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D&T Machine Learning Engineer II

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and build custom connectors linking data sources and enterprise apps to agentic platforms

  • Design, develop and test APIs for secure integration with internal and external systems

  • Develop and optimize orchestration of complex agent workflows and inter-agent communication

  • Tune, patch and maintain agentic platforms, including capacity planning

  • Troubleshoot platform issues and perform root cause analysis

From the employer’s posting
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.
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.
Develop, implement, and optimize sophisticated strategies for orchestrating complex agent workflows, managing inter-agent communication
Conduct ongoing optimization, performance tuning, and lifecycle management of agentic platforms and their underlying capabilities, including bug fixes, security patches, and capacity planning.
Provide advanced technical support and expert-level troubleshooting for complex issues related to agentic platform functionality, integrations, and performance, performing root cause analysis

What you’ll bring

All qualifications

Core experience

  • Deep understanding and extensive experience with API design principles, development, and rigorous testing (RESTful APIs, GraphQL, gRPC).
  • Ability to thrive in a fast-paced, dynamic environment, working both independently and as a key contributor within cross-functional teams.
  • Demonstrated expertise in building custom connectors and integrating diverse systems, including enterprise applications (e.g., Salesforce, SAP, ServiceNow) and various data sources.
  • Good understanding/Working experience of agent orchestration frameworks, multi-agent systems, and techniques for managing complex agent interactions and decision flows.
  • Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance.

Preferred experience

  • Understanding of the Consumer-Packaged Goods (CPG) industry.
  • Familiarity with AI/ML lifecycle stages and MLOps concepts.
  • Strong understanding and practical experience with MLOps principles and practices, including CI/CD for AI/ML workflows, model versioning, and deployment strategies.
  • Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms.
Qualification wording
Deep understanding and extensive experience with API design principles, development, and rigorous testing (RESTful APIs, GraphQL, gRPC).
Ability to thrive in a fast-paced, dynamic environment, working both independently and as a key contributor within cross-functional teams.
Demonstrated expertise in building custom connectors and integrating diverse systems, including enterprise applications (e.g., Salesforce, SAP, ServiceNow) and various data sources.
Good understanding/Working experience of agent orchestration frameworks, multi-agent systems, and techniques for managing complex agent interactions and decision flows.
Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance.
Understanding of the Consumer-Packaged Goods (CPG) industry.
Familiarity with AI/ML lifecycle stages and MLOps concepts.
Strong understanding and practical experience with MLOps principles and practices, including CI/CD for AI/ML workflows, model versioning, and deployment strategies.
Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms.
Education & alternatives
Experience & Education: - 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, with a strong focus on building scalable and resilient systems.
Apply at General Mills

Posting record

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Status in our records
Live
First seen by us
Nov 3, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 4, 2026
Reposted
once since Oct 27, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

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Day 1

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From 4,284 similar postings that came down. Coming down is not always a hire.

General Mills is hiring

57 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • 2% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • Datadog
  • Docker
  • GCP
  • Grafana
  • Kubernetes
  • Terraform
  • Go
Where the posting names them
Technical Skills: - Expert-level proficiency in at least one modern programming language (e.g., Python, Java, Go) with a strong emphasis on writing clean, efficient, and maintainable code. - Deep understanding and extensive experience with API design principles, development, and rigorous testing (RESTful APIs, GraphQL, gRPC).
- Extensive experience with major cloud platforms (Google Cloud Platform is preferred) and their AI/ML services (Vertex AI is preferred). - Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance. - Working knowledge of MCP connections, RAG, Vectors, Embeddings and Indexing, Knowledge graph and Oauth Flows.
- Strong understanding and practical experience with MLOps principles and practices, including CI/CD for AI/ML workflows, model versioning, and deployment strategies. - Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms. - Familiarity with Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation) is a plus.
- Good understanding/Working experience of agent orchestration frameworks, multi-agent systems, and techniques for managing complex agent interactions and decision flows. - Extensive experience with major cloud platforms (Google Cloud Platform is preferred) and their AI/ML services (Vertex AI is preferred). - Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance.
PREFERRED QUALIFICATIONS - Background in building, maintaining, and supporting traditional ML pipelines in a GCP environment. - Understanding of the Consumer-Packaged Goods (CPG) industry.
- Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms. - Familiarity with Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation) is a plus. - Ability to collaborate cross functional teams and provide tech mentorship to other stakeholders

Your next step

Complete your application on genmills.wd1.myworkdayjobs.com. The employer’s form will show what is required.

