causaly - Senior AI Engineer

• · Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver measurable impact. • · Apply strong software engineering principles, such as modularity, testing, code reviews, CI/CD and observability, to ensure AI systems are reliable, maintainable, production-ready and can be readily adapted to future developments. • · Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance. • · Collaborate closely with product, design, and other engineering teams to scope work, align on success metrics, and incrementally ship improvements in user-facing features powered by AI. • · Document system architectures and decision rationale early and clearly, enabling alignment across teams and accelerating onboarding and iteration. • · Champion model and data quality, including dataset versioning, robust evaluation, fairness/bias assessment, and real-world performance tracking. • · Mentor junior AI engineers and cross-functional teammates, sharing best practices in modelling, coding, maintaining and integrating product features, and helping grow a high-trust, high-performance team culture. • · Stay up-to-date with emerging research and tools, distilling key insights and bringing back relevant innovations to elevate team capabilities and product opportunities. • · Contribute to a culture of knowledge sharing, through company-wide Slack channels, Show and Tell presentations and technical deep-dives. • WHAT EXPERIENCE YOU’LL NEED TO BE SUCCESSFUL • · 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, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring. • · Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. • · A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine-tuning. • · Strong software engineering foundations such as version control, unit/integration testing, CI/CD, containerization plus a mindset of building for reliability and scale. • · Experience working in product-focused teams, collaborating with designers, engineers, and PMs, to scope and ship AI features iteratively • · Ability to reason about system behavior end-to-end, including model performance, latency, and observability, and how these impact user experience. • · Clear, structured communicator, comfortable documenting and defending architectural decisions and engaging in thoughtful technical debate. • NOT REQUIRED, BUT IT’S A PLUS IF YOU ALSO HAVE: • · Experience with MLOps/LLMOps frameworks and best practices • · A PhD in Computer Science, Electrical Engineering or a related field. • · A background or work experience in life-sciences, health-tech, or other data-intensive domains