Senior Intelligent Systems Engineer

EntroMetrix
London, GB
On-site

Why this role

Pace
Fast Paced
Collaboration
High
Autonomy
Medium
Decision Impact
Team
Role Level
Individual Contributor

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • reliable decision-making systems
  • validated industrial models
Typical background
engineeringcomputer sciencephysics

Transferable backgrounds

  • Coming from data scientist
  • Coming from software engineer

Skills & requirements

Required

Model DevelopmentSystem EngineeringOptimizationSimulationData Analysis

Preferred

Physics-informed ModelingDigital Twins

Stack & domain

PythonEngineeringComputer SciencePhysicsMathematicsOperations ResearchSystems Engineering

About the role

Original posting from EntroMetrix

Company Description

EntroMetrix is an early-stage UK startup building physics-informed AI for industrial operations.

We help manufacturers improve efficiency, sustainability and operational performance by turning data into actionable intelligence. Our models have already been validated on real industrial data, showing significant improvement potential, and we are now expanding deployment.

We are founded by engineers from Cambridge and Imperial and are a small, high-calibre team tackling a critical industrial challenge, where the pace is fast, the technical bar is high, and every hire has direct impact on what we build.

Role Description

We are looking for an Intelligent Systems Engineer to help develop and scale the technical systems behind EntroMetrix’s industrial intelligence platform. You will work on the modelling, logic and engineering required to support reliable decision-making across complex industrial operations.

This is a hands-on engineering role focused on building robust technical systems for real-world environments. You will work closely with the founding team, engineering team and customer deployments to help ensure our platform is technically rigorous, scalable and useful in operational settings.

What you will do:

  • Develop technical models and engineering logic to support industrial decision-making.
  • Work on systems that connect operational data, engineering constraints and performance improvement opportunities.
  • Help translate complex industrial environments into structured, usable technical representations.
  • Build and improve components that support analysis, simulation, optimisation and decision support.
  • Work with the ML and data teams to ensure outputs are reliable, explainable and operationally relevant.
  • Support customer deployments by helping validate whether system outputs reflect real operational behaviour.
  • Develop reusable technical components that can scale across different sites, sectors and use cases.
  • Contribute to platform reliability, technical quality and engineering standards.
  • Contribute to the technical direction of the platform as one of the first intelligent systems hires.

What we are looking for:

  • A degree in engineering, computer science, physics, mathematics, applied mathematics, operations research, systems engineering or a closely related STEM field from a top university.
  • Strong practical experience building models, simulations, optimisation systems or technical software using Python or similar tools.
  • Experience with one or more of: systems engineering, operations research, optimisation, simulation, control systems, process modelling, production systems or applied engineering software.
  • Comfort working with real-world operational systems, including imperfect data, changing requirements and complex technical constraints.
  • Interest in applying engineering and computational methods to physical operations, manufacturing and industrial performance.
  • Strong engineering judgement, with an ability to translate complex technical problems into practical, scalable systems.
  • 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, process engineering, energy or operational systems.
  • Experience with mathematical optimisation, simulation, decision-support systems or applied modelling.
  • Exposure to digital twins, physics-informed modelling, industrial analytics or operational software.
  • Familiarity with operational datasets from enterprise, production or industrial systems.
  • Research or applied experience in systems modelling, operations research, process systems engineering or applied optimisation.

Why join:

  • Competitive compensation package.
  • Ownership of a critical technical layer at an early-stage company.
  • The chance to build technical systems 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.

How to apply:

Apply on LinkedIn and 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 engineering and computational methods to real-world industrial systems to:

Source: EntroMetrix careers

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