CAREERS

Careers at EntroMetrix

Manufacturing is one of the biggest, hardest and most important systems in the world, but many factories still make critical operational decisions with fragmented data and limited intelligence. EntroMetrix is changing that by building physics-informed AI that helps industrial teams run more efficient, resilient and sustainable operations.

01 / OPEN ROLES

We are a small team founded by engineers from Cambridge and Imperial, working on a problem where better software can have a real-world impact on energy, materials and production. If you want to build serious technology, work close to real industrial customers and have a direct hand in shaping an early company, EntroMetrix is the place to do it. We are hiring across a number of roles. If you're a fit, apply.

THE ROLE

We are looking for a Machine Learning Engineer to help build frontier models to understand and improve complex operational systems. The work sits at the intersection of scientific machine learning, time-series modelling, optimisation and real-world deployment. You will work closely with the founding team, customer sites and industrial data to turn early technical validation into a scalable product.

This is a hands-on engineering role. You will train models and see them run on real plants. You will build systems that need to work with messy data, operational constraints and real-world environments.

WHAT YOU WILL DO
Design, train and deploy machine learning models for complex operational systems.
Work with sparse, noisy and irregular time-series data from real-world environments.
Build models that combine data-driven learning with physical and operational constraints.
Develop reusable modelling components that can scale across different sites and use cases.
Work with the product and engineering team to move models from prototype to production.
Evaluate model performance, reliability and robustness in applied settings.
Spend time with customers to understand the operational context behind the data.
Contribute to the technical direction of the platform as one of the first ML hires.
WHAT WE'RE LOOKING FOR
A degree in machine learning, computer science, engineering, physics, mathematics, applied mathematics, operations research or a closely related STEM field from a top university.
Strong practical experience building machine learning models in Python, ideally using PyTorch, JAX or similar frameworks.
Experience with one or more of: scientific machine learning, physics-informed ML, time-series modelling, optimisation, simulation, forecasting or probabilistic modelling.
Comfort working with messy real-world data, including missing values, drift, noise and inconsistent data quality.
Interest in applying machine learning to physical systems, industrial operations and real-world optimisation problems.
In-person working from our London office, typically 4-5 days per week, with occasional travel to customer sites in the UK.
NICE TO HAVE
Experience deploying ML models into production.
Experience with optimisation, simulation, control systems or operations research.
Exposure to industrial or operational data environments.
Experience with Bayesian approaches, multi-fidelity data streams, symbolic regression (“glass-box”) or reinforcement learning.
Publications or research experience in scientific ML, machine learning for physical systems or applied optimisation.
WHY JOIN
Competitive compensation package.
Ownership of a critical technical layer at an early-stage company.
The chance to build frontier AI models that will define how factories are run over the next decade.
Work directly with manufacturers across sectors, from large enterprises to SMEs, and see your models deployed in real operations to help decarbonise industry and improve operational resilience.
A small, technical founding team with high ownership, honest feedback and no theatre.
Unlimited coffee (other drinks also possible).

Send your CV, a short note on a technical project you are proud of, and a few lines on why you are interested in applying machine learning to real-world systems.

Apply
THE ROLE

We are looking for a Forward Deployed Engineer to lead the technical delivery of EntroMetrix in real industrial environments. You will work directly with manufacturers to understand how their operations run, connect the systems and data needed for deployment, and ensure our models translate into practical recommendations that customers can trust and use.

This is a hands-on engineering role with direct customer exposure. You will move between site visits, technical implementation, product feedback and internal engineering work, helping us turn each deployment into a repeatable foundation for future customers.

WHAT YOU WILL DO
Deploy EntroMetrix at customer sites across manufacturing, supply chain and shopfloor environments.
Work with customers to understand their operational workflows, KPIs, constraints and pain points.
Integrate data from ERP, MRP, production systems, spreadsheets, sensors, energy data, SCADA, historians and other industrial sources.
Translate customer problems into clear technical requirements for the product and engineering team.
Configure dashboards, workflows and model outputs around real customer use cases.
Validate system outputs with plant managers, operations teams, engineers and technical stakeholders.
Work with the ML, data and systems teams to move deployments from pilot to scalable product.
Identify repeatable patterns across customer deployments that can become core platform capabilities.
Contribute to the technical direction of the platform as one of the first forward deployed hires.
WHAT WE'RE LOOKING FOR
A degree in engineering, computer science, data science, physics, mathematics, applied mathematics, operations research or a closely related STEM field from a top university.
Strong practical experience building software, data pipelines or technical systems in Python or similar tools.
Experience working with one or more of: industrial data, enterprise systems, APIs, cloud deployment, data integration, analytics, dashboards or operational software.
Comfort working with messy real-world data, unclear customer requirements, fragmented systems and fast-changing deployment environments.
Strong interest in applying engineering, software and data systems to physical operations, manufacturing and real-world optimisation problems.
Strong communication skills and the ability to work directly with customers, including plant managers, engineers, IT teams and senior operational stakeholders.
In-person working from our London office, typically 4-5 days per week, with regular travel to customer sites in the UK.
NICE TO HAVE
Experience deploying technical products into customer environments.
Experience with manufacturing, industrial operations, supply chain, process engineering or energy systems.
Exposure to ERP, MRP, SCADA, historians, OPC-UA, IoT data, production systems or industrial databases.
Experience in a startup, consulting, implementation engineering, solutions engineering or customer-facing technical role.
Ability to prototype quickly across backend, data, dashboards and customer workflows.
Experience with Bayesian approaches, multi-fidelity data streams, symbolic regression (“glass-box”) or reinforcement learning.
WHY JOIN
Competitive compensation package.
Ownership of a critical deployment layer at an early-stage company.
The chance to build the operating layer that will define how factories are run over the next decade.
Work directly with manufacturers across sectors, from large enterprises to SMEs, and see your work deployed in real operations to help decarbonise industry and improve operational resilience.
A small, technical founding team with high ownership, honest feedback and no theatre.
Unlimited coffee (other drinks also possible).

