Machine Learning Engineer, Enterprise Research London, UK

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products.

At Scale, our Enterprise team works with a variety of customers looking to be at the forefront of incorporating Generative AI capabilities into their services. Forward Deployed ML Engineers (FDMLEs) work directly with our customers to build and own robust, production-grade services which directly integrate into their products. This exciting role lies at the intersection of customer delivery and ML engineering, providing you with a wealth of experience and stimulating both sides of your brain. In this role, your daily tasks may include engaging in discussions with customers and understanding their generative AI needs and using platform tools and packages to finetune and iterate on modeling experiments using Large Language Models (LLM) or Retrieval Augmented Generation (RAG). Your experiments should be focused around data and metrics that drive continuous improvement. This includes designing data-driven experiments focused on optimizing model performance by deeply understanding the training data and model outputs to systematically move key metrics. If you are excited about shaping the future of the data-centric AI movement, we would love to hear from you!

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• Own, plan, and optimize our Enterprise customer’s Generative AI problems, thereby becoming the ML voice in the room that our customers turn to for solutions
  
• Understand the tools available for optimizing performance around LLMs and how to most appropriately apply or combine them in different scenarios
  
• Be analytically rigorous by asking probing questions of the data and results to root out model weaknesses
  
• Demonstrate strong proficiency for writing, testing, and debugging Python code, capable of solving programming problems such as basic algorithms and data structure manipulations
  
• Have experience gathering business requirements and translating them into technical solutions
  
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
  
• Have strong communication skills and the ability to explain technical concepts to non-technical stakeholders
  
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
  
• Deeply understand the AI strategy, goals, and needs of the customers
  
• Build deep relationships with technical stakeholders at all levels and across all roles, both internally and externally
  
• Be able and willing to multi-task and learn new technologies quickly
  

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• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
  
• 3+ years of engineering experience, post‑graduation in a client‑facing setting
  
• At least 2 years of model training experience, specifically in translating business problems into data/model problems.
  
• Deep familiarity with a data‑driven approach when iterating on machine learning models and how changes in datasets can influence model results
  
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
  
• Experience operating in a fast‑paced environment with ambiguity
  
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas) and create functions to break down problems into modular components focused on robustness, readability and maintainability
  

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• Strong knowledge of software engineering best practices
  
• Have experience with AI platforms and technologies, including generative models and LLMs
  
• Have built applications taking advantage of Generative AI in real, production use cases
  
• Familiarity with state of the art LLMs and their strengths/weaknesses
  

Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's Know Your Rights poster for additional information.

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