Sr. D&T Machine Learning Engineer

General Mills · Powai

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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 Sr Machine Learning Engineer to join the Enterprise Data Capabilities Organization. This team builds enterprise level scalable and sustainable data and model pipelines to serve the analytic needs of business impacting problem statements. In this role, you are a critical member of the data science team focused to operationalize the ML and AI models, entails model management and monitoring too. The success is to recommend innovative ways to automate the MLOps pipelines on GCP and set standards that would ensure repeated success.

KEY ACCOUNTABILITIES

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MINIMUM QUALIFICATIONS

Education: Minimum qualification is Bachelor's degree (full time)

Experience: Minimum 6+ yrs of professional experience in MLOps E2E framework and 10+ years of total experience

Technical Skills: Expertise in Data Transformation and Manipulation through Big-Query/SQL, Professional experience with Vertex AI and GCP Services, Expertise in one of the programming Language Python/R, Should have experience in Airflow/Cloud composer, Kubernetes/Kubeflow, MLflow, TFX,Docker -container

Soft Skills: Strong communication skills both verbal and written including the ability to interact effectively with colleagues of varying technical and non-technical. Passionate about agile software processes, data-driven development, reliability, and systematic

PREFERRED QUALIFICATIONS




ELIGIBILITY

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

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