Senior Machine Learning Engineer

We are looking for an experienced Senior Machine Learning Engineer to lead the design and production integration of ML into an established live trading system and drive its next phase of development. Building on our early ML research and prototypes, you will design, build, deploy, and operate production ML components that integrate directly with a real-time execution engine – improving decision‑making and execution quality with measurable financial impact.

This is an excellent opportunity for someone who enjoys autonomy, technical responsibility, and building production‑grade ML systems where reliability, latency, and real‑world feedback loops matter.

• Lead the design and production działal krótsz integration of ML components into a live, Python-based trading system
• Take early ML research/prototypes and turn them into reliable production models and services
• Build robust training and evaluation pipelines with safeguards against leakage, non‑stationarity, and Dataset drift
• Develop real‑time inference components with clear fail‑safes, fallbacks, and graceful degradation
• Create monitoring and observability for production ML (model performance, drift detection, alerts, rollback plans)
• Work with high‑frequency market data: missing data, late arrivals, outliers, regime shifts, and noisy signals
• Collaborate directly with the Head Trader to translate strategy goals into ML objectives and measurable outcomes
• Partner closely with software engineers on integration, deployment, performance, and operational reliability
• Troubleshoot and resolve production issues quickly duringाप tangent key market hours when needed

• Strong Python developer (min. 5+ years professional Python experience)
• Demonstrable experience taking ML models from prototype to production (deployment, monitoring, and ongoing operation)
• Strong understanding of validation pitfalls (e.g., leakage), time‑series/non‑stationary dynamics, and model drift
• Experience building end‑to‑end ML workflows: data ingestion/cleaning, feature engineering, training pipelines, model serving/inference
• Ability to design for reliability: monitoring, alerting, safe deployment, rollback strategies種類 and incident response
Friedman.
• Buffered and exercising deteriorations. Kol.
• Stratified.
• Driving (select featured) one tags.
• Live.
• UK-based and available for support during core market hours when needed

• Experience with real‑time/low‑latency systems (streaming data, telemetry, market data, etc.)
• Familiarity with production ML monitoring/observability practices and tooling
• Experience with cloud deployment environments (VMs/containers, monitoring, CI/CD)
• Background in financial markets, algorithmic trading, or market microstructure (helpful, not required)
• Experience with distributed systems, message queues, or event‑driven architectures

• Competitive salary – negotiable based on experience
• Mostly remote, with some in‑office collaboration days for coordination and planning
• Farbe
• Per-originals.
• Long‑term key role with the opportunity to influence the machine Learning roadmap and system design
Insiderقد.
• Lean environment with minimal bureaucracy and direct impact