Machine Learning Engineer

In Technology Group
Birmingham
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Get AI-powered advice on this job and more exclusive features.

This range is provided by In Technology Group. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from In Technology Group

Head of Data, BI, and AI @ In Technology Group.

Job Title: Machine Learning Engineer – Point Cloud & AI Solutions

Location: Birmingham - Remote (occasional travel)

Salary: £50,000 - £90,000 DOE (Very flexible)

About Us

We are a multidisciplinary UK design and modelling team specialising in data-rich models derived from point cloud scans. Our work supports BIM exercises, photogrammetry, digital twin development, high-fidelity visualisation, and scalable portfolio modelling. Our mission is to continuously enhance laser scanning and Scan2BIM workflows using smart, efficient, and AI-driven technologies.

Role Overview

We are seeking a highly skilled Machine Learning Engineer with a strong background in point cloud data processing, 3D spatial modelling, and the development of AI/ML-driven solutions to join our innovation team. This role will focus on automating and enhancing workflows related to Scan2BIM, digital twin creation, and high-resolution visualisation through the integration of machine learning and AI.

Key Responsibilities

  • Develop and deploy ML algorithms for processing and interpreting 3D point cloud data (e.g., segmentation, classification, object detection).
  • Build AI tools to automate BIM modelling tasks, such as feature extraction, geometry reconstruction, and data labeling.
  • Collaborate with designers and modellers to integrate AI solutions into Autodesk Revit, CAD, and game engine pipelines.
  • Design and train deep learning models for real-time analysis of photogrammetry and LiDAR data.
  • Contribute to the continuous improvement of our Scan2BIM workflows through research, prototyping, and tool development.
  • Ensure scalability and robustness of AI/ML pipelines in production environments.
  • Stay current with advances in 3D computer vision, BIM automation, and AI in construction technology.

Required Skills & Experience

  • Proven experience with point cloud data, including formats such as LAS, E57, PLY, and related toolkits (e.g., PCL, Open3D).
  • Strong background in machine learning and deep learning frameworks such as PyTorch, TensorFlow, or Keras.
  • Experience with 3D vision techniques including semantic segmentation, shape detection, and scene reconstruction.
  • Familiarity with BIM software ecosystems (e.g., Autodesk Revit, Navisworks) and CAD interoperability.
  • Programming proficiency in Python, C++, or similar languages used for ML and 3D data handling.
  • Understanding of photogrammetry, LiDAR, and reality capture methods.
  • Knowledge of ISO 19650, PAS 1192 and BIM Level 2 workflows is a plus.

Nice to Have

  • Experience integrating ML models into Unreal Engine or Unity for real-time visualisation.
  • Experience with synthetic data generation for training ML models on 3D datasets.
  • Publications or personal projects in 3D vision or Scan2BIM automation.

What We Offer

  • A chance to work at the forefront of AI and reality capture innovation.
  • Collaborative and creative multidisciplinary team environment.
  • Flexible working options and supportive company culture.

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionDesign, Information Technology, and Analyst
  • IndustriesIT Services and IT Consulting, Data Infrastructure and Analytics, and Technology, Information and Media

Referrals increase your chances of interviewing at In Technology Group by 2x

Sign in to set job alerts for “Machine Learning Engineer” roles.

Birmingham, England, United Kingdom 3 weeks ago

Stafford, England, United Kingdom 2 weeks ago

Birmingham, England, United Kingdom 2 weeks ago

Birmingham, England, United Kingdom 1 week ago

Coventry, England, United Kingdom 2 weeks ago

Senior Software Engineer (Contract) - Data Team

Birmingham, England, United Kingdom 2 weeks ago

Worcestershire, England, United Kingdom 3 months ago

Birmingham, England, United Kingdom 1 day ago

Senior Software Engineer - Search Quality (Remote - United Kingdom)

Birmingham, England, United Kingdom 1 day ago

Software Installation and Support Engineer

Worcestershire, England, United Kingdom 3 months ago

Worcestershire, England, United Kingdom 1 month ago

Software Installation and Support Engineer

Worcestershire, England, United Kingdom 1 month ago

West Midlands, England, United Kingdom 1 week ago

Birmingham, England, United Kingdom 1 week ago

Birmingham, England, United Kingdom 2 days ago

West Midlands, England, United Kingdom 1 week ago

Senior Data Backend Engineer (Semantic Business Information) (Remote - United Kingdom)

Birmingham, England, United Kingdom 1 day ago

Senior Data Backend Engineer - Content and Contributor Intelligence (Remote - United Kingdom)

Birmingham, England, United Kingdom 2 weeks ago

Telford, England, United Kingdom 1 month ago

Warwick, England, United Kingdom 5 days ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#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.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.