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Machine Learning Engineer
London, UK
About the role
Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities. This role owns the context and memory capabilities within AIS, including their correctness, performance, and evaluation.
We are looking for a Machine Learning Engineer who can own hard technical problems end to end — from research and prototyping through to production deployment — working across knowledge bases, vector stores, RAG pipelines, and context engines to power agents that deliver real impact for enterprise customers.
What you'll do
- Own large areas of the platform end to end, from design through to production deployment.
- Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data.
- Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking.
- Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services.
- Develop context retrieval systems that balance recall, precision, latency, and cost.
- Build evaluation frameworks, datasets, and metrics to measure retrieval quality, context relevance, and end to end agent performance.
- Build reliable backend services and data pipelines that support ML and LLM components in production.
- Deliver experiments and new capabilities quickly, maintaining high quality and tight feedback loops with customers.
- Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.
What we look for
- 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
- Strong engineering fundamentals, supported by a Master’s or PhD degree in Computer Science, Machine Learning, AI, or equivalent practical experience..
- A deep, hands-on understanding of retrieval systems, RAG, embeddings, vector indexing, knowledge representation, and semantic search.
- Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
- The ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
- Strong communication skills and comfort working in customer-facing or cross-functional environments.
- Experience scaling products at hyper growth startups
PLEASE NOTE: 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.
About Us:
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, Ernst & Young, 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 [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Skills Required
- 5+ years building and deploying machine learning or AI systems for production use
- Proven proficiency in Python, writing production-quality, testable, maintainable code
- Deep, hands-on understanding of retrieval systems, RAG, embeddings, and vector indexing
- Experience with knowledge representation, semantic search, knowledge graphs, or ontologies
- Experience building integrations between ML components and enterprise data sources, vector DBs, APIs, and services
- Experience designing evaluation frameworks, datasets, and metrics for retrieval and agent performance
- Master's or PhD in Computer Science, Machine Learning, AI, or equivalent practical experience
- Experience scaling or shipping products at high-growth startups
- Strong communication skills and comfort working in customer-facing or cross-functional environments
- Ability to operate in ambiguous problem spaces and balance research with pragmatic product constraints
Scale AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Scale AI and has not been reviewed or approved by Scale AI.
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Healthcare Strength — Company materials and third‑party pages describe comprehensive medical, dental, and vision coverage along with mental‑health services and an EAP. Health insurance is portrayed as strong, with options like HSA/FSA and indications of high premium coverage.
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Leave & Time Off Breadth — Descriptions highlight generous PTO, paid holidays and sick time, bereavement, volunteer time, and role‑dependent flexibility or remote options. This breadth is positioned as part of a supportive time‑off approach, with specifics varying by location.
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Equity Value & Accessibility — Full‑time offers commonly include equity and an ESPP, which can meaningfully lift total compensation, especially in engineering and senior roles. Job postings and compensation snapshots consistently reference base‑plus‑equity packages aligned with competitive AI market pay.
Scale AI Insights
What We Do
Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.
