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Analytics

Senior Machine Learning Engineer - Scientific AI

Job ID: 95321
  • London
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Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

Your Impact

Your role will be split between developing ML pipelines, scaling AI models, leading architectural discussions, shaping engineering roadmaps and deploying solutions directly with the client delivery teams.
You will leverage your expertise in architecting, orchestrating and scaling complex AI/ML pipelines along with your product development mindset to solve complex problems and create solutions that will accelerate our clients in their respective fields.
We expect you to drive engineering roadmaps for cell-level initiatives and transform AI prototypes into deployment-ready solutions. You will translate engineering concepts for senior stakeholders, enhance McKinsey’s AI Toolbox, and codify methodologies for future deployment.
By working directly with client delivery teams, you will ensure seamless implementation and operationalization of cutting-edge solutions and prototypes. In multi-disciplinary teams, you will ensure smooth integration of AI/ML solutions across projects and mentor junior colleagues.
As a Sr. MLE you’ll be asked to optimize and scale complex AI applications multi machine and multi-GPU setups. You will ensure the latest tools and technologies are used and support your colleagues with codifying and distributing knowledge.

Your Growth

You will be working in our London office in our Life Sciences practice.
You will work with cutting-edge AI teams on research and development topics across our Life Sciences, global energy and materials, and advanced industries practices, serving as a machine learning engineer in a technology development and delivery capacity.
You will be on McKinsey’s global scientific AI team helping to answer industry questions related to how AI can be used for therapeutics, chemicals & materials (including small molecules, proteins, mRNA, polymers, etc.). With your expertise in computer science, computer engineering, cloud, anddistributed computing you will help build and shape McKinsey’s Scientific AI offering.
Your work will involve delivering distinctive capabilities, data, and machine learning systems through collaboration with client teams, playing a pivotal role in creating and disseminating cutting-edge knowledge and proprietary assets, and building the Firm’s reputation in your area of expertise.

Your qualifications and skills

  • Degree in Computer Science, Computer Engineering, or equivalent experience
  • Master’s degree with 5-7 years of relevant experience or PhD with 2-5 years of relevant experience
  • Machine Learning Experience (architecting, deploying, orchestrating, scaling ML/AI solutions)
  • Extensive Kubernetes experience (3y+)
  • Experience in distributed/parallel processing/computing ideally with hands-on experience on Karpenter or Ray
  • Multi-stage deployment orchestration (dev/QA/prod)
  • CI/CD pipelines
  • Cloud Architecture (at least one of AWS, Azure, GCP)
  • GPU Model Deployment
  • ML Model lifecycle management (MLFlow, etc)
  • Security Architecture on Cloud (Authentication & Authorization)
  • Kubernetes Networking (Load Balancing, Proxy, DNS) Terraform















Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.

FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.

Job Skill Group - N/A
Job Skill Code - LCYA - Senior Machine Learning Engineer I
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Tue Feb 25 00:00:00 GMT 2025
LinkedIn Posting City - London
LinkedIn Posting State/Province -
LinkedIn Posting Country - United Kingdom
LinkedIn Job Title - Senior Machine Learning Engineer - Scientific AI
LinkedIn Function - Consulting;Science
LinkedIn Industry - Management Consulting
LinkedIn Seniority Level - Mid-Senior level