about 3 hours ago
Remote, CanadaSenior / Mid Level
H1B Sponsor
Responsibilities
- Design, build, and operate core AI platform components for machine learning models.
- Own model serving and inference workflows, improving reliability and performance.
- Lead optimization efforts for inference systems across CPU and GPU workloads.
- Manage GPU-based inference and training workloads, focusing on performance tuning.
- Improve model lifecycle processes including packaging, versioning, and deployment.
- Implement observability practices for ML services and pipelines.
- Collaborate with product, infrastructure, and security teams to design scalable capabilities.
- Contribute to technical design discussions and mentor junior engineers.
- Participate in operational processes like incident response and post-incident reviews.
Requirements
- Bachelor’s degree with 4–6 years of relevant experience or a Master’s degree with significant hands-on experience.
- Strong experience in Python for machine learning systems and backend services.
- Proven experience deploying ML workloads in cloud environments.
- Solid understanding of model serving architectures and performance tradeoffs.
- Hands-on experience with GPU-based workloads in production settings.
- Experience designing CI/CD pipelines for reliable ML system deployment.
- Ability to independently drive technical initiatives while balancing priorities.
- Strong problem-solving skills for debugging performance issues in distributed systems.
- Effective communication skills for collaboration across teams.
Benefits
- Generous performance-based bonus plans for eligible employees.
- Rich medical, dental, and vision coverage.
- Generous retirement contributions with immediate vesting.
- Quarterly wellness days for all employees.
- Country-specific holidays plus a day off for your birthday.
- One-time home office stipend.
- Annual professional development budget.
- Quarterly well-being stipend.
- Considerable paid parental leave.
- Employee referral bonus program.
- Other benefits vary by country.