Machine Learning Engineer

Lightsonic
Sheffield
9 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer Python AWS

Machine Learning Engineer

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.