Lead Machine Learning Engineer (MLops)

Job description

**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 a Lead ML Engineer to join our dynamic and innovative Global Data Science team. In this role, you are a critical member of the data science group focused on leading efforts in migrating ML-based solutions from concept to production-level operational excellence. You will lead initiatives building scalable, resilient, and automated solutions in GCP (Google Cloud Platform) to ensure that models deliver on organizational objectives. **Key Accountabilities** - Design, develop, and implement end-to-end MLOps pipelines using GCP, Vertex AI, Kubeflow, and Airflow. - Automate model deployment, monitoring, retraining, logging, and ML pipeline orchestration. - Establish and drive MLOps best practices, including version control, CI/CD, coding standards, and quality assurance. - Optimize ML model performance, deployment processes, cloud infrastructure, and operational efficiency. - Lead production support, troubleshoot issues, perform root cause analysis, and implement preventive solutions. - Partner with Data Science, Engineering, and Business teams to deploy scalable, production-ready ML solutions. - Drive ML architecture standards, reusable design patterns, and platform improvements across the organization. - Research and adopt emerging MLOps technologies and best practices to enhance scalability and reduce cloud costs. - Mentor team members, promote knowledge sharing, and foster a collaborative engineering culture. - Continuously enhance technical expertise through learning and adoption of new technologies. **Minimum Qualifications** **Education:** Minimum Bachelor's degree, Advanced degree in a quantitative field (CS, engineering, statistics, math, data science). **Experience:** Relevant Machine Learning experience of 7+ years in MLOps and overall 12+ years of Industry experience **Technical Skills** - Strong proficiency in Python, SQL/BigQuery, and Vertex AI on GCP. - Experience building and deploying production-scale ML models with performance optimization. - Hands-on experience with Airflow, Kubeflow, MLflow, and MLOps orchestration. - Knowledge of CI/CD, TDD, Jenkins, and version control tools such as Git. - Experience working in Agile (Scrum/Kanban) development environments. - Strong understanding of supervised ML algorithms, data transformation, and feature engineering. - Passion for learning new technologies and solving complex engineering problems. **Soft Skills:** Strong verbal and written communication skills including the ability to interact effectively with colleagues of varying technical and non-technical abilities. **Preferred Qualifications** - GCP Machine Learning certification, Understanding of CPG industry - Exposure to Deep Learning/RL/LLMs - Publications or contributions to the data science and AI community. - Certifications in AI, machine learning, or related fields. **ELIGIBILITY** Applicants must meet minimum age qualifications in the country in which the job is located.