McKinsey & Company Hiring for Ml Ops Engineer at Gurgaon, Haryana, India Full Time

Job Description

Who You’ll Work With

You will join the Gurgaon office and will be part of a Technical Delivery/MLOps team in QuantumBlack. You will work with software engineers, data scientists, data engineers, designers and Integrative Consultants on projects which address the topmost strategic priorities of our clients.
We Create Real-World Impact – No project is ever the same; we work across multiple sectors, providing unique learning and development opportunities internationally.
Fusing Tech & Leadership – We work with the latest technologies and methodologies and offer first class learning programs at all levels. Multidisciplinary Teamwork – Our teams include data scientists, engineers, project managers, UX and visual designers who work collaboratively to enhance performance.
Innovative Work Culture – Creativity, insight and passion come from being balanced. We cultivate a modern work environment through an emphasis on wellness, insightful talks, and training sessions.
Striving for Diversity – With colleagues from over 40 nationalities, we recognize the benefits of working with people from all walks of life.

What You’ll Do

As a MLOps Engineer in QuantumBlack you will:
Develop and deploy technology that enables data scientists and data engineers to build, productionize and deploy machine learning models following best practice. Work to set the standards for SWE and DevOps practices within multi-disciplinary delivery teams.
Choose and use the right cloud services, DevOps tooling and ML tooling for the team to be able to produce high-quality code that allows your team to release to production.
Build modern, scalable, and secure CI/CD pipelines to automate development and deployment workflows used by data scientists (ML pipelines) and data engineers (Data pipelines).
Shape and support next generation technology that enables scaling ML products and platforms. Bring expertise in cloud to enable ML use case development, including MLOps.
Our Tech Stack-
We leverage AWS, Google Cloud, Azure, Databricks, Docker, Kubernetes, Argo, Airflow, Kedro, Python, Terraform, GitHub actions, MLFlow, Node.JS, React, Typescript amongst others in our projects.

Qualifications

• Bachelor’s degree; computer science, IT, MIS or engineering preferred
• 2+ years industry experience
• 2+ years of experience contributing to the buidling and design (architecture, design patterns, reliability, and scaling) of production-grade Cloud and DevOps applications, preferably solving for multiple teams and analytics use cases
• 1+ years of on-the-job experience working with data teams and automating ML and other data-intensive applications development workflows
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration (Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow, Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries (e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g., deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking, model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least one common RDBMS (MySQL, Postgres, SQL Server, Oracle)