Machine Learning Engineer Jobs in London 2026: By creating the intelligent technology layer for contemporary manufacturing facilities, FORGIS is assisting factories in becoming more interconnected, flexible, and productive. In order to develop digital engineering solutions that can comprehend production environments and facilitate better decision-making, the company integrates industrial automation, machine learning, real-time data, and intelligent software.
An experienced ML specialist has an intriguing opportunity to work on issues where artificial intelligence and practical manufacturing collide in the Machine Learning Engineer position. Instead of creating models that stay in research settings, you will use production data from industrial equipment to assist in the development, testing, deployment, and improvement of machine learning systems.
For someone who appreciates addressing challenging technical challenges and wants to see their work have a quantifiable impact in actual operational contexts, this is a great opportunity. You will assist in the development of intelligent solutions for production optimization, anomaly detection, and predictive maintenance while working with data from PLCs, robots, sensors, and various industrial systems.
Details of Machine Learning Engineer Job:
- Job Title: Machine Learning Engineer Jobs in London 2026 – Apply Now
- Company: FORGIS
- Location: Zurich, Switzerland or Fully Remote
- Job Type: Full-time
- Industry: Artificial Intelligence, Machine Learning, Industrial Technology
- Work Arrangement: Remote opportunity available
- Education: Master’s degree in a relevant technical field preferred
About FORGIS:
In order to link devices, hardware, software, and automation systems in various manufacturing settings, FORGIS is creating an orchestration platform. Its technique seeks to create a cohesive, intelligent system out of disparate industrial machinery.
Digital engineers may learn from production data, make informed decisions, anticipate any issues, and constantly enhance manufacturing processes thanks to the platform’s integration of real-time information and industrial connection.
For a machine learning engineer, this entails working in close proximity to the real-world industrial AI difficulties and developing technologies that have the potential to impact factory operations.
Responsibilities for Machine Learning Engineer Jobs in London:
- Create and hone machine learning models with industrial and real-world production data.
- Create predictive models for production performance, maintenance needs, and equipment breakdowns.
- Develop anomaly detection systems to find odd trends in sensor and machine data.
- Utilize machine learning methods to increase production-line productivity and manufacturing processes.
- Utilizing both historical and current plant data, models are trained and continuously improved.
- Evaluate the model’s predictions against actual production results and make adjustments based on the findings.
- Integrate dependable machine learning models into the FORGIS system.
- Create machine learning pipelines that can handle data from industrial equipment, PLCs, robots, and sensors.
- Before using models to make operational decisions, test and validate them against actual production situations.
- Investigate issues with data, software, infrastructure, and machine learning models.
- Take charge of the entire machine learning lifecycle, from testing and development to implementation and oversight.
Who Should Apply?
This opportunity is particularly suitable for a technically strong Machine Learning Engineer who enjoys moving ideas from research into production.
- You should ideally have a Master’s degree from a leading university, such as UCL, King’s College London, Imperial College London, the University of Oxford, or another respected institution, in computer science, machine learning, statistics, electrical engineering, or a closely related field.
- FORGIS is looking for candidates who can demonstrate practical technical achievements, including machine learning models successfully deployed to production or substantial ML projects progressed from research through real-world implementation.
- Strong software engineering and programming skills are important, particularly experience developing and deploying machine learning pipelines at scale.
- Experience working with time-series information, sensor data, predictive maintenance, anomaly detection, or industrial process optimization would be highly valuable.
- You should also understand core machine learning principles, including model training, evaluation, validation, deployment, and the statistical concepts behind reliable model performance.
- The ideal candidate will be comfortable investigating problems across the complete ML stack and taking ownership from raw data through production deployment.
Check Also: Data Scientist Jobs at Wheely in London – Apply Now
Key Skills and Experience:
- master’s degree in a technological field that is pertinent.
- strong foundations in statistics and machine learning.
- outstanding skills in software engineering and programming.
- familiarity with implementing ML models in production.
- understanding of machine learning installations and pipelines.
- familiarity with sensor or time-series data.
- knowledge of anomaly detection and predictive maintenance.
- the capacity to assess and validate models with actual data.
