{"id":631542,"url":"https://alion.io/job/walt-disney-company-senior-machine-learning-engineer-espn","title":"Senior Machine Learning Engineer - ESPN","company":{"id":4283,"name":"Walt Disney Company","domain":"disney.com","url":"https://alion.io/company/walt-disney-company","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":87,"open_postings":90,"ghost_share":0.022,"stale_share":0.644,"repost_share":0.033,"time_to_fill_p50_days":19,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Glendale, United States","San Francisco, United States","New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":148700,"max":199400,"currency":"USD","period":"year","gross":null,"usd_annual":199400},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Kinesis","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"C++","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-07-17T00:00:00Z","employer_posted_date":"2026-07-17","last_verified_at":"2026-10-31T22:19:46Z","board_verified":true,"closed_at":null,"days_open":107,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":106},"description":"Job Posting Title:\nSenior Machine Learning Engineer - ESPNReq ID:\n10150610Job Description:\nDisney Entertainment & ESPN Technology\nOn any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.\nA few reasons why we think you’d love working for Disney Entertainment & ESPN Technology\nBuilding the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.\n\nReach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day - from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.\n\nInnovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.\n\nProduct Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.\nJob Summary:\nESPN is investing in large-scale data infrastructure and real-time processing platforms that power next-generation personalization and live sports experiences. As a Machine Learning Engineer, you will focus on building and operating distributed data and ML infrastructure that supports high-throughput, low-latency data processing and real-time ML use cases.\nIn this role, you will work closely with senior MLEs, data engineers, platform/SRE, and product teams to develop streaming data pipelines, feature computation systems, and ML-adjacent services that operate reliably at scale. The role emphasizes hands-on engineering, strong fundamentals in distributed systems, and practical experience operating production data infrastructure.\nResponsibilities and Duties of the Role:\n1) Large-Scale Data Processing & Streaming Systems\nBuild and maintain high-throughput batch and streaming data pipelines to support ML, analytics, and real-time decisioning use cases.\n\nImplement data ingestion, enrichment, aggregation, and transformation workflows using modern distributed data frameworks.\n\nEnsure pipelines meet latency, reliability, and data quality requirements for downstream ML and product teams.\n\n2) Real-Time Data & Feature Infrastructure\nDevelop and operate systems that support real-time feature computation and delivery for online ML services.\n\nWork with feature stores and event-driven architectures to ensure consistency between offline and online data.\n\nImprove data freshness, schema evolution, and backward compatibility in streaming environments.\n\n3) ML-Adjacent infrastructure & Platform Engineering\nBuild and operate ML-adjacent services such as inference inputs, feature APIs, and data access layers.\n\nContribute to scalable service patterns including autoscaling, rollout strategies, and resiliency mechanisms.\n\nPartner with platform/SRE teams to improve system availability, performance, and cost efficiency.\n\n4) Reliability, Observability & Operations\nInstrument data and ML infrastructure with metrics, logging, and alerting to support production operations.\n\nParticipate in on-call rotations and incident response for data and ML platforms.\n\nIdentify and remediate data pipeline failures, performance regressions, and operational risks.\n\n3) Collaboration & Engineering Execution\nCollaborate with applied ML and data science teams to enable production ML workflows through reliable data systems.\n\nParticipate in design reviews, code reviews, and technical discussions.\n\nFollow established platform standards and contribute incremental improvements over time\n\nRequired Education, Experience/Skills/Training:\nBasic Qualification:\nExperience building and operating large-scale data or ML systems in production.\n\nStrong fundamentals in distributed systems and data processing architectures.\n\nHands-on experience with streaming and batch data technologies (e.g., Kafka, Kinesis, Spark, Flink, or equivalent).\n\nProficiency in Python and working knowledge of Java, Scala, Go, or C++.\n\nExperience operating systems in cloud-native environments (AWS, containers, Kubernetes, IaC tools).\n\nFamiliarity with observability and operational best practices for production systems.\n\nStrong collaboration skills and ability to work effectively across engineering and data teams\n\nPreferred qualification:\nExperience supporting real-time personalization, recommendation, or analytics systems.\n\nFamiliarity with feature stores, event-driven architectures, and real-time ML pipelines.\n\nExposure to ML infrastructure concepts such as inference pipelines, data validation, and model lifecycle tooling.\n\nExperience optimizing data systems for latency, throughput, and cost efficiency.\n\nUnderstanding of experimentation platforms and data instrumentation for online systems.\n\nExperience with:\n5+ years of industry experience building data-intensive or ML-adjacent systems in production\n\nRequired Education\nBachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related field\n\nThe hiring range for this position in New York, NY is $148,700 - $199,400 per year and in Glendale, CA is $141,900 - $190,300. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.Job Posting Segment:\nProduct EngineeringJob Posting Primary Business:\nPE - Streaming BackendPrimary Job Posting Category:\nMachine LearningEmployment Type:\nFull timePrimary City, State, Region, Postal Code:\nGlendale, CA, USAAlternate City, State, Region, Postal Code:\nUSA - CA - Market St, USA - NY - 7 Hudson SquareDate Posted:\n2026-06-05","description_format":"text","description_chars":6577,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Film Production","Animation","Theme Parks & Attractions","Streaming & OTT Platforms"],"lifecycle":[{"event":"open","at":"2026-09-10T19:22:11Z"}],"visa":[],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.26,"p_room":0.28,"age_days":106,"expected_fill_days":19,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-31T05:58:55Z"},"pay":{"stated_usd_annual":199400,"is_top_pay":false},"html_url":"https://alion.io/job/walt-disney-company-senior-machine-learning-engineer-espn","json_url":"https://alion.io/job/walt-disney-company-senior-machine-learning-engineer-espn.json","meta":{"generated_at":"2026-11-01T04:27:20Z","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":6874,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-02T00:00:00Z"}},"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":4283},"rest":"https://alion.io/mcp/rest/get_company?id=4283"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fwalt-disney-company-senior-machine-learning-engineer-espn"},{"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%2Fwalt-disney-company-senior-machine-learning-engineer-espn"},{"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%2Fwalt-disney-company-senior-machine-learning-engineer-espn"},{"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/walt-disney-company-senior-machine-learning-engineer-espn\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fwalt-disney-company-senior-machine-learning-engineer-espn"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":631542}},{"tool":"search_jobs","arguments":{"company":"disney.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":631542},"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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