responsibilities for software development as required.
Benefits
- 75% employer-paid medical for employee. Family coverage also included.
- 100% employer paid dental, and vision for employee and dependents
- 100% employer paid long-term, short-term disability, and life insurance policy
- 401k Match, if you’re contributing 5% we match 4%. 100% vested immediately.
- 10 paid holidays
- Starting at 15 days paid PTO (inclusive of sick and vacation time) annually
- Employee Assistance Program (EAP)
- Flexible Spending Account (FSA)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
1-10 employees
