Staff Machine Learning Engineer

Unity
Mountain View, CA, USAPosted 19 April 2026

Job Description

The opportunity At Unity, we're shaping the future of real-time 3D technology by building AI to transform how games are created and experienced. From intelligent authoring tools to new ways of interacting with content, we're engineering the next generation of pipelines that make 3D game development faster, more immersive, and more efficient. We're seeking a versatile, self-driven Staff Machine Learning Engineer to raise the bar on reliability, scalability, performance, and maintainability of our AI authoring products. You'll drive operational excellence via DevOps best practices, including CI/CD automation, Kubernetes management, infrastructure-as-code, agentic troubleshooting, and robust disaster recovery strategies. You'll establish cross-team standards for infrastructure and deployments, build a trustworthy A/B testing framework, manage software releases with client-server compatibility in mind, and drive observability across system health and business metrics. The systems you build will span high-level architecture down to hands-on implementation, powering asset generation, LLM inference, and the ML-driven tools that bring AI-assisted game creation to life. What you'll be doing Partner closely with product, design, and other engineering teams to influence the product roadmap. Contribute to technical strategy and architectural decisions for Unity AI and backend platforms, balancing short-term delivery with long-term product health. Design and implement sustainable, scalable solutions for Unity AI products, pushing the boundaries of the Unity Editor with cutting-edge AI agent technologies. Improve the reliability, performance, observability, security, and cost-efficiency of our backend systems, and support investigations into issues like performance regressions and network latency through strong observability and monitoring. Run technical spikes with developers to address application infrastructure needs on Microsoft Azure and Google Cloud. Build and mature the infrastructure and processes for promoting application code from development to production, writing high-quality, maintainable infrastructure-as-code and Helm deployments, and defining best practices for Terraform Cloud, Helm, and Kubernetes. What we're looking for Experience building and shipping complex, user-facing software products at scale Experience delivering and supporting cloud backend services using Terraform, Kubernetes, Helm, and CI/CD pipelines (e.g., Argo, GitHub Actions) Hands-on experience with Microsoft Azure or Google Cloud Platform Proven track record in observability, including monitoring, logging, alerting, and debugging tools such as Grafana to ensure system reliability and performance Strong grasp of software delivery best practices and network security, paired with a quality-first mindset Ability to translate business and user needs into technical solutions Strong communication and interpersonal skills, with a proven ability to align stakeholders across disciplines and organizations You might also have Exposure to ML infrastructure or LLM inference deployment Backend service development experience, including API design Familiarity with networking, caching, real-time data pipelines, and relational databases such as PostgreSQL Familiarity with languages such as C#/.NET, Python, or Go Familiarity with Unity or similar 3D engines Additional information International relocation support 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 ... (truncated, view full listing at source)
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