Lead Machine Learning Engineer

India is among the top ten priority markets for General Mills, and hosts our Global Shared Services Centre. This is the Global Shared Services arm of General Mills Inc., which supports its operations worldwide. With over 1,300 employees in Mumbai, the center has capabilities in the areas of Supply Chain, Finance, HR, Digital and Technology, Sales Capabilities, Consumer Insights, ITQ (R&D & Quality), and Enterprise Business Services. Learning and capacity-building is a key ingredient of our success.

We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one other and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.​

OVERVIEW

General Mills, Digital and Technology India, is seeking a Lead ML Engineer (Agentic focus) to join our dynamic and innovative Global AI & Automation team. In this role, you are a critical member of the enterprise AI & Agentic group focused on leading efforts in migrating AI-based solutions from concept to production-level operational excellence. The ideal candidate will have expertise in Agentic & AI platforms, AI model / workflow life cycle, Classic & Agentic AI-based workflow / application management including orchestration, deployment, and monitoring, GCP Vertex AI (Gemini Enterprise Agent Platform), and a proven track record of successful AI solution delivery.

ML Engineering capability is leveraged to fuel advanced AI/ML solutions driving decision-making for critical enterprise needs. It is also responsible for implementing and enhancing the community of practice to determine the best practices, standards, and MLOps / AIOps frameworks to efficiently deliver enterprise data solutions at General Mills. This role works in close collaboration with Data Scientists, Data Engineers, Architects and other teams to support the analytic consumption needs. Enhances the performance of the models and automates the production pipelines to gain efficiency

KEY ACCOUNTABILITIES

Establish and Implement AIOps / Agentic AI practices:

• Advanced Agentic Platform Enablement: Lead the technical enablement, integration, and continuous enhancement of advanced agentic AI platforms, ensuring they adhere to stringent performance, scalability, reliability, and security standards. This includes evaluating new agentic-first platforms, tools and frameworks. Expertise in Agentic Deployment capabilities using Google Agent Engine and GKE
• Custom Connector & Integration Development: Architect, design, develop, and implement robust custom connectors and integration solutions to seamlessly connect diverse data sources, enterprise applications, and external services with our agentic platforms.
• API Design, Testing & Integration: Drive the design, development, and rigorous testing of APIs, ensuring secure, reliable, and efficient integration with both internal and external systems to support agentic workflows.
• Agent Orchestration & Workflow Management: Develop, implement, and optimize sophisticated strategies for orchestrating complex agent workflows, managing inter-agent communication, and enhancing decision-making processes within the platform to achieve desired business outcomes.
• Monitoring, Observability & Reliability Engineering: Strong understanding and working knowledge to collaborate with other engineering teams to establish, implement and support comprehensive monitoring and observability capabilities for Agentic workflows across multiple platforms. Working knowledge of Datadog is a plus.
• ML Systems Engineering: Research, operationalize, and standardize ML tooling and processes, including installation, maintenance, documentation, and best practices.
• Generative & Agentic AI Architecture Knowhow: Comprehensive knowledge and working experience (preferred) of setting up an Agentic ecosystem with a cloud platform like Google Cloud Platform (GCP) or Amazon Web Services (AWS).
• Platform Optimization & Lifecycle Management: Conduct ongoing optimization, performance tuning, and lifecycle management of agentic platforms and their underlying capabilities, including bug fixes, security patches, and capacity planning.
• Drive Agile Agentic POCs: Strong working knowledge and experience to develop & lead solution prototypes from ideation, scoping, implementation, and future road mapping with internal and vendor led teams. Drive agile POC execution with focus on hands-on capability validation on new emerging tools and platforms.
• Expert-Level Troubleshooting & Support: Provide advanced technical support and expert-level troubleshooting for complex issues related to agentic platform functionality, integrations, and performance, performing root cause analysis and implementing preventative measures.
• Evaluation and Guardrail: Establish evaluation and guardrail patterns for agentic systems, including quality benchmarking, safety controls, prompt and workflow versioning, and human-in-the-loop review where needed.
• Technical Documentation Excellence: Create and maintain comprehensive, high-quality technical documentation for platform architecture, custom connectors, API specifications, operational procedures to ensure knowledge transfer and system maintainability.
• Governance & Best Practices: Help develop, collaborate, and establish Governance best practices, enterprise standards for Agentic tooling & new agentic solutions
• Security & Compliance: Ensure all platform development and integrations adhere to enterprise security policies, data privacy regulations, and compliance standards.
• Embrace learning mindset: Continually invest in your own knowledge and skillset through formal training, reading, and attending conferences and meetups.

