AI Summary
OptiTrack is seeking a Machine Learning Engineer to design, automate, and scale an MLOps system. The role involves building infrastructure for large-scale distributed experimentation, developing CI/CD workflows, and optimizing GPU/compute utilization. The ideal candidate will have experience with Python, ML frameworks, and cloud platforms.
Key Highlights
Design and maintain automated ML training pipelines
Build infrastructure for large-scale distributed experimentation
Optimize GPU/compute utilization across cloud and on-prem environments
Key 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
Collaborate closely with ML researchers make new algorithms product ready
Technical Skills Required
Benefits & Perks
75% employer-paid medical for employee
100% employer-paid dental, and vision for employee and dependents
100% employer-paid long-term, short-term disability, and life insurance policy
Nice to Have
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)
Job Description
OptiTrack is a global leader in motion capture technology, delivering precision tracking solutions for animation, robotics, virtual production, biomechanics, and industrial applications.
About The Role
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.
What You'll Do
- 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
Required Qualifications
- 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.
Interested in remote work opportunities in Machine Learning & AI? Discover Machine Learning & AI Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- 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
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Work on cutting-edge motion tracking systems
- Contribute to technology used across robotics, animation, virtual reality, biomechanics, and virtual production
- Remote-first flexibility
- Opportunity to shape the next-generation of motion capture technology
All benefits start on first day of employment!
- 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)
OptiTrack is an equal opportunity employer, we believe in fostering a culture of equality, diversity, and inclusivity. Our commitment to this goal is clearly expressed in our zero-tolerance policy for discrimination and harassment of any kind, including on the basis of race, color, sex, age, religion, sexual orientation, national origin, disability, genetic information, pregnancy, protected veteran status or any other characteristic protected by applicable federal, state, or local laws. Our hiring practices ensure that decisions are based solely on qualifications, merit, and current business needs, while extending to all aspects of our operations - from recruitment and promotion to layoff and recall, to leave of absence, compensation, benefits, and training. We are committed to remaining a drug free workplace
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