Senior Machine Learning Engineer - Remote

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.​ General Mills is seeking a Senior Machine Learning Engineer to help design, build, deploy, and support scalable AI and machine learning solutions that deliver real business value. In this role, you will help move machine learning solutions from concept to production while improving reliability, automation, observability, and operational excellence across the AI lifecycle. This role sits within a broader shared team model, where talent is matched to the highest-priority work across a growing portfolio of AI initiatives. That means this position is intentionally broad: you may work on traditional machine learning solutions, foundational platform and backend capabilities, or newer agentic and generative AI use cases depending on team needs and your strengths. We are looking for a strong technical engineer first and foremost—someone with solid software engineering discipline, strong Python skills, and the flexibility to work across evolving AI problem spaces. What You'll Do Design, develop, deploy, and maintain machine learning and AI systems in GCP to solve complex business problems, improve operations, and create new value. Translate machine learning concepts into practical, scalable production solutions with a strong focus on reliability, supportability, and quality. Partner across teams to understand problem definitions, data needs, and solution approaches for a wide range of business and technical use cases. Prepare data, engineer features, develop and evaluate models, and help operationalize solutions in production environments. Build and automate ML pipelines, including orchestration, monitoring, logging, diagnostics, and alerting for failures, drift, degradation, and upstream data issues. Support model deployment, MLOps practices, cloud resource management, and change control processes. Research, evaluate, and operationalize new tools, frameworks, platforms, and processes that help scale AI solutions, including emerging agentic and generative AI capabilities. Take ownership of production issues, perform root cause analysis, and drive improvements to reduce repeat incidents. Create and improve documentation, standards, and quality assurance processes for machine learning systems and pipelines. Help create, maintain, and support production and lower environments, including development, QA, and staging. Contribute to cloud security and compliance practices. Mentor others and help raise the team’s engineering and machine learning best practices. Minimum Qualifications Bachelor’s degree in computer science, engineering, statistics, mathematics, data science, or another quantitative field. 3+ years of professional experience as a software engineer, integration engineer, ML engineer, AI engineer, or data scientist. 3+ years of professional experience working with a major cloud platform such as GCP, Azure, Snowflake, or Databricks. Strong Python development skills. Experience building, deploying, or supporting production-grade machine learning or AI solutions. Familiarity with CI/CD, TDD, and related engineering tools and practices. Experience with orchestration frameworks such as Prefect or Airflow. Experience working in agile software development environments such as Kanban or Scrum. Experience with version control and team-based development practices using tools such as Git or TFS. Strong verbal and written communication skills, with the ability to work effectively with both technical and non-technical partners. Passion for learning new technologies, solving challenging problems, and operating with a data-driven engineering mindset. Preferred Qualifications 5+ years of professional experience as a software engineer, integration engineer, ML engineer, AI engineer, or data scientist. Strong software engineering background, ideally including several years of hands-on engineering experience before or alongside machine learning work. Experience in a GCP environment, including Vertex AI. Experience building and supporting APIs and endpoints, ideally in GCP. Experience building, maintaining, and supporting traditional machine learning pipelines in a cloud environment. Background in statistical modeling techniques such as regression, ARIMA, Random Forest, optimization, or forecasting. Exposure to agentic AI platforms, generative AI solutions, or related modern AI tooling. Track record of producing machine learning models and production infrastructure at scale. Ability to mentor others and lead through engineering and ML best practices. Experience working across a variety of use cases or business domains, with the flexibility to match skills to evolving priorities. Additional Considerations We are open to remote employees within the United States. International relocation or international remote working arrangements (outside of the US) will not be considered. Applicants for this position must be currently authorized to work in the United States on a full-time basis. General Mills will not sponsor applicants for this position for work visas. ELIGIBILITY Applicants must meet a minimum 18-year age qualification. EQUAL OPPORTUNITY EMPLOYER (EOE) ​ General Mills is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, marital or familial status, status regarding public assistance, or membership or activity in a local human rights commission. REASONABLE ACCOMODATION REQUEST If you need to request an accommodation during the application or hiring process, please fill out our online accommodation request form by following this link: Accommodation Request .