Senior Machine Learning Engineer

Senior Machine Learning Engineer

AI / Machine Learning London / Remote-First

We are representing an early-stage technology company building AI-driven systems to help detect and counter harmful information threats in real time. The company operates in a mission-critical problem space combining machine learning data infrastructure and applied intelligence workflows to help users make faster more reliable decisions.

This is a high-ownership environment suited to engineers who care about building robust production systems not just experimenting with models.

The Role

This is an opportunity to join as a Senior Machine Learning Engineer and take ownership of production-grade ML systems from development through deployment monitoring and continuous improvement.

You will work closely with a cross-functional team across engineering machine learning and intelligence-focused domains. The role is hands-on and systems-oriented with a strong focus on reliability scalability and real-world performance.

This is not a research-only position. The ideal candidate has a proven track record of shipping operating and improving ML systems in live production environments.

What Youll Do

• Build deploy and maintain production machine learning systems for detecting harmful or misleading information at scale.
• Own the full ML lifecycle from data pipelines and model development through deployment monitoring and iteration.
• Design reliable and scalable ML infrastructure that supports both real-time and batch processing needs.
• Work with SQL and NoSQL databases to support data ingestion storage retrieval and analysis.
• Implement clean modular maintainable Python code that can be extended by other engineers.
• Use containerisation CI/CD and cloud infrastructure to support production-grade deployment workflows.
• Evaluate technical trade-offs across latency accuracy cost scalability and performance.
• Collaborate with engineering product and domain specialists to shape both the product and the underlying ML architecture.
• Translate ambiguous mission-critical problems into practical working technical systems.

What Were Looking For

• Strong experience building and deploying machine learning systems in production environments.
• A clear track record of owning ML systems end to end from data and models through deployment and monitoring.
• Strong Python engineering skills with the ability to write clean modular maintainable code.
• Hands-on experience with CI/CD pipelines and containerisation tools such as Docker.
• Solid experience working with both relational and non-relational databases.
• Experience with large-scale data processing frameworks including streaming and batch workflows.
• Broad exposure to different machine learning approaches and the judgment to apply the right method to the problem.
• Strong systems thinking especially around reliability scalability latency cost and operational performance.
• A pragmatic outcome-focused mindset suited to building real-world systems.
• Comfort working in a high-ownership early-stage environment.

Nice to Have

• Experience with NLP or machine learning systems related to content integrity misinformation trust and safety or information analysis.
• Exposure to intelligence security geopolitical risk or similarly complex data environments.
• Experience in an early-stage or high-growth startup.
• Familiarity with deep learning frameworks.
• Product-minded approach to ML engineering with an interest in shaping both technical infrastructure and user-facing outcomes.

Why This Role Is Exciting

• Own meaningful ML infrastructure in a mission-critical and technically challenging domain.
• Work on production systems where speed reliability and accuracy have real-world importance.
• Join early enough to shape the architecture engineering culture and product direction.
• Collaborate with a highly cross-functional team spanning engineering ML and specialist domain expertise.
• Take on broad ownership across the full ML lifecycle rather than being limited to narrow model work.
• Solve complex problems involving real-time detection large-scale data processing and applied machine learning.
• Work in an outcomes-driven environment with flexibility and autonomy.

Work Model

This is a full-time remote-first role based around London with flexibility and occasional in-person collaboration or business travel expected.

Apply now.

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