About the Role
As an MLOps Lead in QuantumBlack, you will be instrumental in overseeing the development and deployment of technology that empowers data scientists and data engineers to build, productionize, and deploy machine learning models following best practices. You will be responsible for setting the standards for Software Engineering (SWE) and DevOps practices within multi-disciplinary delivery teams.
What You'll Do
- Oversee the development and deployment of 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.
- Work with clients to understand their technology stack and then 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.
Qualifications
- Bachelor’s degree or higher required, preferably in the field of Computer Science, IT, MIS, or Engineering.
- 6+ years industry experience.
- 4+ years of experience contributing to the building and design (architecture, design patterns, reliability, and scaling) of production-grade Cloud and DevOps applications, preferably solving for multiple teams and analytics use cases.
- 4+ years of on-the-job experience working with data teams and automating ML and other data-intensive applications development workflows.
- 2+ years in a technical lead role.
- Experience managing stakeholders and interacting with technical leaders.
- Expertise in delivering solutions through others and leading teams through problem solving on deep technical issues.
- Excellent hands-on expert knowledge of cloud platform infrastructure and administration (Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security.
- Experience architecting complete cloud based solutions and working with development teams on delivery.
- 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).
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.
Who You'll Work With
You will join the London 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.