CAREERS

Software
that moves
a mixer.

Most AI jobs end at a prediction. Here the prediction becomes a setpoint on a 2,000 litre vessel at 3am, and a chemist has to trust it. If that sounds like the interesting version of the problem, we should talk.

HYBRIDPLANT + REMOTE
SMALLTEAM
HIGHOWNERSHIP
REALCONSEQUENCES
VESSEL STATEEMULSON
VISCTEMPTORQUE PREDICTED STATE VS ENVELOPET−120sNOW EST. VISCOSITY 42,100 cP · IN ENVELOPE · CONF 0.94

State estimated from drive telemetry, not from a sample nobody took.

PROCESS MLEDGE SYSTEMSCOMPUTER VISIONOPTIMISATIONCONTROLQUALITY SYSTEMSFORWARD DEPLOYED

OPEN ROLES

Who we are looking for

All roles involve time inside real plants. Nobody here builds manufacturing autonomy purely from a laptop.

ENGINEERING

PROCESS ML ENGINEER

Build the process world model: multimodal models over inline sensors, formula structure and batch outcomes. You should be comfortable being wrong in front of a chemist.

  • PyTorch, time series, multimodal
  • Bonus: rheology or chemical engineering

ENGINEERING

EDGE SYSTEMS ENGINEER

Deterministic Rust/C++ runtime on Jetson and IGX: control loops, watchdogs, safe-state, offline survival and signed OTA.

  • Rust or C++, Linux, real-time
  • Bonus: OPC-UA, industrial protocols

ENGINEERING

COMPUTER VISION ENGINEER

Spectral shade regression and high-speed defect vision across compacts, bullets, jars and tubes at full line rate.

  • TensorRT, camera pipelines
  • Bonus: colour science, spectrophotometry

ENGINEERING

OPTIMISATION ENGINEER

Campaign sequencing, changeover, cleaning validation and filler balancing with cuOpt at plant scale.

  • Constrained optimisation, OR
  • Bonus: manufacturing scheduling

FIELD

FORWARD-DEPLOYED ENGINEER

Live on site during instrumentation and go-live. Translate between chemists, OT teams and the model stack.

  • Strong generalist engineer
  • Bonus: GMP plant experience

QUALITY

QUALITY SYSTEMS LEAD

Own validation approach, audit design and ISO 22716 alignment. Make autonomy defensible to an inspector.

  • Cosmetics or pharma GMP
  • Bonus: computerised system validation

HOW WE WORK

The operating style

ON SITE, OFTEN

Engineers visit plants. You cannot model an emulsion you have never watched being made, and you cannot design a console for an operator you have never met.

HONEST ABOUT LIMITS

We label what is aspirational, internally and publicly. Overclaiming to a quality manager is a career-limiting move in this industry.

SMALL SURFACE, DEEP WORK

One vertical, five products, one runtime. We say no to adjacent verticals constantly.

WRITTEN THINKING

Decisions are written down with their assumptions, because in two years an auditor or a successor will ask why.

REAL DEADLINES

A pilot window is a plant’s production calendar. It does not move because a sprint slipped.

NO THEATRE

No demo-driven development. If it will not survive a night shift, it is not done.

HIRING PROCESS

Four steps, two weeks

  1. 01

    INTRO

    Thirty minutes on what you have built and what you want to build. Mutual filter, no whiteboard.

  2. 02

    TECHNICAL

    A real problem from our domain, discussed together. No leetcode, no take-home that eats a weekend.

  3. 03

    DEPTH

    A session with the team you would join, plus a conversation about how you handle being wrong in production.

  4. 04

    OFFER

    Reference calls, offer, and a written explanation of the level and the compensation logic.

WHAT WE OFFER

The deal

EQUITY

Meaningful equity at an early stage, explained clearly including the parts that are uncomfortable.

FLEXIBILITY

Hybrid working around plant visits. Deep work is protected; site weeks are intense by design.

HARDWARE

Real GPU access for development and training, plus the edge hardware you need on your desk.

LEARNING

You will learn cosmetics chemistry, GMP and industrial control from people who do it professionally.

LEVELS

How we think about seniority

How we think about seniority
LEVELSCOPESIGNAL
EngineerOwns componentsShips correct work with support; asks good questions early
SeniorOwns a subsystemDesigns for failure modes; unblocks others; writes it down
StaffOwns a domainSets technical direction; trusted alone in front of a customer’s quality team
PrincipalOwns a cross-cutting betChanges what the company builds; carries the hardest ambiguity

REALITY CHECK

What this job is not

NOTA PURE RESEARCH ROLE
NOTFULLY REMOTE
NOTLOW STAKES
NOTA BIG TEAM

INTERVIEW PREP

What we will actually ask you

We ask about a system you shipped that had consequences when it failed, and what you changed afterwards. We ask how you would detect that a model has quietly degraded on one vessel.

We ask what you would refuse to automate. Candidates who cannot name anything they would refuse to automate tend not to do well here.

  • A failure you owned and what it changed.
  • How you would detect silent model degradation.
  • What you would refuse to automate, and why.
  • How you explain uncertainty to a non-ML expert.
  • The last time you were wrong in front of a customer.

PROCESS FACTS

STEPS
4
TYPICAL DURATION
2 WEEKS
TAKE-HOME
NO
LEETCODE
NO
SITE VISIT
OFFERED
FEEDBACK
ALWAYS GIVEN

If it will not survive a night shift with a tired operator and a sensor that just went noisy, it is not finished.

Serumon engineering standard

CAREERS FAQ

Before you apply

APPLY

Tell us what you would build

Not a cover letter. One page on the hardest part of closing a control loop in a GMP plant, and how you would attack it.