At a Glance
- Tasks: Lead the development and deployment of cutting-edge ML technology and CI/CD pipelines.
- Company: Join QuantumBlack, a leader in innovative tech solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting projects and career advancement opportunities.
- Why this job: Shape the future of machine learning and collaborate with top talent in the industry.
- Qualifications: 6+ years in tech, strong cloud and DevOps expertise, and leadership experience.
The predicted salary is between 80000 - 100000 £ per year.
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.
MLOps Lead employer: QuantumBlack, AI by McKinsey
At QuantumBlack, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. As an MLOps Lead in our London office, you will have access to cutting-edge technology and a diverse team of experts, providing ample opportunities for professional growth and development. We offer competitive benefits and a supportive environment that encourages creativity and the pursuit of excellence in machine learning and data engineering.
Contact Details:
QuantumBlack, AI by McKinsey Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Lead
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the MLOps space. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. You never know when a casual chat could lead to your next big opportunity!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving CI/CD pipelines or cloud solutions. Having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Don’t be shy about reaching out directly to companies you’re interested in, like QuantumBlack. A quick email or LinkedIn message expressing your enthusiasm for their work can go a long way. Plus, applying through our website gives you a direct line to the hiring team!
✨Tip Number 4
Prepare for those technical interviews! Brush up on your coding skills in Python and get comfortable discussing cloud services and DevOps practices. Practising common interview questions can help you feel more confident and ready to impress.
We think you need these skills to ace MLOps Lead
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the MLOps Lead role. Highlight your experience with cloud services, CI/CD pipelines, and any relevant projects that showcase your skills in machine learning and DevOps practices.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about MLOps and how your background aligns with our needs at QuantumBlack. Don’t forget to mention specific technologies you’ve worked with!
Showcase Your Technical Skills:We want to see your hands-on experience! Be sure to include details about your coding skills in Python, your familiarity with tools like Docker and Kubernetes, and any experience you have with setting up MLOps tooling.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role as quickly as possible!
How to prepare for a job interview at QuantumBlack, AI by McKinsey
✨Know Your Tech Stack
Familiarise yourself with the specific technologies mentioned in the job description, like AWS, Azure, and Kubernetes. Be ready to discuss your hands-on experience with these tools and how you've used them to build scalable CI/CD pipelines.
✨Showcase Your Leadership Skills
As an MLOps Lead, you'll need to demonstrate your ability to manage stakeholders and lead teams. Prepare examples of past experiences where you successfully guided a team through technical challenges or delivered solutions through collaboration.
✨Prepare for Technical Questions
Expect in-depth technical questions related to cloud infrastructure, DevOps practices, and MLOps tooling. Brush up on your coding skills in Python and be ready to explain your approach to automating ML workflows and maintaining production software.
✨Ask Insightful Questions
Engage your interviewers by asking thoughtful questions about their current projects, team dynamics, and future technology initiatives. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
