Staff Machine Learning Engineer

Our vision is to build a thriving entertainment ecosystem where stories and worlds are imagined, brought to life and experienced. We create for every age and audience, anchored by the strength of our content and experiences and the depth of our connection with fans. We are creator-first, audience-focused, tech-forward, globally scaled.

• →Own the architecture and roadmap of the model serving runtime, supporting multiple ML frameworks and inference engines behind one control plane
• →Lead large-scale migrations and rollouts of production models onto the platform with zero viewer-facing regressions
• →Build and maintain serving backends, model configurations and batching strategies that meet strict tail-latency targets at high request volume
• →Design autoscaling, capacity management and multi-region resilience for latency[1]critical serving across Max, Discovery+ and other WBD offerings
• →Drive observability, cost optimization and performance tuning across the serving fleet, including hardware selection, GPU and CPU utilization, and model optimization
• →Define the contract between model training and serving so a validated model artifact deploys to production through standard, automated paths
• →Establish per-model SLOs with model owners and build the telemetry that proves them
• →Collaborate with applied scientists, partner engineering teams and the core infrastructure team as the platform onboards new models, runtimes and markets
• →Author, test, review and optimize production-level code in Python while executing best practices in version control, CI/CD and code integration
• →Take part in the platform on-call rotation and lead incident reviews that result in design changes, not just fixes
• →Contribute design documents and technical documentation to support architecture decisions, knowledge transfer and sharing
• →Mentor engineers, raise the bar in design and code reviews, and represent the platform in cross-team architecture decisions
  

• 9+ years of industry experience
• 5+ years of experience building or operating production ML infrastructure or comparable low-latency, large-scale distributed systems with a large customer base
• Hands-on experience running model inference in production at scale
• Strong Kubernetes fundamentals and experience running GPU and CPU workloads on it
• Proven performance engineering skills: profiling, tail-latency analysis, batching and concurrency under load
• 7+ years of programming experience in Python, plus working fluency in a systems language such as C++, Go or Rust
• Good practical knowledge of the modern machine learning lifecycle, from training artifacts through deployment, rollout and monitoring
• Strong architectural and design skills, with a track record of leading multi-quarter technical initiatives across teams
• Operational maturity: experience owning a tier-1 service, including on-call
• Experience with one of the cloud platforms AWS/GCP/Azure, Docker and Kubernetes, and CI/CD tools like GitHub Actions, Jenkins etc.
• Excellent written and verbal communication skills; comfortable contributing to technical documentation and on-call support
• Ability to technically collaborate with partners across time zones
  

• Experience extending an inference server with custom backends, or contributing to an open-source serving runtime
• Background in recommendation, ranking or search systems and their latency and freshness constraints
• Experience building an internal platform that other teams adopted self-service
• Working experience with global teams

Skydance is a next-generation global media and entertainment company, comprised of three business segments: Studios, Direct-to-Consumer, and TV Media. Skydance's portfolio unites legendary brands, including Paramount, Warner Bros., HBO and HBO Max, Paramount+, Pluto TV, CBS, CNN, CBS Sports, TNT Sports, Nickelodeon, Cartoon Network, MTV, Food Network, BET, HGTV, and Comedy Central.

We embrace the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit. In line with the laws of the country or region in which the role is based, this includes consideration without regard to race, color, ethnicity, national origin, citizenship status, religion or belief, sex, gender, gender identity or expression, sexual orientation, age, marital status, pregnancy, parenthood, physical or mental disability, genetic information, military or protected veteran status, union status or any other category protected by applicable law.

If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.