About the company
At knok, we dare to lead and humanise the digital transformation of healthcare. We envision a world where everyone has timely access to quality healthcare through digital technology, creating a more equal society. Through a Digital Front Door strategy, knok connects patients, providers and healthcare professionals in one place. Our API-first white-label platform enables a continuous, engaging and personalised healthcare experience for all conditions through a cutting-edge Patient Journey Engine.
Responsibilities
- Contribute to designing, building, evaluating, shipping, and improving the product through AI/ML development.
- Work alongside the Product, Data and Engineering teams to implement AI/ML-powered features.
- Develop initiatives across the AI stack (prompt engineering, RAG, fine-tuning, agentic workflows), prototype fast, and push to production.
- Collaborate with Data Engineering team to develop the datasets required to build and evaluate models.
- Read research in the health AI space and translate research advancements into tangible product features.
Requirements
- Bachelor's or Master’s Degree in Computer Science, Data Science, Mathematics, Physics, or a related field.
- 2+ years of professional experience as a ML engineer, applied researcher, or software engineer with a focus on ML systems.
- Experience taking applied ML initiatives from early experimentation and prototyping through evaluation, deployment, and iteration in production.
- Strong foundations in machine learning, including generative AI.
- Experience deploying ML/AI services in a cloud environment.
- Ability to communicate technical concepts to non-technical stakeholders.
Nice to have:
- Track record of building and deploying production-grade software in healthcare.
- Experience with model training and observability platforms (e.g., Vertex AI, SageMaker, WandB, MLFlow, LangSmith, Langfuse).
- Experience with vector databases (e.g., ChromaDB, Pinecone).
- Experience working with analytical databases (BigQuery, Redshift, Snowflake).
Conditions
- Recruitment stages: People Interview, Hiring Manager Interview, Case Study, Final Interview.
- We know that great candidates don't always fit a rigid checklist. If you don't meet every single requirement but are passionate about AI and healthcare, we strongly encourage you to apply!