Staff Machine Learning Engineer (Pricing)

Location: United Kingdom; fully remote, distributed across Europe

Salary: £115,000 or equivalent in local currency annually, plus equity

Company

hirify.global is a technology company rebuilding energy transactions by connecting businesses directly with renewable generators and making transactions transparent and traceable. The company has 160+ employees, serves 4,000+ UK businesses across 8,500+ sites, and raised a $75M Series B in early 2026.

What you will do

• Own core components of Rosso, hirify.global’s dynamic pricing syshirify.global, from design through production operation.
• Choose and evaluate modelling, experimentation, and measurement approaches that reduce sales adjustment, including holdouts for low-volume, high-value deals.
• Build monitoring, alerting, guardrails, staged releases, drift detection, and protections against runaway feedback loops.
• Make pricing decisions reproducible for debugging, incident response, and regulatory review.
• Work with Price Quoting, ML Platform, engineering, product, and commercial teams to ship production-ready models and improve commercial metrics.
• Turn sales pricing adjustments into model inputs and redesign recurring pricing workflows with appropriate AI assistance while deciding which steps remain human.

Requirements

• Hands-on production coding is required; this is not a people-leadership or architecture role where others implement the work.
• Experience owning a live ML syshirify.global that made automated decisions involving money, such as algorithmic trading, dynamic pricing, marketplaces, ad bidding, credit, or betting.
• Experience handling production failures including feedback loops, silent drift, bad outputs reaching customers, and rollbacks.
• Strong probabilistic modelling, decision-making under uncertainty, pricing, conversion or elasticity modelling, and experimentation skills.
• Experience formulating problems from first principles and selecting simple effective approaches.
• Experience running ML services on AWS or similar cloud infrastructure, including containerised models behind APIs, event-driven microservices, infrastructure as code, CI/CD, testing, and rollback pipelines.
• Production-grade Python with a focus on observability, testing, and replay; ability to work as a peer with software engineers.
• Track record of moving a commercial metric with product managers and commercial stakeholders.
• Daily use of AI tooling as a productivity multiplier, with an understanding of its limitations.
• Energy experience is not required; experience with live pricing or trading syshirify.globals and the judgement gained from operating them is essential.

Nice to have

• Experience in energy, commodities, or markets where prices, forecasts, and risk interact.
• Production experience with contextual bandits, causal inference, or Bayesian methods.
• Experience with stochastic optimisation or operations research.
• PhD in mathematics, physics, computer science, operations research, or a related field.

Culture & Benefits

• Fully remote work across Europe.
• £1,200 or €1,200 annual home-working and wellbeing budget for equipment, coworking, therapy, fitness, or similar expenses.
• 25 days of holiday plus public holidays, with the option to swap public holidays, and an additional birthday day off.
• Stock options for all team members.
• Interview process normally takes 2–3 weeks from first call to offer.

Hiring process

• Talent Team call covering experience, motivation, and the role.
• Behavioural interview with the Rosso GM and hiring manager.
• 90-minute technical interview with potential peers, including a live technical exercise.
• Final 45-minute Bar Raiser interview with two cross-functional stakeholders.