Lead the execution of AI Solutions Scale:

• Partners with business stakeholders to design & deliver the right value-added insights and intelligent solutions through ML and AI.
• Collaborates with Data Science Leads, ML System Engineering and Platform teams to ensure the models are deployed in a scaled and optimized way. Additionally, ensure supporting the post-production phase to ensure model performance degrades are proactively managed.
• Play a lead role in spearheading the development effort of new standards (design patterns, coding practices, orchestration patterns) and drive value and adoption across the Data Science team
• Is considered an expert in Generative AI and Agentic AI space; brings together business knowledge, architecture, resources, people, and technology to create more effective solutions
• Ensure all solutions and integrations adhere to enterprise security policies, data privacy requirements, and compliance standards

Research, Evolve and Publish best practices:

• Research and operationalize technology and processes necessary to scale Agentic AI solutions.
• Recommend model changes to optimize cloud spend, inference efficiency, latency, throughput, and operational effectiveness
• Ability to research and recommend best practices on new technologies, platforms, and services.
• Drive ideation, design, and creation of new AI Architecture patterns in discussion with the Enterprise Architecture team.
• Identify opportunities to improve agentic frameworks, internal accelerators, and reusable components based on implementation learnings and emerging best practices
  

Communication and Collaboration:

• Knowledge sharing with the broader analytics team and stakeholders.
• Communicate on the on goings to embrace the remote and geographical culture.
• Ability to communicate accomplishments, failures, and risks in timely manner.
• Knowledge sharing session with team for specific Agentic AI topics. Coach and Mentor junior ML Engineering members in the team.
• Foster a collaborative and innovative team environment. Contribute to the overall effort to educate stakeholders on AI practices.
• Closely collaborates with the stakeholders on projects and data science leaders to ensure practices are developed and enhanced to support accelerated analytic development and maintainability.

Embrace a learning mindset:

• Continually invest in one’s knowledge and skillset through formal training, reading, and attending conferences and meetups

MINIMUM QUALIFICATIONS

• Education: Minimum Bachelor's degree, Advanced degree in a quantitative field (CS, engineering, statistics, math, data science).
• Experience: Relevant Agentic AI/Machine Learning experience of 6+ years and overall 12+ years of Industry experience.
• Technical Skills:
• Experience in Generative AI / Agentic Solutions, Enterprise scale implementations, and Operations management.
• Passionate about agile software processes, data-driven development, reliability, and systematic experimentation.
• Good understanding of CI, CD, TDD, and tools for Enterprise scale Agentic solution deployment.
• Strong understanding of Agentic protocols like MCP, and A2A.
• Agile software development experience such as Kanban and Scrum.
• Experience in software version control team practices and tools such as GIT and TFS.
• Professional experience with Vertex AI and GCP Services.
• Working knowledge of Observability solutions like Datadog
• Strong proficiency in Python.
• Experience contributing to enterprise standards, governance frameworks, or reusable platform accelerators

• Soft Skills:
• Strong verbal and written communication skills including the ability to interact effectively with colleagues of varying technical and non-technical abilities.
• Passion for learning new technologies and solving challenging problems.

PREFERRED QUALIFICATIONS

• GCP Generative AI Leader certification
• Knowledge of Agentic development frameworks like Google’s Agent Development Kit (ADK), LangChain or other similar ones
• Hands-on Experience with Multi Agent Orchestration tools like UnifyApps, Zapier, n8n, Lyzr etc.
• Understanding of CPG industry
• Exposure to SLMs and LLM fine tuning
• Prior experience with CPG industry.
• Publications or contributions to the data science and AI community.
• Certifications in AI, machine learning, or related fields.

We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one other and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.