Senior AI Engineer at Causaly

Causaly

London·10h ago

SeniorFull-timePythonRustRailsTensorFlowPyTorchCI/CDAIMLNLP

Salary Range

$99,450 - $134,550 /year

Estimated

This salary is estimated based on similar roles. The actual salary may vary.

About the Role

We are looking for AI engineers to join Causaly, an AI platform for enterprise-scale scientific research. You will help transform research outcomes in biomedical sciences by utilizing generative AI and agents to help scientists find novel connections and insights from biomedical literature and datasets.

Key Responsibilities

→Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring
→Apply strong software engineering principles to ensure AI systems are reliable, maintainable, and production-ready
→Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions
→Collaborate closely with product, design, and other engineering teams to scope work and ship improvements in user-facing features
→Document system architectures and decision rationale early and clearly
→Champion model and data quality, including dataset versioning, robust evaluation, and real-world performance tracking
→Mentor junior AI engineers and cross-functional teammates
→Stay up-to-date with emerging research and tools, bringing back relevant innovations

Requirements

✓A master's degree or above in Computer Science, Electrical Engineering or a related field
✓5+ years of experience building AI/ML systems in production environments
✓Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain
✓A solid understanding of LLMs for natural language processing applications
✓Strong software engineering foundations such as version control, unit/integration testing, CI/CD, and containerization
✓Experience working in product-focused teams, collaborating with designers, engineers, and PMs
✓Ability to reason about system behavior end-to-end, including model performance, latency, and observability
✓Clear, structured communicator, comfortable documenting and defending architectural decisions