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

Apply Now

Senior Machine Learning Engineer

Timely Find
London
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (One Braham (4140), London, United Kingdom)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Join the Team at Groundtruth AI Ltd.

Position: Senior Machine Learning Engineer

About Us
Established in 2024, Groundtruth AI is on the brink of celebrating our first anniversary. We’ve expanded our small team from 2 to 4 members and achieved significant milestones within this short timeframe.

As a proud partner of Google Cloud, we are dedicated to revolutionizing the ways major financial organizations detect and combat financial crimes. Our founders have extensive experience with Google, having played pivotal roles in the development of Google’s latest Cloud initiative focused on Anti-Money Laundering. Our mission is to deploy innovative technologies that contribute to a tangible impact in the fight against financial misconduct, alleviating the human suffering linked to the billions lost and laundered annually.

Who We Seek
We are in search of skilled machine learning engineers to construct and implement efficient data and machine learning systems, web applications, and complete AI solutions tailored for our banking clients' GCP infrastructure. Your responsibilities will include defining and automating workflows with varied datasets while diving deep into understanding the data and the financial domain.

Being a nascent enterprise, you will collaborate closely with our co-founders from the outset. A proven history of accomplishing objectives in environments with uncertain targets is essential. Comfort with pioneering technologies and approaches while taking complete ownership of problems from inception to completion is a must.

We champion robust software delivery and an engineering-focused consultancy approach. While expertise in financial crime isn't mandatory, an eagerness to learn and explore this domain is crucial.

Required Experience
We are open to candidates at various experience levels, but the following are non-negotiable:

  • Deploying software into production environments, centering on data processing or MLOps.
  • Collaborating within a development team utilizing version control systems.
  • Creating data transformations on extensive platforms, whether relational or non-relational.
  • Conducting ad-hoc data analyses and explorations.
  • Troubleshooting data workflows, identifying and addressing complex data and performance issues.
  • Implementing strategic solutions for system and architectural design, ideally within financial services or other intricate regulated fields.

Preferred Qualifications

  • Background in financial crime and transaction monitoring.
  • Experience with managed machine learning API services.

Technical Expertise
We expect to evaluate some of these skills during our interviewing process.

Essential Skills

  • Advanced proficiency in Python within a structured code environment for data pipelines and machine learning applications.
  • Strong skills in data manipulation languages, capable of conducting data analysis and hypothesis testing via Advanced SQL or Python.

Seniority Level:Mid-Senior level

Employment Type:Full-time

Job Function:Engineering and Information Technology

Industries:Human Resources Services

#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.

Jobs

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.

Jobs

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.