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# Senior Staff Machine Learning Engineer - ML Platform

- **Company:** Tem, Inc
- **Location:** United Kingdom (Remote available)
- **Experience:** Expert
- **Salary:** £115,000 - £127,000
- **Contract:** Temporary to permanent
- **Skills:** Algorithmic Trading, Databases, Data Structures, Data Systems, Machine Learning, Azure Machine Learning, Build Management, Machine Learning Operations
- **Published:** November 11, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5961472541

## About the Role

* Strong ML engineering foundations: experience developing, deploying and improving ML models in production.
 * Experience contributing to or building an MLOps stack, including ensuring reliability and observability.
 * Experience with the scaling pressures and complexities of large-data ML workloads, and designing data systems (pipelines, databases, query patterns) to handle them.
 * Experience with time-series forecasting in particular.
 * Knowing what good looks like in a ML platform, and being ready to build it in a high-ownership environment.

## Description

In this role you will work on the ML platform inside Rosso, improving the infrastructure, tooling and standards that let us develop, train, evaluate, monitor and iterate models quickly and with confidence. You know ML engineering deeply and will contribute to model improvements where it matters, with a primary focus on building the platform and tools that help the whole team work faster and better.

You will:

 * Build the systems that let us deploy, iterate, and scale ML and optimisation models without friction.
 * Give us clear operational visibility into how every model is performing, and where it is not.
 * Build evaluation and backtesting tooling for ML models, pricing and trading strategies.
 * Take ownership of model inference and training in production. The role includes work-hours on-call responsibility, and may extend to out-of-hours in the future.

The metric this role moves: number of effective forecasting & optimisation ML models deployed within our stack. Success means a new model goes from idea to trusted production with standard tooling, clear evaluation and confidence from day one.

ML infrastructure and deployment

 * Shape and improve the infrastructure that underpins ML deployment across pricing, forecasting, prediction and optimisation.
 * Design and build the systems that let us take a model from experiment to production quickly and repeatably.
 * Scale models and pipelines as volume, markets and complexity grow.

Observability and quality

 * Build the tooling and code that ensure models run reliably and produce sensible results.
 * Create operational and analytical monitoring so we catch failures, drift and degradation early.
 * Build confidence in our input data through validation, checks and clear data contracts.

Evaluation, experimentation and backtesting tooling

 * Develop the tooling and abstractions to evaluate ML models and optimisation algorithms during experimentation, including backtesting of pricing and trading strategies.
 * Standardise processes and data structures so each new model is faster to ship than the last.

Data systems

 * Mature the data systems (databases, pipelines, validations, ingestions) that let us manage model rollouts safely.

Ownership

 * Own model inference and training in production, including on-call during working hours. There is no out-of-hours on-call today, though this may change as the platform grows.
 * Contribute directly to model improvements where your ML expertise moves the needle., * Probabilistic modelling and quantifying uncertainty, for example probabilistic forecasts, calibration or Bayesian methods.
 * Quant tooling experience, such as building backtesting frameworks or evaluation tooling for trading or optimisation strategies.
 * Any of the above in finance or energy, including automated trading systems.

 * Salary aligned to internal benchmarks and reviewed twice a year.
 * Stock options so everyone has ownership in our mission.
 * 25 days holiday plus public holidays. Swap public holidays for the ones that matter most to you, and enjoy your birthday off.
 * Remote first and flexible working, with clear core hours and no internal meetings on Friday afternoons.

Home working and wellbeing budgets:

 * Up to GBP1,200 or EUR1,200 per year for your remote setup.
 * Up to GBP150 or EUR150 per month for wellbeing.

We move fast. Most processes take 2 to 3 weeks from first chat to offer. If you need us to adapt anything, let us know.

 * Intro call with Talent, 30 minutes.
 * Behavioural interview, 30 minutes.
 * Skills interview 90 minutes
 * Bar Raiser interview with leadership stakeholders, 30 minutes.