Staff Machine Learning Engineer, ML Infrastructure Online

The opportunity

Unity Vector builds ML infrastructure that powers real-time prediction experimentation attribution and AI-driven decision-making across the company.

Our online ML systems serve production models at scale supporting low-latency inference large-scale experimentation model deployment and optimization feature processing and business-critical decisioning. As model complexity traffic volume and experimentation velocity continue to grow our inference platform must remain reliable scalable observable and cost-efficient.

To support this growth we need strong technical ownership to evolve the online ML infrastructure that enables ML teams to safely deploy validate and operate production models at scale.

The Role

We are seeking a senior/staff ML engineer to design and evolve Unity Vectors online model inference platform. This role focuses on 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 can be deployed scaled monitored and iterated on efficiently. You will play a key role in shaping how models are packaged served validated monitored and optimized in production environments.

This role requires strong systems thinking deep experience with production ML infrastructure and the ability to drive architectural improvements across teams.

What youll be doing

• Design and operate large-scale online inference infrastructure that serves production ML models with low latency and high reliability.
• Build and improve model serving systems using technologies such as PyTorch Triton Inference Server Kubernetes GKE Ray or similar distributed serving frameworks.
• Optimize inference performance through batching model compilation GPU/CPU utilization improvements request scheduling and runtime-level tuning.
• Develop infrastructure for model deployment canary testing A/B experimentation traffic splitting rollback and production validation.
• Improve observability of online ML systems through latency throughput error-rate cost saturation and model-health monitoring.
• Build self-healing and autoscaling capabilities to support dynamic experiment traffic changing model complexity and production reliability requirements.
• Partner closely with ML engineers to support faster model iteration while maintaining production safety scalability and cost efficiency.
• Improve the reliability and reproducibility of model serving workflows including model packaging artifact validation compatibility testing and deployment automation.
• Lead architectural improvements that make the online ML platform more robust user-friendly scalable and cost-efficient.

What were looking for

• 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.

Additional information

• Relocation support is not available for this position
• Work visa/immigration sponsorship is not available for this position

Benefits
At Unity we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility specific offerings and coverage vary based on the country and employment status.

While specific benefits vary here are some of the ways we strive to take care of our eligible team members globally: 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

Life at Unity
Unity NYSE: U is the worlds leading game engine powering play for more than 3 billion consumers each month. The top mobile games in the world the most played PC indie titles the most innovative console games and virtually all of the top XR and Web Games are developed deployed and grown in Unity. Unity also enables teams across industries like automotive manufacturing and healthcare to design simulate and collaborate in 3D closing the gap between ideas and reality. For more information please visit .

Unity is an equal opportunity employer committed to fostering an inclusive innovative environment with the best employees. Therefore we provide employment opportunities without regard to age race color ancestry national origin disability gender or any other protected status in accordance with applicable law. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

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