Physical AI Data Engineering Consultant - QuantumBlack Labs

McKinsey; Greater London; On-site; GBP 95,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

World-class benefits

Global community

Continuous learning

Mentorship program

Job summary

McKinsey & Company is building foundational data infrastructure powering cutting-edge AI applications. You will design scalable data pipelines, manage secure environments, and prepare data for AI-driven systems, collaborating with cross-functional teams and clients in London or Munich.

Join a team of engineers and ML specialists advancing agentic and autonomous AI capabilities, with opportunities to contribute to R&D and scalable production-ready AI solutions across industries.

Qualifications

• Advanced graduate degree in computational mechanics, materials science, mechanical/aerospace/nuclear engineering or related field.
• 2+ years of relevant professional experience building and deploying data solutions.
• Strong Python and SQL for data engineering and robust production-grade code.
• Experience building end-to-end data pipelines and platforms for Agentic/Generative AI.
• Experience with cloud platforms (AWS/Azure/GCP) and modern data tools.

Responsibilities

• Design and maintain scalable data pipelines and infrastructure for AI/ML systems.
• Prepare data and manage secure data environments for enterprise use.
• Collaborate with cross-functional teams and clients on data-driven solutions.
• Contribute to R&D initiatives focused on innovating and scaling AI capabilities.

Skills

Python

SQL

Data pipelines

MLOps

LangChain

Education

MS/PhD in computational mechanics / related field

Tools

Databricks

Snowflake

BigQuery

Terraform

LangSmith

Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.

YOUR IMPACT

You will build the foundational data infrastructure that powers cutting-edge AI applications leveraging LLMs, retrieval systems, workflows, and emerging agentic architectures. You will design and maintain scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems while collaborating with cross-functional teams and clients. You’ll tackle real-world challenges by contributing to the development of next-generation AI systems and grow as a technologist by working alongside diverse experts across industries. You will design and build the scalable, reproducible data components essential for machine learning, agentic, and autonomous AI systems. You’ll assess data landscapes, apply data quality fundamentals, and prepare data for AI solutions. Additionally, you’ll learn to translate simple hypotheses into engineered features, manage secure data environments, and contribute to R&D initiatives focused on innovating and scaling next-generation AI capabilities. Your work will help solve some of the most complex and high-impact challenges facing clients across industries. Collaborating across McKinsey’s QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you’ll help develop innovative AI capabilities and scalable enterprise solutions. You’ll help build robust data foundations for scalable, production-ready AI systems. Your contributions will directly support the firm’s ability to accelerate AI adoption, solve complex business problems at scale, and enable clients to achieve meaningful, lasting impact. Based in the London or Munich office, you will be part of QuantumBlack Labs and the Robotics and Physical AI team, a group of engineers, scientists, product managers, and machine learning specialists building a first of its kind physics AI capability that accelerates and scales how the world designs and builds physical systems.

YOUR GROWTH

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. When you join us, you will have:

• Continuous learning:Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
• A voice that matters:From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
• Global community:With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
• World-class benefits:On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

YOUR QUALIFICATIONS AND SKILLS

• Advanced graduate degree (M.S. or Ph.D.) in computational mechanics, materials science, mechanical/aerospace/nuclear engineering, computational physics, or a closely related engineering or physical science field required; significant industry or national laboratory experience in applied simulation or scientific machine learning may apply
• 2+ years of relevant professional experience building and deploying data solutions
• Strong proficiency in Python and SQL for data engineering and experience writing robust, production-grade code, including deploying code across environments
• Proven experience building end-to-end data pipelines and platforms for Agentic AI, Generative AI, Machine Learning, or Business Intelligence, covering data preparation, embeddings generation, vector search, and system integration using modern frameworks (Spark, dbt, LangChain)
• A strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.)
• Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform)
• Experience building systems with different data formats (structured vs unstructured) and data processing methods (streaming vs batch) and deploying across major cloud platforms (AWS, Azure, GCP)
• Exceptional time management in a complex and largely autonomous work environment.
• Commercial client-facing or senior stakeholder management experience is beneficial.
• Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus.
• Ability to travel to and work in varying environments that may be challenging and/or not accessible (e.g., manufacturing facilities, etc.)
• Business level language fluency skills, both verbal and written, in English and German (for Munich), with the ability to adjust your style to suit different perspectives and seniority levels

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.