Define and drive the technical vision for ML solutions across products and platforms
Own the end-to-end software development lifecycle — from design and code reviews through to deployment and operations
Architect high-performance, scalable microservices, including synchronous and asynchronous web services
Build real-time inference pipelines for complex models using Triton, TensorRT, and mixed-precision computing
Mentor engineers, set technical direction, and foster a strong team culture
Champion engineering excellence, system resilience, and continuous operational improvement

Degree in Computer Science, Mathematics, or a related field
5–10 years of full software development lifecycle experience (design, coding, testing, deployment, and operations)
5–10 years of Python expertise, including advanced features and libraries
Strong experience designing RESTful APIs (e.g., FastAPI)
Proficiency with Docker, Kubernetes, and CI/CD pipelines
3+ years designing and architecting large-scale distributed systems on cloud platforms (AWS, Azure, or GCP)
Proven experience as a tech lead or engineering mentor
MS or PhD in Computer Science or ML
Hands-on experience with ML frameworks: PyTorch, SageMaker, Triton, or TensorRT
Familiarity with NoSQL and document databases
Track record of handling big data, optimising workflows, and improving system performance

AI Staff Machine Learning Engineer, General AI, ML, Big Data

Key skills