- strong analytical problem-solving and debugging abilities.
- the capacity to operate autonomously and assume responsibility for ML initiatives.
- It is beneficial to have an interest in robotics, automation, industrial technology, or smart manufacturing.
Working Location:
- Location: Zurich, Switzerland or fully remote
- Job Type: Full-time
- Work Arrangement: Remote option available
- Visa Sponsorship: FORGIS states that visa sponsorship and relocation support are available. Applicants are encouraged to share their current location so the company can discuss the appropriate arrangements.
Benefits of Machine Learning Engineer Job:
- Professional Development and Advanced AI Knowledge: Machine Learning Engineer While working on difficult technology projects, jobs in London can offer chances to gain advanced experience in machine learning, artificial intelligence, predictive analytics, and real-world model deployment.
- Real-World Machine Learning Applications: By using machine learning to solve real-world issues including anomaly detection, predictive maintenance, time-series analysis, sensor data processing, and industrial process optimization, engineers can obtain invaluable experience.
- Robust Software Engineering creation: These positions can assist professionals become more competent end-to-end machine learning engineers by strengthening their programming, ML pipeline creation, model evaluation, deployment, debugging, and infrastructure skills.
- Opportunities for Remote and Flexible Work: Some Machine Learning Engineer jobs in London provide remote or hybrid work arrangements, which provide skilled workers more freedom while enabling them to work with cutting-edge digital firms and global engineering teams.
- Potential for International Career and Relocation: Some companies may sponsor visas and offer relocation support to qualified applicants, giving talented foreign engineers the chance to improve their careers while utilizing cutting-edge AI technologies.
- Meaningful Impact Through Intelligent Technology: Through useful artificial intelligence solutions, machine learning engineers may assist systems that enhance operational efficiency, anticipate equipment breakdowns, facilitate better decision-making, and revolutionize conventional industries.
Why Consider This Opportunity?
This role can be especially rewarding for engineers who want their machine learning expertise to have a visible, practical impact. You will not simply build models for theoretical benchmarks. Your work will help interpret real industrial data, identify problems before they become costly, and support smarter decisions on manufacturing floors.
Working across machine learning, industrial automation, software engineering, and real-time data also provides an opportunity to broaden your technical experience while contributing to an emerging area of industrial AI.
A Chance to Build Practical AI:
Manufacturing is becoming increasingly connected, but many factories still operate with equipment and systems from different vendors that do not naturally work together. FORGIS is working to address this challenge by bringing connectivity and intelligence into one platform.
As a Machine Learning Engineer, you can become part of that transformation. Your models could help machines communicate more intelligently with the wider production environment, identify unusual behavior, anticipate failures, and support continuous operational improvement.
For someone who wants to build technology that moves beyond experimentation and into the real world, this position offers an opportunity to work at the intersection of advanced AI and practical industrial challenges.
How to Apply for Machine Learning Engineer Jobs in London 2026?
The supplied application instructions ask candidates to:
- Join the FORGIS Slack community using the application invitation provided in the original listing.
- Send your CV to Atharva Dastenavar, Head of Product.
- Include your current location when applying, particularly if you require visa sponsorship or relocation support.
- Highlight relevant production ML projects, technical achievements, and experience deploying models into real-world environments.
Candidates should review the current FORGIS vacancy and application instructions before submitting an application, as recruitment details may change.
Do Machine Learning Engineer jobs offer remote working options?
Many technology employers offer remote or hybrid working arrangements, depending on business requirements. Candidates should carefully review each vacancy because working arrangements differ. Some positions may also support fully remote work from other eligible countries.
What skills do London Machine Learning Engineers need?
Important skills include machine learning, statistics, programming, software engineering, data analysis, model evaluation, deployment, and debugging. Experience with time-series data, sensors, predictive maintenance, anomaly detection, and scalable machine learning pipelines can provide additional advantages.
Can international candidates find sponsored Machine Learning Engineer positions?
Some London employers provide visa sponsorship and relocation support for eligible international candidates. However, sponsorship availability varies between companies and individual vacancies. Applicants should verify current eligibility requirements directly with employers before accepting offers or making relocation plans.
