{"id":954085,"url":"https://alion.io/job/dyson-lead-mlops-engineer","title":"Lead Mlops Engineer","company":{"id":160,"name":"Dyson","domain":"dyson.com","url":"https://alion.io/company/dyson","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":91,"open_postings":61,"ghost_share":0,"stale_share":0.344,"repost_share":0.016,"time_to_fill_p50_days":30,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","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":28000,"max_usd":73000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":34},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Kubernetes","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-15T00:00:00Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-17T07:29:00Z","board_verified":true,"closed_at":null,"days_open":32,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":32},"description":"Role purposeLead the design, delivery and operation of robust, production-grade MLOps/AIOps capabilities that move Dyson’s ML, AI and GenAI/agent\nsystems from development into reliable production, and keep them healthy at scale.\nOwn and evolve the engineering patterns for CI/CD, cloud infrastructure, deployment, monitoring and lifecycle management, and set the\nstandards followed across the Data Science and AI estate\nRole overview\nCombines hands-on engineering with technical leadership\nLeads deployment and operation of scalable ML and AI/agent systems\nDesigns and runs CI/CD pipelines and cloud infrastructure\nImplements monitoring, logging, evaluation and lifecycle management\nWorks closely with data science, AI engineering, platform, security and governance teams\nEnsures solutions are reliable, secure and compliant with organisational standards\nMentors engineers and raises the bar for engineering practices across the team and drives continuous improvement\nKey responsibilities\nBuild & Deploy\nDesign, build and maintain CI/CD pipelines for ML, AI and agent systems\nDeploy and operate ML models and AI/agents in production (e.g. Cloud Run, containerised services)\nDevelop containerisation and orchestration strategies\nPlatform & Infrastructure\nArchitect and manage solutions on cloud infrastructure (GCP) and Infrastructure as Code (Terraform)\nOptimise infrastructure for performance, scalability and cost\nDefine and evolve the MLOps/AIOps platform roadmap, aligning with AI, cloud and governance strategies\nObservability & Quality\nImplement monitoring, logging and observability across performance, latency, errors and drift\nBuild and run evaluation pipelines, regression testing and drift detection\nLifecycle & Reliability\nManage model and agent lifecycle (versioning, rollout/rollback, retraining, decommissioning)\nOwn production reliability, incident response and on-call\nAgent Systems\nOperate AI agent systems, including MCP-based integrations, ensuring observability, evaluation and reliability\nCross-team enablement\nEnable multiple teams to adopt standardised deployment, monitoring and lifecycle patterns across ML and AI systems\nExperience & qualifications\nBachelor’s degree in Computer Science, Engineering or related field (Master’s preferred).\n~5+ years in MLOps, ML engineering or cloud engineering. Strong experience with Python, Terraform, Docker and Kubernetes, and deep\nfamiliarity with GCP and its ML ecosystem.\nDyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. 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