National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Lead Machine Learning Engineer (Agentic Infrastructure)

ZipRecruiter
London
2 days ago
Create job alert

Job Description
Over the past 8 years, Codesearch AI have had the pleasure to work with some of the most ground-breaking and successful starts ups around. We can safely say this company is as exciting as it gets.
We are an exclusive partner to a YC-backed start-up that's building truly transformative AI technology. Their agentic AI platform goes well beyond chat interfaces, offering ground-breaking memory capabilities that solve real enterprise problems with unprecedented accuracy. As validation of their innovative approach, one of the world's most widely used AI tools is already exploring adoption of their technology.
With a founding team of accomplished researchers and engineers from organizations like LinkedIn and FAIR, they're now expanding their core team to bring this revolutionary product to market.
The Role
They're seeking their first dedicated ML Engineer to help productise their Agentic AI platform. This role is perfect for someone who loves to move fast, ship usable systems, and operate at the intersection of LLMs, infrastructure, and software engineering.
What You'll Be Doing
Take working prototypes of LLM-based agents and productize them into scalable, robust systems
Build infrastructure and pipelines to support and integrate AI Agents in real-world enterprise environments
Collaborate with the founding team to integrate models into internal and external user flows
Write clean, production-ready code - often improving or refactoring existing prototypes
Think holistically about agent lifecycle , observability, failure handling, and scalability
Help define the tech stack and architecture for core components of the platform
Contribute to novel research and publish at top conferences when opportunities arise
What You'll Have
MSc or PhD in Machine Learning, Computer Science or a related field
5+ years of experience in ML engineering, MLOps and/or backend/infra-focused roles
Experience integrating LLMs into enterprise SaaS or internal tooling
Strong Python experience with ML/LLM libraries (e.g., Transformers, LangChain, LangGraph, OpenAI APIs)
Experience with cloud platforms (AWS, GCP, or Azure), deployment, and CI/CD pipelines
Familiarity with containerization (Docker, Kubernetes) and observability (e.g., Prometheus, Grafana)
A builder mindset: you're comfortable with ambiguous specs, early-stage infrastructure, and iterating fast
Excellent communication and self-management skills
Nice To Have
Familiarity with agentic frameworks, orchestration tools, or vector databases
Background in DevOps/MLOps or platform engineering
Passion for building something from scratch and seeing the impact of your work in production
What We Offer
Competitive salary with equity options based on experience and profile
Flexible work arrangements with remote/hybrid options
Comprehensive health benefits and wellness programs
Professional development budget for conferences and continued learning
A front-row seat to the agentic AI evolution
Full ownership and trust over your code and system decisions
A lean, expert team with direct access to product, users, and strategic investors
Opportunity to shape the future of AI in a fast-growing market segment

#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Machine Learning Engineer – LLMs - Ramboll Tech

Lead Machine Learning Engineer (Agentic Infrastructure)

Lead Machine Learning Engineer – LLMs - Ramboll Tech...

Lead Machine Learning Engineer

Lead Machine Learning Engineer, Associate Director, London

Lead Machine Learning Engineer

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.