Senior Machine Learning Engineer, ML Efficiency
New
J
JobgetherTechnology
Based in United StatesFull-TimeSenior
Salary$216,700 - $303,400 USD
Apply NowOpens the employer's application page
Job Details
- Required Skills
- Machine LearningPyTorch
Requirements
- Deep experience working with production machine learning systems and large-scale ML workloads.
- Proven track record of improving ML training or inference efficiency with measurable performance outcomes.
- Strong understanding of optimization strategies across model-level, runtime-level, and infrastructure-level systems.
- Experience owning complex technical projects from concept through implementation and impact measurement.
- Ability to balance short-term performance improvements with long-term scalability, adoption, and maintainability.
- Strong communication skills with the ability to explain complex technical tradeoffs clearly to engineering and partner teams.
- Experience with GPU training or serving optimization (preferred).
- Experience with PyTorch, distributed training frameworks, or kernel/runtime optimization (preferred).
- Familiarity with efficiency benchmarking, launch certification systems, cost monitoring, or model deployment optimization techniques such as quantization, pruning, distillation, or checkpoint optimization.
Responsibilities
- Own high-value optimization projects across machine learning training, inference, serving systems, and launch-readiness workflows.
- Diagnose performance bottlenecks in production environments using profiling, benchmarking, monitoring, and observability tools.
- Develop optimization frameworks, performance tooling, efficiency playbooks, and reusable engineering capabilities that benefit multiple teams.
- Improve model launch readiness by contributing to load testing, reliability improvements, fallback strategies, latency monitoring, and cost visibility.
- Partner with applied ML engineers, platform teams, and infrastructure owners to implement practical solutions while maintaining scalability and maintainability.
- Influence technical direction by identifying recurring challenges, automation opportunities, and patterns that can be standardized across engineering teams.
- Mentor engineers by sharing expertise in debugging, measurement-driven development, system optimization, and technical execution.
View Full Description & ApplyYou'll be redirected to the employer's site