Send your CV, a short note on a technical project you are proud of, and a few lines on why you are interested in deploying technical systems in real-world industrial environments.

Apply
THE ROLE

We are looking for an Industrial Data Engineer to support and scale the data infrastructure behind EntroMetrix's industrial intelligence platform. You will work with operational data from manufacturing environments, helping connect ERP, production, inventory, energy and shopfloor data into reliable pipelines that support modelling, optimisation and customer deployment.

This is a hands-on engineering role focused on making industrial data robust, traceable and usable across multiple sites. You will work across data ingestion, transformation, validation and pipeline development, helping extend a repeatable data layer as EntroMetrix scales across different factories, sectors and customer systems.

WHAT YOU WILL DO
Support and extend data pipelines for industrial operations, including ERP, MRP, production, inventory, energy, sensor and shopfloor data.
Work with real operational datasets from manufacturing environments, including time-series, transactional and process data.
Clean, structure and validate industrial data for modelling, optimisation and customer deployment.
Develop reusable schemas and data models that can scale across different customer sites and use cases.
Integrate data from spreadsheets, APIs, databases, SCADA systems, historians and other industrial sources.
Work closely with the ML, systems and deployment teams to ensure data is reliable, traceable and model-ready.
Identify data quality issues, missing signals, unit inconsistencies, timestamp problems and system-level gaps.
Help improve the data architecture required to support scalable deployment across multiple industrial sites.
Contribute to the technical direction of the platform as one of the first data engineering hires.
WHAT WE'RE LOOKING FOR
A degree in computer science, engineering, data science, mathematics, physics, applied mathematics, operations research or a closely related STEM field from a top university.
Strong practical experience building data pipelines, data systems or backend infrastructure using Python, SQL or similar tools.
Experience working with one or more of: data engineering, ETL/ELT pipelines, time-series data, APIs, databases, data warehouses, cloud platforms or analytics infrastructure.
Comfort working with real-world data, including missing values, inconsistent formats, irregular timestamps, noise and variable data quality.
Interest in applying data engineering to physical systems, industrial operations and real-world optimisation problems.
Strong engineering judgement, with an ability to balance speed, reliability and scalability in early deployments.
In-person working from our London office, typically 4-5 days per week, with occasional travel to customer sites in the UK.
NICE TO HAVE
Experience with industrial, manufacturing, supply chain, energy or operational datasets.
Exposure to ERP, MRP, SCADA, historians, OPC-UA, IoT data, production systems or industrial databases.
Experience building data infrastructure for ML, analytics, optimisation or simulation systems.
Familiarity with cloud infrastructure, deployment workflows, data orchestration tools or modern data stacks.
Experience working in a startup, applied engineering team or customer-facing technical environment.
WHY JOIN
Competitive compensation package.
Ownership of a critical data layer at an early-stage company.
The chance to build the data infrastructure that will support how factories are run over the next decade.
Work directly with manufacturers across sectors, from large enterprises to SMEs, and see your work deployed in real operations to help decarbonise industry and improve operational resilience.
A small, technical founding team with high ownership, honest feedback and no theatre.
Unlimited coffee (other drinks also possible).

Send your CV, a short note on a technical project you are proud of, and a few lines on why you are interested in applying data engineering to real-world industrial systems.

Apply
02 / HOW TO APPLY

We are hiring now. To apply, ask a question, or request any adjustments to your application, email info@entrometrix.ai. You can also follow us on LinkedIn for updates.

These are in-person roles based in London. We are currently unable to offer visa sponsorship, so applicants must already have the right to work in the UK.

We read every application, but the volume means we cannot always reply individually. If you have not heard back within two weeks, please assume we have not been able to take your application forward this time.