{"id":2033665,"url":"https://alion.io/job/comcast-corporation-machine-learning-engineer-xumo","title":"Machine Learning Engineer-Xumo","company":{"id":9377,"name":"Comcast","domain":"comcast.com","url":"https://alion.io/company/comcast-corporation","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Irvine, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":142651,"max":190201,"currency":"USD","period":"year","gross":null,"usd_annual":190201},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"BigQuery","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Machine Learning","optional":false},{"name":"MySQL","optional":false},{"name":"Oracle","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Recommender Systems","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CentOS Stream","optional":true},{"name":"GCP","optional":true},{"name":"Linux","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-07T15:12:15Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T00:33:44Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Xumo, a joint venture between Comcast and Charter Communications, was formed to develop and offer a next-generation streaming platform for the entire entertainment industry. The company consists of three primary lines of business: Xumo devices, Xumo Play, and Xumo Enterprise. Powered by Comcast’s global entertainment platform, Xumo devices feature a world-class user interface with universal voice search capabilities, making it easy for consumers to find and enjoy their favorite streaming content. Xumo Play is a free ad-supported streaming TV (FAST) service offering hundreds of linear channels and on-demand options. Xumo Enterprise provides tools and services for content creators, distributors, and advertisers to make FAST content more accessible.Job Summary\nXUMO is looking for a highly experienced and motivated ML Engineer to solve business problems by designing and training sophisticated machine learning algorithms and implementing our core recommendation system, which will collaborate with multiple systems to increase product engagement.As the ML Engineer for the XUMO Software Engineering Team, you’ll develop complex predictive models using huge amounts of data, create scalable algorithmic solutions to solve business problems, and work with team members to architect and lead the development of the recommendation engine's intelligence. Utilizing tools like Python, BigQuery, and modern ML frameworks, you will build the personalization algorithms that immerse millions of viewers through streaming devices. To succeed in this role, it is necessary to continuously provide clear technical solutions and algorithmic strategies which satisfy the business requirements from the product and operation teams.\nThis job focuses on developing machine learning algorithms for products, training models, and deployment. It involves data pipeline management, technical documentation, and innovation via patents and APIs. The role evaluates ML solutions, conducts case studies, and designs proofs of concept. Team collaboration and junior engineer mentorship are key components.\nJob Description\nPosition Duties:\nAnalyze big data to drive algorithmic insights\nCollaborate with the data team to analyze massive datasets, extracting key user behavioral features and defining quantitative metrics to evaluate model performance.\nEngineer high-quality feature sets and training data schemas optimized specifically for training and serving recommendation algorithms.\nDesign and execute rigorous offline model evaluations and online A/B tests, generating deep insights on algorithmic performance against established baselines and benchmarks.\nDevelopment of Recommendation System\nCollaborate with product and operations teams to translate business requirements into algorithmic solutions, documenting model architectures and logic to align development tasks.\nRapidly prototype new recommendation concepts and algorithms, validating mathematical approaches and transitioning experimental models into high-quality, production-ready code.\nDevelop the core intelligence of the recommendation system, focusing on implementing, tuning, and scaling advanced machine learning models and the logic for multi-algorithm A/B testing.\nPlan and manage recommendation algorithm development\nCollaborate with backend and client engineering teams to integrate machine learning models seamlessly, prioritizing algorithmic enhancements and defining the optimal approaches for model serving and latency reduction.\nCreate comprehensive technical documentation detailing algorithmic behavior, model dependencies, and the specifications required for other systems to interact with the recommendation engine.\nDrive strategic decisions regarding model selection, hyperparameter optimization, and feature engineering to solve complex business problems, continuously improving the user experience through highly personalized content delivery.\nQualifications\n3+ years’ experience of using statistical computer languages (Python, R , etc.)\n3+ years’ experience of manipulating big data (Big Query, etc.)\n3+ years’ experience of operating database (MySQL, PostgreSQL, Oracle, MongoDB)\nExperienced and has knowledge of developing variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.\nExperienced and has knowledge of developing advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.\nStrong problem-solving skill with an emphasis on product development\nExcellent written, drawing, and verbal communication skills for coordinating across teams.\nStrong leads with designing, implementation skills to approach the solution for any new features or problem solving\nSelf-starter to able to work with minimal supervision for high-quality output\nAggressive learner for new technologies and techniques.\nPosition is office based in Irvine, CA 4 days/week in office & 1 day remote.\nDesirable Experiences\nExperience with operating servers on cloud-based environments (Google Cloud, AWS, Azure)\nExperience with data processing framework (Spark)\nExperience with working with Linux-based operation system (CentOS, OSX)\nExperience developing scalable and highly available applications\nExperience with recommendation services\nResponsibilities:\nDeveloping and enhancing machine learning algorithms for product and application integration, working with specifications and data pipeline architectures\nLeading the training of machine learning models, overseeing their validation and deployment into production systems\nCreating and maintaining data pipelines, ensuring efficient data ingestion, validation, cleaning, and monitoring processes\nAuthoring comprehensive documentation and technical requirements, including evaluation plans, white papers, and reports\nContributing to the creation of patents, Application Programming Interfaces (APIs), and other intellectual property\nEvaluating machine learning solutions from internal and external partners, leading testing and assessment initiatives\nConducting in-depth case studies and compile findings to inform product development and testing strategies\nDesigning and developing proof of concept solutions, directing studies that support the advancement of future products or applications\nCollaborating with cross-functional teams and provide technical solutions to complex issues associated with assigned projects\nOffering guidance and mentorship to junior engineers, setting a technical example within the team\nConsistent exercise of independent judgment and discretion in matters of significance.\nRegular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary.\nOther duties and responsibilities as assigned.\nEmployees at all levels are expected to:\nUnderstand our Operating Principles; make them the guidelines for how you do your job.\nOwn the customer experience think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.\nKnow your stuff be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.\nWin as a team make big things happen by working together and being open to new ideas.\nBe an active part of the Net Promoter System a way of working that brings more employee and customer feedback into the company by joining huddles, making call backs and helping us elevate opportunities to do better for our customers.\nDrive results and growth.\nSupport a culture of inclusion in how you work and lead.\nDo what's right for each other, our customers, investors and our communities.\nDisclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.\nSkills\nAlgorithms, Business Problems, Collaboration, Recommendation EnginesCompensation\nPay Range: This job can be performed in California with a good faith estimated pay range upon hire of $142,651.46 - $190,201.94 USD.Comcast intends to offer the selected candidate base pay within the posted range for this role at the time of posting dependent on job-related, non-discriminatory factors such as experience. The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality - to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details.\nEducation\nBachelor's DegreeWhile possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.Certifications (if applicable)\nRelevant Work Experience\n5-7 YearsComcast is an equal opportunity workplace. 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