Full Lifecycle AI/ML Engineering Lead
Tasks
- Build scalable platform integration
- Collaborate on edge deployment constraints
- Drive engineering best practices including automated testing
- Implement MLOps pipelines
- Integrate agentic workflows and AI assisted engineering tools
- Lead software engineering team
- Own software development lifecycle for product lines
- Partner with product managers on technical roadmaps
- Provide technical oversight for architecture and strategy
- Set up CI CD and monitoring for deployed models
Perks/Benefits
- Employee resource groups
- Flexible family care days
- Medical, dental & vision coverage
- Paid Holidays
- Paid parental leave
- Paid time off
- Prescription Drug Coverage
- Tuition assistance
Skills/Tech-stack
AWS | Agile | Automated testing | Azure | CI/CD | Cloud infrastructure | Computer Vision | Computer vision models | Data Engineering | Edge Computing | GCP | Industrial IoT | MLOps | Machine Learning | Model Inference | Model Monitoring | Model Training | Vision Models
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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