Python Software Engineer (AWS)

We're looking for exceptional Software Engineers to join a scaleup Medical AI firm aiming to do wonders for the healthcare sector using novel ML techniques. With big investment and data tie-ins secured, an already-large valuation and top talent on board, this one is not to be missed! You’ll build the sophisticated tooling and infrastructure that powers their groundbreaking Foundation Models - this is a rare opportunity to work at the intersection of advanced software engineering and frontier AI research, building systems that directly enable breakthroughs in drug development and patient care. You'll be working alongside world-class ML researchers, designing and implementing the tools, APIs, and platforms they need to train, evaluate, and deploy models at unprecedented scale. This isn't about maintaining legacy systems, it's about creating novel solutions to complex problems that haven't been solved before, in a domain where the stakes genuinely matter. Your work will directly accelerate their research velocity, enabling the team to iterate faster, experiment more effectively, and push the boundaries of what's possible in AI-driven healthcare. Strong academic background in Computer Science, Mathematics, Engineering, or a related quantitative field Proven track record of delivering high-quality software in fast-paced, high-stakes environments - whether in startups, research labs, or high-performance teams in larger firms Expert-level proficiency in Python, including deep understanding of the language's idioms, performance characteristics, and ecosystem Demonstrated experience designing and building APIs, SDKs, or developer toolkits used by other engineers or researchers Strong understanding of distributed systems concepts and familiarity with modern software engineering practices Experience working with complex data types and data structures, particularly in scientific computing or data-intensive applications Bonus points for: Direct experience working on large-scale ML systems, particularly training infrastructure, model serving, or ML platforms Previous work in or adjacent to ML research teams, bridging the gap between research and engineering Hands-on experience with ML frameworks and libraries (PyTorch, TensorFlow etc) Experience building data pipelines for large-scale scientific or healthcare datasets Understanding of modern ML infrastructure (GPU clusters, distributed training, optimization) Knowledge of healthcare data standards, regulations (GDPR, HIPAA), or experience in regulated industries Contributions to open-source projects, particularly in the ML or scientific computing space Experience with cloud platforms (AWS, GCP, Azure) and infrastructure as code The firm offers competitive salaries plus equity and bonus schemes, and aims to provide a meritocratic environment where performance is rewarded in a big way.