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General Mills

Manufactures and distributes packaged foods

D&T Machine Learning Engineer 2

AI Application EngineeringUpdated on Nov 12
Full-timeNo salary listedHybrid

About the Job

Requirements

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a closely related technical field.
  • 5–7 years of progressive experience in software engineering, platform development, or a related technical field, focused on building scalable and resilient systems.
  • At least 1–2 years of hands-on, in-depth experience with Generative AI and Agentic AI technologies, platforms, and frameworks such as LangChain, LlamaIndex, AutoGen, and Glean.
  • A proven track record of designing, developing, and deploying complex integrations and custom connectors for enterprise-level applications.
  • Expert-level proficiency in at least one modern programming language, such as Python, Java, or Go, with an emphasis on clean, efficient, and maintainable code.
  • Deep understanding and extensive experience with API design principles, development, and testing, including RESTful APIs, GraphQL, and gRPC.
  • Expertise in building custom connectors and integrating diverse systems, including enterprise applications such as Salesforce, SAP, and ServiceNow, and various data sources.
  • Good understanding or working experience with agent orchestration frameworks, multi-agent systems, and techniques for managing complex agent interactions and decision flows.
  • Extensive experience with major cloud platforms and their AI/ML services; Google Cloud Platform and Vertex AI are preferred.
  • Proficiency with monitoring, logging, and observability tools such as Prometheus, Grafana, ELK stack, Datadog, or Splunk.
  • Working knowledge of MCP connections, retrieval-augmented generation, vectors, embeddings and indexing, knowledge graphs, and OAuth flows.
  • Strong problem-solving and analytical capabilities, attention to detail, and a proactive approach to resolving complex technical challenges.
  • Ability to communicate technical concepts clearly to technical and non-technical stakeholders and collaborate effectively.
  • Ability to work independently and contribute within cross-functional teams.
  • Passion for learning new technologies and solving challenging problems.
  • Must meet the minimum age qualifications in the country where the job is located.

Responsibilities

  • Lead the technical enablement, integration, and continuous enhancement of advanced agentic AI platforms, ensuring performance, scalability, reliability, and security standards are met.
  • Evaluate new agentic-first platforms, tools, and frameworks.
  • Architect, design, develop, and implement custom connectors and integration solutions connecting diverse data sources, enterprise applications, and external services with agentic platforms.
  • Drive API design, development, and rigorous testing to ensure secure, reliable, and efficient integrations with internal and external systems supporting agentic workflows.
  • Develop, implement, and optimize strategies for orchestrating complex agent workflows, managing inter-agent communication, and improving platform decision-making processes to achieve business outcomes.
  • Collaborate with engineering teams to establish, implement, and support monitoring and observability capabilities for agentic workflows.
  • Optimize and tune platform performance and manage platform lifecycles and underlying capabilities, including bug fixes, security patches, and capacity planning.
  • Provide advanced technical support and troubleshooting for complex platform, integration, and performance issues; perform root cause analysis and implement preventative measures.
  • Create and maintain technical documentation covering platform architecture, custom connectors, API specifications, operational procedures, and best practices.
  • Ensure platform development and integrations comply with enterprise security policies, data privacy regulations, and compliance standards.
  • Continue developing role-related knowledge and skills through training, reading, conferences, and meetups.

Desired Qualifications

  • Background building, maintaining, and supporting traditional machine-learning pipelines in a Google Cloud Platform environment.
  • Understanding of the Consumer-Packaged Goods industry.
  • Familiarity with AI/ML lifecycle stages and MLOps concepts.
  • Practical experience with MLOps principles and practices, including CI/CD for AI/ML workflows, model versioning, and deployment strategies.
  • Experience with Docker, Kubernetes, and orchestration platforms.
  • Familiarity with Infrastructure as Code tools such as Terraform or CloudFormation.
  • Ability to collaborate with cross-functional teams and provide technical mentorship to stakeholders.
  • Potential to mentor junior engineers and drive best practices.

About the Company

General Mills

Manufactures and distributes packaged foods

General Mills is a global food company that manufactures and sells a wide range of packaged foods. Its products include cereals (like Cheerios), baking and ready-to-eat mixes (Betty Crocker, Pillsbury), ice cream (Haagen-Dazs), and pet foods (Blue Buffalo). The company distributes these products through grocery stores and online retailers and supports its brands with targeted advertising. Its food lines reach households, families, and pet owners alike. General Mills differentiates itself through a broad, well-known portfolio, a commitment to quality and sustainability, responsible sourcing, and community involvement, which helps build customer trust. Its goal is to provide tasty, nutritious foods while making a positive impact on people, communities, and the environment.

Company size
Not listed
Company stage
IPO
Headquarters
Minneapolis, MN
Founded
1928

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