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 adhering to best practices. You will be responsible for setting the standards for Software Engineering (SWE) and DevOps practices within multidisciplinary delivery teams.
Responsibilities
- Work with clients to understand their technology stack and subsequently select and utilize appropriate cloud services, DevOps tooling, and ML tooling to enable the team to produce high-quality code and facilitate releases to production.
- Build modern, scalable, and secure CI/CD pipelines to automate development and deployment workflows for both data scientists (ML pipelines) and data engineers (Data pipelines).
- Shape and support next-generation technology that enables the scaling of ML products and platforms, bringing expertise in cloud to facilitate ML use case development, including MLOps.
Qualifications
- Bachelor’s degree or higher required, preferably in Computer Science, IT, MIS, or Engineering.
- 6+ years of 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 in 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 in Python 3 (e.g., API including automated testing frameworks and libraries like pytest), 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 of 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 be part of a Technical Delivery/MLOps team in QuantumBlack. You will collaborate with software engineers, data scientists, data engineers, designers, and Integrative Consultants on projects addressing the topmost strategic priorities of our clients.