Senior Machine Learning Engineer, ML Infrastructure - Online
Shanghai, China
Posted 3 hours ago
Last seen 3 hours ago
Active
full-time
AI & Machine Learning
Job Summary
Join Unity Vector as a Senior Machine Learning Engineer to shape the future of online ML infrastructure, powering real-time prediction and AI-driven decision-making. You'll design and optimize large-scale inference platforms, ensuring reliability and efficiency for production ML models across high-traffic systems.
About this job
As a Senior Machine Learning Engineer, you will design and evolve Unity Vector’s online model inference platform. This role involves building reliable infrastructure for serving machine learning models in production, optimizing inference performance, and enabling safe, efficient experimentation across high-traffic online systems. You will work closely with ML engineers, platform teams, and product stakeholders to ensure models are deployed, scaled, monitored, and iterated on efficiently.
Requirements
- Strong experience building and operating production-grade online ML inference systems.
- Experience with model serving frameworks such as NVIDIA Triton Inference Server, TorchServe, Ray Serve, TensorFlow Serving, or similar systems.
- Experience optimizing inference workloads using techniques such as dynamic batching, model compilation, quantization, GPU acceleration, GPU kernel optimization, caching, or runtime tuning.
- Strong experience with distributed systems, Kubernetes, autoscaling, service reliability, and production observability.
- Strong programming skills in Python, with practical experience working on production ML systems and high-scale services.
- Experience with PyTorch and modern model deployment workflows, including model packaging, validation, and serving lifecycle management.
- Experience designing infrastructure for safe model rollout, canary testing, A/B experimentation, and automated rollback.
- Strong systems thinking, with the ability to reason about latency, throughput, reliability, scalability, and cost tradeoffs in online systems.
- Proven ability to lead technical direction and influence architectural decisions across teams without formal authority.
Benefits & Perks
- Comprehensive health, life, and disability insurance
- Commute subsidy
- Employee stock ownership
- Competitive retirement/pension plans
- Generous vacation and personal days
- Support for new parents through leave and family-care programs
- Office food snacks
- Mental Health and Wellbeing programs and support
- Employee Resource Groups
- Global Employee Assistance Program
- Training and development programs
- Volunteering and donation matching program
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