REGISTRIEREN

Jobbörse

Finde Jobs in deiner Nähe – ob vor Ort, hybrid oder remote.
  • Ähnliche Jobs zu: Principal Machine Learning Engineer (Revenue Optimisation)
XX
Principal Machine Learning Engineer (Revenue Optimisation)tem • London, England, United Kingdom
Jetzt Bewerben
XX

Principal Machine Learning Engineer (Revenue Optimisation)

tem
  • GB
    London, England, United Kingdom
  • GB
    London, England, United Kingdom
Jetzt Bewerben

Über

Requirements
Deep experience building ML systems for pricing, revenue optimisation, or real-time decision-making — at companies where pricing is the product, not a supporting function. Track record of models that reached production and moved commercial metrics
Strong foundation in stochastic optimisation and probabilistic modelling. The judgement to formulate ambiguous business problems mathematically before reaching for a tool
First-principles reasoning across methods. You choose between stochastic programming, reinforcement learning, classical ML, or a simple heuristic based on what the problem demands
The engineering depth to match your modelling. Production-grade Python, high bar for code quality, and the ability to carry models from formulation to deployment without being blocked
Senior technical leadership. A track record of setting direction for a significant technical area, influencing cross-functional teams, and translating complex model behaviour into clear terms for commercial, product, and engineering stakeholders — so decisions are understood and acted on
(Desirable) Experience with real-time pricing at scale — ride-hailing, food delivery, logistics, or similar environments where latency and portfolio effects matter
(Desirable) Familiarity with energy markets, power trading, or portfolio risk management
(Desirable) PhD or equivalent research depth in a quantitative discipline — statistics, applied mathematics, operations research, or similar
(Desirable) Ability to reason about trade-offs between optimisation solvers (Gurobi etc.) and gradient-based methods (PyTorch etc.), and the judgement to know when to reach for each
(Desirable) Experience with causal inference or reinforcement learning in applied commercial settings
What the job involves
Rosso is tem's core IP. It's the transaction infrastructure that replaces what a traditional trading desk does — forecasting energy prices and volume, building a real-time picture of the portfolio, optimising the fees placed on every quote, and autonomously managing hedging decisions. All of it running continuously. All of it on the critical path for every deal tem closes
Machine learning is at the heart of it. Rosso combines forecasting, optimisation and classical ML to process billions of data points and drive thousands of automated decisions a day. Every inference shapes the prices our customers see
We've proved the concept. tem now serves 2% of the UK market. The next step is building a pricing engine that doesn't just react — one that proactively drives growth by targeting the right customers at the right time, at the right price, while protecting margin and portfolio balance. Then taking that internationally
We're looking for a Senior Staff Machine Learning Engineer to own pricing ML within Rosso. This is a hands‑on senior IC role with real technical authority — you set the strategy, define the mathematical approach, build the models, and ship them. You work closely with MLOps and software engineers, but you don't wait on them. The hard part of this job is the formulation, not the infrastructure
Own the technical direction for pricing ML. Define what to build and how. Set the roadmap for the pricing engine as a core piece of tem's IP — and be accountable for its performance
Formulate and solve the pricing problem properly. The mathematical foundation doesn't fully exist yet. Your first job is to define it: a dynamic, real‑time system that simultaneously optimises for signing probability, portfolio balance, and margin. Choose the right approach — stochastic programming, reinforcement learning, classical ML, or a hybrid — based on the problem, not familiarity
Build and ship models end-to-end. Own the modelling and data layer. Write production-grade Python. Architect models with deployment in mind and carry them through to production — you can execute without being blocked by engineering dependencies
Solve imbalance problems. Develop probabilistic models to optimise risk management and short-term balancing decisions in a highly dynamic environment
Be the voice of pricing ML across the business. Commercial, product, and engineering teams depend on this engine. They need to understand what it's doing and why. You make that happen — clearly, without losing precision
#J-18808-Ljbffr
  • London, England, United Kingdom

Sprachkenntnisse

  • English
Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.