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

Apply Now

Machine Learning Research Engineer

Unitary
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Machine Learning Research Engineer

Machine Learning Research Engineer

Machine Learning Research Engineer

Machine Learning Research Engineer (Foundational Research)

Machine Learning Research Engineer - Speech/Audio/Gen-AI - 6 Month Fixed Term Contract

Machine Learning Research Engineer - Speech/Audio/Gen-AI - 6 Month Fixed Term Contract

Machine Learning Research Engineer


About Us

We’re Unitary, a fast-growing AI startup building Virtual Agents that combine deterministic code, LLM reasoning, and human expertise to automate complex operational workflows. Our technology powers trust & safety systems at scale, analysing millions of images and videos daily for enterprise customers.


Backed by Creandum and Plural, with over $25M raised, we’re scaling rapidly and shaping a future where AI can make safe, fair, and reliable decisions online.


The Role

We’re looking for a Machine Learning Research Engineer to pioneer how Virtual Agents are built, deployed, and scaled. You’ll design an “Agent Factory” — a system that can automatically generate agents from captured workflows, combining the speed of code with the reasoning power of AI.


Working closely with platform and ML teams, you’ll research, prototype, and productionise capabilities that let AI autonomously build reliable software workflows.


What You’ll Do

  • Design and build the Agent Factory to generate and deploy Virtual Agents
  • Develop code-generation and evaluation frameworks for workflow automation
  • Integrate LLM-based reasoning with deterministic Python systems
  • Benchmark and iterate on automation quality through experimentation
  • Collaborate with engineers and customer teams to deploy at scale
  • Contribute to Unitary’s ML research community and technical direction


About You

  • Expert in Python and experienced with LLMs, Agentic AI, or code-generation systems
  • Strong engineering fundamentals (software design, testing, DevOps, MLOps)
  • Curious and inventive — comfortable moving between research and implementation
  • Collaborative communicator who thrives in a small, fast-moving team

Bonus: experience with workflow orchestration (e.g., Temporal), browser automation (Playwright), CI/CD, Terraform, or scaling ML systems in production.


Why Unitary

  • Remote-first across Europe/North America
  • Competitive salary + equity
  • Flexible hours and generous parental/sick leave
  • Annual budgets for learning and wellbeing
  • 3 annual team off-sites in London or Europe


Join us to push the frontier of agentic automation — where AI learns to build and operate systems that make the internet safer.

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 Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.