Staff ML Engineer, Production Systems

ActAI; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

ActAI in London, UK is hiring a Member of Technical Staff, Machine Learning to build core ML components for production systems from day one. You will ship, debug, and iterate on real-world models within latency, cost, and reliability constraints.

Ideal candidates have hands-on experience training, fine-tuning, and deploying ML models using Python with PyTorch or JAX, and you will collaborate with senior ML engineers and product teams to deliver robust ML-powered features at scale.

Qualifications

• Strong foundations in machine learning and modern neural architectures.
• Hands-on experience training, fine-tuning, or deploying ML models.
• Comfortable writing production-quality code and learning new tools quickly.
• Curious, coachable, and eager to learn from real systems in production.
• Able to work through ambiguity with guidance and grow ownership over time.

Responsibilities

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability and safety.

Skills

ML fundamentals

Neural architectures

Production coding

System design

Tools

Python

PyTorch

JAX

GPU deployments

Job description

ActAI in London, UK is hiring a Member of Technical Staff, Machine Learning to build core ML components for production systems from day one. You will ship, debug, and iterate on real-world models within latency, cost, and reliability constraints.

Ideal candidates have hands-on experience training, fine-tuning, and deploying ML models using Python with PyTorch or JAX, and you will collaborate with senior ML engineers and product teams to deliver robust ML-powered features at scale.