{"id":2913752,"url":"https://alion.io/job/eli-lilly-and-company-advisor-ml-engineering-operations","title":"Advisor - ML Engineering & Operations","company":{"id":1753780,"name":"Eli Lilly and Company","domain":"lilly.com","url":"https://alion.io/company/lilly-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":75,"open_postings":60,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":27,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","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":34000,"max_usd":79000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":13,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kedro","optional":false},{"name":"Keras","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"MLFlow","optional":false},{"name":"Pinecone","optional":false},{"name":"Prefect","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Scrum","optional":false},{"name":"Semantic Search","optional":false},{"name":"TensorFlow","optional":false},{"name":"LangChain","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-13T00:00:00Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-27T13:29:59Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work-but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.\nAbout Lilly\nAt Lilly, everything we do starts with patients. We unite caring with discovery to make life better for people around the world. Headquartered in Indianapolis, Indiana, our global team of over 50,000 employees work with urgency and purpose to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. We bring our best to this work because people depend on it. If you're driven by purpose and determined to make a meaningful difference for patients, we invite you to bring your skill and your commitment to Lilly.\nAbout Commercial at Lilly, Bengaluru\nThe medicines Lilly develops only reach patients if the commercial engine behind them works with precision. At Lilly in Bengaluru, the commercial function builds and powers that engine, designing the capabilities, generating the intelligence, and developing the strategies that Lilly's customer-facing teams around the world depend on to connect medicines to the people who need them. The work here is not local in scope. It shapes how Lilly operates commercially across geographies, business units, and markets globally.\nThe Lilly Bengaluru Business Insights & Analytics team was started in 2017 with the objective of using innovative data mining and analytics to support business decisions to Marketing functions in the US and ex-US affiliates (focused on in-line and pre-launch brands). This team has rapidly grown and currently comprises of more than 100 staff members, with varied backgrounds and skills across data management, data sciences, analytical techniques, pharmaceutical commercial operations, and business insights. The team provides analytics outcomes for driving decision making across Lilly's Marketing, Sales, Medical Affairs, and a range of other functions.\nTo support the marketing teams in their decision-making, a data and analytics team has been set up simultaneously in Indianapolis (HQ) and Bengaluru (Lilly Bengaluru). This team is responsible for setting up the data warehouses necessary to handle large volumes of digital streaming data, create meaningful analyses using that data, and deliver recommendations to leadership.\nAs part of the Lilly Bengaluru team, we have an exciting opportunity for a Senior ML/AI Engineer who will own complex ML architecture and pipeline decisions across key initiatives while also leading technical integration with Lilly's Agentic AI engineering team as our programs adopt agentic AI capabilities. This is a hands-on, individual contributor role that calls for genuine depth on both sides: production-grade ML engineering and agentic AI development.\nCore Responsibilities:\nOwn end-to-end ML architecture, feature engineering, and pipeline design decisions for key commercial analytics initiatives\nDesign and review ML architectural decisions with stakeholders, setting patterns that other engineers build on\nOwn CI/CD pipeline orchestration, deployment (Docker/Kubernetes/Prefect), and production monitoring across multiple projects\nApply software engineering rigor and best practices to ML systems, including CI/CD, automation, and testing\nOptimize model hyperparameters and evaluate model performance, robustness, and explainability across production ML systems\nDesign and build production agentic AI systems using frameworks such as LangGraph - multi-step reasoning, tool use, and orchestration across complex workflows\nOwn the LLMOps practice for initiatives you lead: prompt versioning, evaluation pipelines, cost/latency monitoring, and guardrails for production LLM applications (Claude or similar)\nArchitect retrieval-augmented generation systems and integrate vector databases (e.g., Pinecone) for semantic search and retrieval at production scale\nServe as the primary technical point of contact with Lilly's Agentic AI engineering team, defining technical contracts, APIs, and shared SLAs as programs adopt agentic capabilities\nSet and document human-in-the-loop boundaries in partnership with Data Science and business stakeholders\nProvide informal technical oversight for 2-3 more junior engineers - reviewing designs and code, and unblocking hard technical problems, without formal people-management responsibility\nCoordinate with diverse stakeholders such as Data Scientists, software engineers, and infrastructure teams to design the most optimal ML and agentic pipelines\nRequired\n13+ years of demonstrated expertise building ML/AI systems in production - including model versioning, data/model lineage, monitoring, deployment, optimization, scalability, and automated pipelines - with substantial recent depth in generative AI and agentic system development, not just brief exposure\nKnowledge of architectural design and implementation of end-to-end ML and agentic AI solutions\nStrong knowledge of core ML frameworks (scikit-learn, PyTorch, TensorFlow, Keras, or equivalent) and the ability to understand and extend the modeling work of Data Scientists into production-grade systems\nStrong knowledge of Python and PySpark for large-scale data processing; working knowledge of R is preferred (for Framebar pipeline hand-off from Data Science)\nProficient in AWS components such as SageMaker, Lambda, and other AWS/serverless services (this role consumes cloud infrastructure rather than provisioning it directly)\nStrong knowledge of Docker, Kubernetes, and CI/CD tooling (GitHub Actions)\nExtensive hands-on experience with LangGraph or a comparable agentic framework, at a level where you'd be setting patterns for others, not learning them\nExperience with MLOps frameworks such as MLflow, Kedro, and Prefect\nProduction experience with LLM application development - prompt engineering, RAG architecture, and LLMOps practices (evaluation, cost/latency monitoring, guardrails)\nExperience with Pinecone or a similar vector database for semantic search/retrieval at production scale\nExperience defining technical contracts, APIs, or integration boundaries with another engineering team, not just consuming someone else's platform\nExperience developing in a Scrum/Agile environment\nExcellent verbal and written communication skills, with the ability to advocate technical solutions to Data Scientists, engineering teams, and business audiences\nEducation:\nMaster's or PhD in Computer Science, Computer Applications, or a related technical field, or equivalent specialization/certifications in ML/AI Engineering, with a deep understanding of SDLC\nAt Lilly, caring is not only what we do for patients. It is how we work. We believe the people who dedicate themselves to making medicines better deserve an environment that makes their lives better too, one where they are supported, respected, and given the space to do their best work. This is not just a policy. It is who we are.\nLilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.\nLilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.\n#WeAreLilly","description_format":"text","description_chars":8188,"description_truncated":false,"requirements":{"experience_years_min":13,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Prescription Drugs","Oncology Therapeutics","Cardiometabolic Therapeutics"],"lifecycle":[{"event":"open","at":"2026-10-20T10:18:42Z"}],"visa":[],"liveness":{"score":50,"band":"ok","label":"Likely open","p_open":0.9,"p_active":0.611,"p_room":0.9,"age_days":14,"expected_fill_days":27,"reasons":["conf:68","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-10-27T05:46:45Z"},"pay":null,"html_url":"https://alion.io/job/eli-lilly-and-company-advisor-ml-engineering-operations","json_url":"https://alion.io/job/eli-lilly-and-company-advisor-ml-engineering-operations.json","meta":{"generated_at":"2026-10-27T17:56:09Z","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":7764,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-28T00:00:00Z"}},"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":1753780},"rest":"https://alion.io/mcp/rest/get_company?id=1753780"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Feli-lilly-and-company-advisor-ml-engineering-operations"},{"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%2Feli-lilly-and-company-advisor-ml-engineering-operations"},{"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%2Feli-lilly-and-company-advisor-ml-engineering-operations"},{"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/eli-lilly-and-company-advisor-ml-engineering-operations\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Feli-lilly-and-company-advisor-ml-engineering-operations"}]}