Senior Machine Learning Infrastructure Engineer
WFA Digital Insight
The demand for machine learning specialists grew 25% in 2025, driven by the need for real-time data processing. Unity's Vector Ads team is at the forefront of this trend, and this role offers a unique chance to work on a high-scale, low-latency environment. With a strong background in systems engineering and ML infrastructure, candidates can expect a competitive environment with a company that's committed to innovation. Before applying, candidates should be aware of the importance of collaboration and communication in a remote-first environment, as well as the need for continuous learning in the field of machine learning.
Job Description
About the Role
The Senior Machine Learning Infrastructure Engineer will be responsible for designing, building, and maintaining the infrastructure that serves ML models in real-time across Unity's ads ecosystem. This is a high-scale, low-latency environment that processes billions of requests daily, requiring a strong background in systems engineering and ML infrastructure. The successful candidate will be part of the Vector Ads team, which is responsible for building the real-time systems that power Unity's global advertising platform.The role entails working closely with ML engineers to productionize models, manage model deployments, and improve iteration speed. The Senior Machine Learning Infrastructure Engineer will also be responsible for improving the observability, performance, and cost-efficiency of ML serving infrastructure. This is a great opportunity for an engineer who is excited to work at the intersection of ML systems and distributed infrastructure.
The Vector Ads team is a dynamic and innovative group that is committed to delivering fast, relevant ads to players around the world. The team is passionate about using machine learning to improve the player and advertiser experience, and the Senior Machine Learning Infrastructure Engineer will play a key role in achieving this goal.
What You Will Do
- Design, build, and maintain the infrastructure that serves ML models in real-time across Unity's ads ecosystem
- Build and operate scalable model serving pipelines, owning latency, throughput, and reliability in a high-QPS production environment
- Partner with ML engineers to productionize models, manage model deployments, and improve iteration speed
- Improve observability, performance, and cost-efficiency of ML serving infrastructure
- Contribute to architectural decisions around feature serving, model versioning, and inference optimization
- Collaborate with cross-functional teams to ensure seamless integration of ML models into the ads ecosystem
- Develop and maintain tools and scripts to automate ML model deployment and monitoring
- Troubleshoot and resolve issues with ML model serving and infrastructure
- Participate in on-call rotations to ensure 24/7 coverage of ML infrastructure
What We Are Looking For
- Experience building and operating ML infrastructure or model serving systems in production
- Proficiency in Golang or Python, with strong systems engineering fundamentals
- Hands-on experience with Kubernetes and container orchestration at scale
- Familiarity with ML serving frameworks such as Ray Serve, Triton, TorchServe, or similar
- Understanding of distributed systems, API design, and system reliability
- Strong collaboration and communication skills in a remote-first environment
- Experience with feature stores, feature pipelines, or online/offline feature serving
- Background in ad tech, real-time bidding, or programmatic advertising systems
- Familiarity with infrastructure-as-code such as Terraform
Nice to Have
- Experience with observability tooling such as Prometheus, Grafana, or OpenTelemetry
- Background with real-time data pipelines, caching layers, or low-latency serving systems
- Familiarity with cloud-based technologies such as AWS or GCP
- Experience with CI/CD pipelines and automated testing
Benefits and Perks
- Competitive salary and benefits package
- 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 and mental health and wellbeing programs
- Global Employee Assistance Program and training and development programs
- Volunteering and donation matching program
- Flexible working hours and remote work options
- Access to the latest technologies and tools
- Opportunities for career growth and professional development
How to Stand Out
- Tip: Make sure to highlight your experience with machine learning infrastructure and model serving systems in your resume and cover letter.
- Tip: Be prepared to discuss your experience with Kubernetes and container orchestration, as well as your understanding of distributed systems and API design.
- Tip: Show your passion for working at the intersection of ML systems and distributed infrastructure, and be ready to provide examples of your experience in this area.
- Tip: Familiarize yourself with Unity's products and services, and be prepared to discuss how your skills and experience align with the company's goals and mission.
- Tip: Don't be afraid to ask questions during the interview process, and be sure to ask about the company culture and values.
- Tip: Be prepared to provide examples of your experience with collaboration and communication in a remote-first environment, and highlight your ability to work independently and as part of a team.
- Tip: Consider creating a portfolio or GitHub repository that showcases your experience and skills, and be prepared to discuss your projects and accomplishments during the interview process.
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