Senior ML Systems Engineer

This role combines advanced machine learning infrastructure expertise with strong systems engineering capabilities to deliver scalable, production-ready AI solutions. The focus is on building high-performance platforms that enable the training, evaluation, and deployment of cutting-edge models across large multimodal datasets, directly impacting real-world applications in a rapidly evolving domain.

As the organization continues to scale its AI capabilities, it is hiring a Senior ML Systems Engineer to take ownership of its end-to-end ML infrastructure. This is a high-impact, hybrid role suited to someone who can operate across data engineering, model infrastructure, and production systems. You will work closely with research and product teams to translate complex requirements into robust, scalable systems that drive performance, reliability, and innovation.

Your Role

You will design, build, and optimize the infrastructure that powers large-scale machine learning workflows. From data ingestion and training pipelines to model deployment and inference optimization, you will operate across the full ML lifecycle. This role blends deep technical execution with cross-functional collaboration, ensuring systems are efficient, scalable, and aligned with business and product goals.

What You’ll Do

▪️ Build and evolve a data platform for managing large-scale multimodal datasets including video, embeddings, and metadata

▪️ Develop and optimize ML training infrastructure and data pipelines using modern distributed frameworks

▪️ Create tools and systems for dataset inspection, model evaluation, and experimentation workflows

▪️ Design and maintain infrastructure for model versioning, lifecycle management, and production promotion

▪️ Own and optimize production inference pipelines, including GPU utilization and parallelization strategies

▪️ Collaborate with research teams to productionize models and improve training efficiency

▪️ Ensure scalability, reliability, and performance across the ML platform

▪️ Implement best practices for monitoring, testing, and system observability

▪️ Contribute to architectural decisions and continuously improve platform design

▪️ Work in Agile environments and maintain clear technical documentation

What You Bring

▪️ Proven experience building production ML systems or ML infrastructure

▪️ Strong programming skills in Python and at least one robust production language such as C++, Java, or Scala

▪️ Experience with distributed computing frameworks and large-scale data processing

▪️ Hands-on experience with ML frameworks such as PyTorch and tools for scaling training workloads

▪️ Familiarity with modern data platforms and technologies such as Spark, Ray, or similar

▪️ Experience working with high-performance compute environments and GPU-based systems

▪️ Strong understanding of system design, scalability, and performance optimization

▪️ Product mindset with the ability to solve complex problems autonomously

▪️ Excellent communication skills and ability to collaborate with research and engineering teams

Why Join?

▪️ Own and shape the ML infrastructure behind cutting-edge AI systems

▪️ Work closely with highly technical teams on complex, high-impact challenges

▪️ Build scalable systems that directly influence product performance and innovation

▪️ Join a team that values autonomy, technical excellence, and continuous improvement

Package

▪️ Competitive base salary aligned to experience

▪️ Equity package with strong growth potential

▪️ Visa sponsorship available

▪️ Hybrid working model with flexibility

Location

▪️ London, United Kingdom

▪️ Hybrid role with in-office collaboration