{"id":3542829,"url":"https://alion.io/job/warner-bros-discovery-staff-machine-learning-engineer","title":"Staff Machine Learning Engineer","company":{"id":21042,"name":"Warner Bros. Discovery","domain":"wbd.com","url":"https://alion.io/company/warner-bros-discovery","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":78,"open_postings":23,"ghost_share":0,"stale_share":0.87,"repost_share":0,"time_to_fill_p50_days":26,"computed_at":"2026-11-08T05:47:12Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":82000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"SLI/SLO/SLA","optional":false}],"status":"closed","first_seen_at":"2026-10-30T19:48:41Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-04T19:03:43Z","board_verified":false,"closed_at":"2026-11-04T19:03:43Z","days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Storytelling is, and will always be, the heart of what we do at Skydance.\nOur 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.\nHere, you’ll work with talented teams that move fast, think boldly and collaborate with purpose to deliver results. We aim high, champion the best ideas and win together, earning the trust of our employees, creators, partners and audiences every day.\nIf you’re energized by the opportunity to help build the next-generation global media and entertainment company powered by creativity and technology, we’d be thrilled to welcome you aboard. LET’S GO!\nㅤ\nStaff Machine Learning Engineer \nWe are looking for a passionate Staff Machine Learning Engineer to build, run and scale the production inference platform behind search and personalization for the global streaming app Max as well as ongoing and future streaming initiatives. Every recommendation, search result and personalized row a viewer sees is served by a model running on this\nplatform, and it has to answer in milliseconds for 100+ million users worldwide.\nThe team, ML Infrastructure & Tools (MLIT), owns the deployment, lifecycle and inference of models for the Search & Personalization organization. We build and operate a shared, self-service inference platform on Kubernetes that serves models across multiple frameworks and runtimes behind one common control plane and model lifecycle. You will be the technical owner of that serving runtime. You are excited about working in a fast[1]moving environment that fosters engineering and operational excellence, and you believe a platform is only done when data scientists can ship models on it without you in the critical path.\nRoles & Responsibilities\nOwn the architecture and roadmap of the model serving runtime, supporting multiple ML frameworks and inference engines behind one control plane\nLead large-scale migrations and rollouts of production models onto the platform with zero viewer-facing regressions\nBuild and maintain serving backends, model configurations and batching strategies that meet strict tail-latency targets at high request volume\nDesign autoscaling, capacity management and multi-region resilience for latency[1]critical serving across Max, Discovery+ and other WBD offerings\nDrive observability, cost optimization and performance tuning across the serving fleet, including hardware selection, GPU and CPU utilization, and model optimization\nDefine the contract between model training and serving so a validated model artifact deploys to production through standard, automated paths\nEstablish per-model SLOs with model owners and build the telemetry that proves them\nCollaborate with applied scientists, partner engineering teams and the core infrastructure team as the platform onboards new models, runtimes and markets\nAuthor, test, review and optimize production-level code in Python while executing best practices in version control, CI/CD and code integration\nTake part in the platform on-call rotation and lead incident reviews that result in design changes, not just fixes\nContribute design documents and technical documentation to support architecture decisions, knowledge transfer and sharing\nMentor engineers, raise the bar in design and code reviews, and represent the platform in cross-team architecture decisions\nWhat to Bring\n9+ years of industry experience\n5+ years of experience building or operating production ML infrastructure or comparable low-latency, large-scale distributed systems with a large customer base\nHands-on experience running model inference in production at scale\nStrong Kubernetes fundamentals and experience running GPU and CPU workloads on it\nProven performance engineering skills: profiling, tail-latency analysis, batching and concurrency under load\n7+ years of programming experience in Python, plus working fluency in a systems language such as C++, Go or Rust\nGood practical knowledge of the modern machine learning lifecycle, from training artifacts through deployment, rollout and monitoring\nStrong architectural and design skills, with a track record of leading multi-quarter technical initiatives across teams\nOperational maturity: experience owning a tier-1 service, including on-call\nExperience with one of the cloud platforms AWS/GCP/Azure, Docker and Kubernetes, and CI/CD tools like GitHub Actions, Jenkins etc.\nExcellent written and verbal communication skills; comfortable contributing to technical documentation and on-call support\nAbility to technically collaborate with partners across time zones\nPreferred\nExperience extending an inference server with custom backends, or contributing to an open-source serving runtime\nBackground in recommendation, ranking or search systems and their latency and freshness constraints\nExperience building an internal platform that other teams adopted self-service\nWorking experience with global teams\nAbout Skydance\nSkydance 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.\nSome Important Details\nWe 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.\nIf 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.","description_format":"text","description_chars":6518,"description_truncated":false,"requirements":{"experience_years_min":9,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Film Production","TV Production","Streaming & OTT Platforms"],"lifecycle":[{"event":"open","at":"2026-10-30T19:48:41Z"},{"event":"close","at":"2026-11-04T19:03:43Z"}],"visa":[],"liveness":null,"pay":null,"html_url":"https://alion.io/job/warner-bros-discovery-staff-machine-learning-engineer","json_url":"https://alion.io/job/warner-bros-discovery-staff-machine-learning-engineer.json","meta":{"generated_at":"2026-11-08T08:37:46Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":18702,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-09T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":21042},"rest":"https://alion.io/mcp/rest/get_company?id=21042"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fwarner-bros-discovery-staff-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fwarner-bros-discovery-staff-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fwarner-bros-discovery-staff-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/warner-bros-discovery-staff-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fwarner-bros-discovery-staff-machine-learning-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3542829}},{"tool":"search_jobs","arguments":{"company":"wbd.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3542829},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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