Senior ML Engineer: End-to-End Production & Impact

Guidant Global; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Guidant Global is seeking a senior Machine Learning Engineer to lead end-to-end ML delivery in a security‑aware environment in the United Kingdom. You will develop, validate and deploy models, framing hypotheses with statistical rigor and running experiments to evaluate performance and impact.

You will translate complex technical concepts for non‑technical stakeholders, and collaborate with engineering and governance teams to productionise ML in regulated contexts.

Qualifications

• Senior practitioner level in ML engineering or equivalent.
• Strong grounding in applied mathematics, statistics and scientific practice.
• Excellent Python skills for building, evaluating and deploying ML models.
• Experience evaluating models through quantitative evidence and structured experimentation.
• Strong software engineering practices delivering readable, testable and maintainable code.
• Experience integrating ML solutions into production systems.
• Experience operating in secure, regulated or high-assurance environments.

Responsibilities

• Lead end-to-end delivery of ML solutions from problem definition through experimentation and iteration.
• Develop, validate and deploy ML models into production environments.
• Apply statistical and scientific thinking to frame hypotheses and assess uncertainty.
• Design and run experiments to evaluate model behaviour and impact.
• Work with real, imperfect data from operational systems.
• Integrate ML components into broader software and data platforms.
• Communicate complex ideas clearly to non-technical stakeholders.

Skills

Python

Mathematics / Statistics

Experimentation

Production systems

Communication

Job description

Guidant Global is seeking a senior Machine Learning Engineer to lead end-to-end ML delivery in a security‑aware environment in the United Kingdom. You will develop, validate and deploy models, framing hypotheses with statistical rigor and running experiments to evaluate performance and impact.

You will translate complex technical concepts for non‑technical stakeholders, and collaborate with engineering and governance teams to productionise ML in regulated contexts.