Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Machine Learning Engineer – LLMs - Ramboll Tech

Ramboll
London
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer - Search

Senior Machine Learning Engineer – Computer Vision

Machine Learning Quant Engineer - Investment banking

Applied Machine Learning Engineer

Applied Machine Learning Engineer

Applied Machine Learning Engineer

Job Description

At Ramboll Tech, we believe innovation thrives in diverse, supportive environments where everyone can contribute their best ideas. As a Lead Machine Learning Engineer, you will step up and take responsibility to create cutting-edge AI solutions that empower our business while mentoring others and fostering a culture of collaboration and growth.

As the sparring partner for your product owners and your Chapter lead, your job is to shape the technical roadmap and contribute to the implementation of best practices both in the product team (“Pod”) you work in and the global Chapter of ML Engineers. You will work with the global Chapter leads, subject matter experts, and other ML Engineers to deliver impactful AI solutions.

WHAT YOU WILL DO

Technological Leadership:

  • Define architectural patterns for scalable LLM pipelines, ensuring robust versioning, monitoring, and adherence to best practices.
  • Drive the integration of external knowledge bases and retrieval systems to augment LLM capabilities.

Research and Development:

  • Effective RAG architectures and technologies for organizing complex domain-specific data (e.g. vector databases, knowledge graphs) and effective knowledge extraction.
  • Explore and benchmark state-of-the-art LLMs, tuning, adaptation, and training for performance and cost efficiency.
  • Incorporate recent trends like instruction tuning, RLHF, or LoRA fine-tuning for domain customization.
  • Embed domain-specific ontologies, taxonomies, and style guides into NLP workflows to adapt models to unique business contexts.

Evaluation and Optimization:

  • Analyze models for quality, latency, sustainability metrics, and cost, identifying and implementing improvements for better outcomes.
  • Define and own the ML-Ops for your Pod.

Experimentation and Continuous Improvement:

  • Develop experiments for model evaluation and improvement, keeping the solutions aligned with evolving industry standards.

Best Practices:

  • Establish scalable coding standards and best practices for maintainable and production-ready systems.

Team Support:

  • Mentor ML engineers to foster their personal growth.

HOW YOU WILL SUCCEED IN YOUR ROLE

We’re looking for someone who is excited to make an impact and grow with us. While not everyone will have all the qualifications listed, you might be a great fit if you bring some of the following. We’re working with every team member individually to grow according to their needs and abilities.

Education:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Experience:

  • Minimum 5 years of experience implementing machine learning projects.
  • At least 2 years in a senior or lead role.
  • Demonstrated expertise integrating modern LLMs into production systems.

Leadership skills:

  • Proven leadership in driving technical projects to successful completion in agile environments.
  • Strong communication skills to align technical solutions with business goals.
  • Ability to mentor and foster innovation within the team.

Technology Skills:

  • Strong expertise in building Retrieval-Augmented Generation (RAG) architectures and integrating with vector and graph databases.
  • In-depth experience with modern Transformer-based LLMs (e.g., GPT-4, Claude, Gemini, Llama, Falcon, Mistral).
  • Demonstrated ability to fine-tune and optimize LLMs for quality, latency, sustainability, and cost-effective performance.
  • Advanced Python proficiency and expertise with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain.
  • Experience with containerization tools (e.g. Docker, Kubernetes) and workflow management tools (e.g. Azure ML Studio, MLFlow).
  • Hands-on experience with (preferably Azure) Cloud environments for scalable AI deployment, monitoring, and optimization.
  • Experience with relational (SQL), NoSQL databases.
  • Familiarity with platforms like Snowflake or Databricks.

WHAT DEFINES US: CURIOSITY, OPTIMISM, AMBITION, EMPATHY

Our team at Ramboll Tech is currently on a steep growth trajectory while maintaining a strong team culture.

We are curious about other people and their motivations; about new business models and technologies; about each other and the future.

We are optimistic, focusing on solutions rather than problems; we plan for success and are willing to take calculated risks instead of playing it safe.

We are ambitious, setting our own standards higher than others’ expectations, and we celebrate each others successes.

We are empathetic, taking ourselves, others, and each other seriously without prejudgment, and we help each other and our clients, colleagues, and the world.

HOW WE WORK AS A TEAM

Our team culture is crucial to us; thats why we take time daily to exchange ideas and discuss our work priorities. We support each other when facing challenges and foster a strong team spirit. We aim to learn and grow continuously from one another. We value diversity, and although were not perfect, we regularly engage in open discussions about how we can improve in this area.

Our current hybrid work approach focuses on adapting to different needs, including increased flexibility that works best for teams and individuals, with as much autonomy as possible. We also meet up in person regularly, such as twice a year at our offsite or during team dinners.

WHO IS RAMBOLL

Ramboll is a global architecture, engineering, and consultancy firm. We believe sustainable changes aim is to create a livable world where people thrive in healthy nature. Our strength is our employees, and our history is rooted in a clear vision of how a responsible company should act. Openness and curiosity are cornerstones of our corporate culture, fostering an inclusive mindset that seeks new, diverse, and innovative perspectives. We respect and welcome all forms of diversity and focus on creating an inclusive environment where everyone can thrive and reach their full potential.

AND WHAT DOES RAMBOLL TECH DO

Ramboll Tech accelerates innovation and digital transformation for the entire Ramboll group and directs all AI-related initiatives within the company. This includes collaborating with markets at Ramboll on their AI projects, as well as working on larger change processes within the corporation and developing proprietary AI products for Ramboll and our clients. Our team currently has over 300 employees from Denmark, Germany, the USA, and India. We are looking to quickly expand in key areas across Europe and the globe.

EQUALITY, DIVERSITY AND INCLUSION

Equality, diversity, and inclusion are at the heart of what we do. At Ramboll, we believe that diversity is a strength and that different experiences and perspectives are essential to creating truly sustainable societies. We are committed to providing an inclusive and supportive work environment where everyone is able to flourish and reach their potential. We also know how important it is to achieve the right balance of where, when, and how much you work. At Ramboll, we offer flexibility as part of our positive and inclusive approach to work. We invite applications from candidates of all backgrounds and characteristics. Please let us know if there are any changes, we could make to the application process to make it more comfortable for you. You can contact us at with such requests.

IMPORTANT INFORMATION

We do require a cover letter together with your current CV (preferably without a photo) through our application tool, and were eager to get to know you better in a conversation.

Do you have any questions? Feel free to contact the hiring team through our recruitment tool.

J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.