Senior Machine Learning Engineer, ML Infrastructure- Online

Unity Technologies; Seattle (WA); On-site; USD 187,000 - 243,000; Full time

Job summary

Unity Technologies in Seattle is seeking a Senior ML Engineer to design and evolve Unity Vector’s online model inference platform. You will build reliable production infrastructure for serving ML models with low latency and high reliability, and enable safe experimentation at scale.

You will work closely with ML engineers, platform teams, and product stakeholders to ensure models can be deployed, scaled, monitored, and iterated on efficiently.

Qualifications

• Experience building and operating production-grade online ML inference systems.
• Experience with model serving frameworks such as Triton, TorchServe, Ray Serve, or TensorFlow Serving.
• Experience optimizing inference workloads (dynamic batching, quantization, GPU acceleration, kernel tuning).
• Strong experience with distributed systems, Kubernetes, autoscaling, and production observability.
• Strong Python programming skills for production ML systems.
• Experience with PyTorch and model packaging, validation, and serving lifecycle management.
• Experience designing infrastructure for safe model rollout, canary testing, and automated rollback.
• Ability to reason about latency, throughput, reliability, and cost tradeoffs in online systems.

Responsibilities

• Design and operate large-scale online inference infrastructure with low latency and high reliability.
• Develop infrastructure supporting distributed training workflows (e.g., PyTorch, Ray Data, Ray Train).
• Integrate ML pipelines with workflow orchestration (Flyte, Airflow) for multi-stage training workflows.
• Optimize model performance via compilation, GPU/CPU utilization, scheduling, and kernel fusion.
• Improve observability of ML systems (latency, throughput, error-rate, cost, model-health).
• Collaborate with ML engineers to accelerate model iteration while ensuring safety and scalability.
• Improve reliability and reproducibility of serving workflows (packaging, validation, deployment automation).
• Lead architectural improvements to make the platform robust and cost-efficient.

Skills

Production ML infra

Distributed systems

System design

Observability

Performance optimization

Leadership (influence)

Tools

NVIDIA Triton Inference Server

TorchServe

Ray Serve

TensorFlow Serving

Kubernetes

Python

PyTorch

Flyte/Airflow

Job description

The Role

We are seeking a Senior ML engineer to design and evolve Unity Vector’s 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 you'll be doing

• Design and operate large-scale online inference infrastructure that serves production ML models with low latency and high reliability, such as PyTorch, Triton Inference Server, Kubernetes, GKE, Ray, or similar distributed serving frameworks.


• Develop infrastructure that supports distributed training workflows using technologies such as Pytorch, Ray Data, and Ray Train, etc.


• Integrate ML pipelines with workflow orchestration systems (e.g., Flyte, Airflow, or similar) to enable reliable multi-stage training workflows


• Optimize model performance through model compilation, GPU/CPU utilization improvements, request scheduling, kernel fusion, and runtime-level tuning.


• Improve observability of ML systems through latency, throughput, error-rate, cost, saturation, and model-health monitoring.


• 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 we're looking for

• Experience building and operating production‑grade online ML inference systems, such as NVIDIA Triton Inference Server, TorchServe, Ray Serve, TensorFlow Serving, or similar 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


• $187,200$-$243,300

This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate’s relevant experience, professional background, and skill set.

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 world’s 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 www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators.

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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.

This posting is intended to fill an existing vacancy, and we are committed to providing applicants with updates throughout the hiring process in accordance with applicable law.

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