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

Apply Now

Machine Learning Engineer

Lightsonic
London
5 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer (LLMs & AI Agents)

Machine Learning Engineering Lead

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

About Lightsonic

Lightsonic is building the future of smart infrastructure monitoring through ML-powered solutions that integrate with urban technology stacks. Our disruptive technology helps preserve and optimize natural resources, reduce carbon emissions, and protect critical infrastructure, starting with our innovative approach to water leak detection.


Following recent investment and strong customer traction, we're in an exciting phase of rapid growth and expansion. As an early-stage company with proven technology, we're uniquely positioned to transform how critical infrastructure is monitored, creating a more sustainable and resilient environment.


Who you are

Required:

  • Someone excited about creating positive environmental impact through technology and motivated by solving real-world problems that matter
  • Team player who thrives in collaborative environments, working effectively with both technical and non-technical stakeholders
  • Adaptable individual who embraces the dynamic nature of a startup, adjusting to evolving objectives and enjoying direct interaction with our customers
  • Engineer with 3+ years’ experience building and deploying supervised machine learning algorithms using time series data
  • Professional with a Bachelor's degree or higher in a STEM field (Computer Science, Engineering, Mathematics, Physics, or related technical discipline)
  • Strong coder with proficiency in Python and SQL who is comfortable working in a cloud environment
  • Individual with experience in MLOps practices (model deployment, monitoring, versioning) and data preprocessing techniques for handling noisy or incomplete data
  • Applicants must have the legal right to work in the UK or Norway, as applicable to the role location.


Desirable:

  • Previous experience working with real-time data / IoT data / distributed fibre optic sensing data
  • Previous acoustic data processing experience
  • Direct experience with elements of our technology stack (Azure Cloud, DBT, Apache Iceberg, Dask, Pytorch, Dagster)
  • Experience solving industrial problems (predictive maintenance, control systems, etc)


What the job involves

  • As one of our first technical hires, you will have complete ownership of all our machine learning processes
  • Successful candidates will need to collaborate closely with our customers to deeply understand the impact and effectiveness of our predictions and continuously improve our product with this information
  • You’ll need to provide thought leadership throughout all phases of the data lifecycle, from data exploration and visualization to reporting, automation and continuous model improvement
  • We work with complex, multi-dimensional datasets and successful candidates will need to continuously innovate and problem solve to extract maximum value from this data
  • Your work will directly impact how water utilities detect and prevent pipeline leaks, creating tangible environmental and societal benefits
  • Successful candidates will directly impact the future of the company and sharing in its success


Salary range

£70,000 - £120,000 base salary

This position will also include equity. This is a best faith estimate of the base salary range for this position. Multiple factors including experience, education, level, and location are considered when determining this.


Company benefits & perks

  • Fast-paced and team-oriented environment where you will be instrumental in the direction of the company
  • Remote first (with travel to customer sites 1-2 days per week)
  • Life assurance and medical insurance
  • 25 days holiday per year
  • Home office setup allowance
  • Eligible for company ESOP scheme


Data privacy

By applying for this role, you consent to the processing of your personal data as outlined in our Recruitment Privacy Notice. We are committed to handling your information securely and in accordance with UK and EU GDPR regulations.

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 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.

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.