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Has General Mills posted this job before?

Yes. We’ve followed one other D&T Machine Learning Engineer II job there since October 2026. It came down after 7 days.

  1. PowaiCame down after 7 days, first seen Oct 27
  2. This jobUp 1 day so far, first seen Nov 3

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

COMPANY OVERVIEW

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 another 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 an ML Engineer(Agentic) to join the D&T Global Artificial Intelligence and Automation (AIA) Organization as part of the overall AIA Engineering group. This team builds enterprise-level scalable and sustainable AI solution pipelines and Agentic workflows to serve the AI and Agentic needs of business-impacting problem statements, maintains cloud and agentic platforms, and explores new complementary tooling for AI and Intelligent automation requirements.

 

In this role, you are a critical member of the AIA team focused on leading efforts dedicated to enabling, optimizing, and scaling our next-generation agentic AI platforms. The candidate will be instrumental in designing and implementing robust custom connectors, ensuring seamless and secure API integrations, and orchestrating complex agent behaviors to unlock new business capabilities.

 

We are looking for an individual with a strong background in Generative AI and Agentic AI, coupled with a passion for developing, maintaining, and continuously enhancing intelligent systems that deliver significant business value and drive innovation across the enterprise.


KEY ACCOUNTABILITIES

  • 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.
  • 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: Overall understanding to collaborate with other engineering teams to establish, implement and support comprehensive monitoring and observability capabilities for Agentic workflows
  • 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.
  • 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.
  • Technical Documentation & Best Practices: Create and maintain comprehensive, high-quality technical documentation for platform architecture, custom connectors, API specifications, operational procedures, and best practices to ensure knowledge transfer and system maintainability.
  • 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

MINIMUM QUALIFCATIONS

Experience & Education:

  • 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, with a strong focus on building scalable and resilient systems.
  • Minimum of 1-2 years of hands-on, in-depth experience specifically with Generative AI (Gen AI) and Agentic AI technologies, platforms, and frameworks (e.g., LangChain, LlamaIndex, AutoGen, Glean, etc.).
  • Proven track record of designing, developing, and deploying complex integrations and custom connectors for enterprise-level applications.

Technical Skills:

  • Expert-level proficiency in at least one modern programming language (e.g., Python, Java, Go) with a strong emphasis on writing clean, efficient, and maintainable code.
  • Deep understanding and extensive experience with API design principles, development, and rigorous testing (RESTful APIs, GraphQL, gRPC).
  • Demonstrated expertise in building custom connectors and integrating diverse systems, including enterprise applications (e.g., Salesforce, SAP, ServiceNow) and various data sources.
  • Good understanding/Working experience of agent orchestration frameworks, multi-agent systems, and techniques for managing complex agent interactions and decision flows.
  • Extensive experience with major cloud platforms (Google Cloud Platform is preferred) and their AI/ML services (Vertex AI is preferred).
  • Proficiency in establishing and utilizing monitoring, logging, and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog, Splunk) to ensure platform health and performance.
  • Working knowledge of MCP connections, RAG, Vectors, Embeddings and Indexing, Knowledge graph and Oauth Flows.

Soft Skills:

  • Exceptional problem-solving and analytical capabilities, with a keen eye for detail and a proactive approach to identifying and resolving complex technical challenges.
  • Superior communication and collaboration skills, with the ability to articulate technical concepts clearly to both technical and non-technical stakeholders.
  • Ability to thrive in a fast-paced, dynamic environment, working both independently and as a key contributor within cross-functional teams.
  • Passion for learning new technologies and solving challenging problems.

PREFERRED QUALIFICATIONS

  • Background in building, maintaining, and supporting traditional ML pipelines in a GCP environment.
  • Understanding of the Consumer-Packaged Goods (CPG) industry.
  • Familiarity with AI/ML lifecycle stages and MLOps concepts.
  • Strong understanding and practical experience with MLOps principles and practices, including CI/CD for AI/ML workflows, model versioning, and deployment strategies.
  • Experience with containerization technologies (Docker, Kubernetes) and orchestration platforms.
  • Familiarity with Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation) is a plus.
  • Ability to collaborate cross functional teams and provide tech mentorship to other stakeholders
  • Strong leadership potential with the ability to mentor junior engineers and drive best practices



ELIGIBILITY

Applicants must meet minimum age qualifications in the country in which the job is located.

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Powai, Mumbai, MH

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