{"id":3344517,"url":"https://alion.io/job/disney-india-staff-product-software-engineer-ml","title":"Staff Product Software Engineer (ML)","company":{"id":3300,"name":"Disney India","domain":"disney.in","url":"https://alion.io/company/disney-india","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","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":35000,"max_usd":81000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Datadog","optional":false},{"name":"Machine Learning","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scrum","optional":false}],"status":"live","first_seen_at":"2026-10-27T16:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-27T16:35:00Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"As a Lead Machine Learning Engineer, you will play a leading role in shaping the technical direction of the NewsML platform. You will drive infrastructure for scalable learning, inference, and monitoring, conduct in-depth data exploration and analysis, and collaborate across product, data, and engineering teams to power exceptional, personalized guest experiences. Your work will directly support strategic initiatives to help shape the roadmap for algorithmic innovation while ensuring that solutions are scalable, impactful, and aligned with stakeholder needs.\n\nThe core responsibilities for the job include the following:\n\n80% of Time: \nOwn complex technical initiatives end-to-end, from technical design through production deployment and operational excellence.\nDesign and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries.\nDrive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, auto-generated tagging solutions, and RAGs.\nPartner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions.\nStrategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution.\n\n20% of Time: \nChampion engineering best practices across code quality, testing, CI/CD, observability, and incident response.\nMentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement.\nContribute to technical documentation and promote knowledge sharing across teams.\n\nRequirements: \nBachelor's degree in computer science, information systems, statistics, math, or a comparable field of study, and/or equivalent work experience.\n8+ years of experience building and operating ML engineering systems in production environments.\nExpertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems.\nComfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training, and low-latency online serving.\nExperience designing and developing backend microservices for large-scale distributed systems using REST.\nExperience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize).\nFamiliarity with developing and deploying Spark and ML pipelines.\nHands-on experience with big data technologies such as Databricks, Kinesis, and Kafka.\nProven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals.\nExperience with observability tools for metrics, logging, and monitoring such as Datadog.\nExperience working in Agile/Scrum development environments.\nExcellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment.\nSkills\nAWS, Cloud, Data Science, Deep Learning, Glue, Lambda, ML, Machine Learning, Statistics, Step 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