Job summary
The Senior AI/ML Engineer is a hands-on technical leader who designs, builds, and ships production-grade AI solutions for the Ezderm platform - a dermatology-focused electronic health record (EHR) and practice management system used by clinics to run their day-to-day care. Your work puts AI directly into the hands of clinicians, improving how they document, decide, and operate. The primary focus is agentic AI systems and tooling - LLM-based agents, multi-agent orchestration, and RAG workflows - that automate clinical and administrative workflows, owned end-to-end, from rapid prototype to reliable, scalable production. This is a full senior AI/ML role: while agentic and GenAI work is the day-to-day focus, you bring a solid foundation across classical machine learning, data science, and NLP, and can apply the right approach as our needs evolve.
You will join our Architecture team in an early and foundational role, helping shape our AI engineering practice as it grows, while setting technical direction and mentoring others.
Responsibilities:
- Agentic Systems & Tooling: Designs, builds, and ships production-grade agentic AI systems - LLM-based agents, tool/function calling, multi-agent orchestration, and RAG workflows that automate clinical and administrative workflows safely and reliably;
- GenAI Application Development: Builds LLM integrations, RAG pipelines, vector search, and retrieval systems, taking them from rapid prototype to scalable, industrialized deployment;
- Evaluation & Quality: Develops evaluation suites for prompt testing, output validation, and monitoring of model drift, factual grounding, and response quality;
- Data Pipelines: Designs Python-based pipelines to clean, validate, and transform raw data into reliable, model-ready datasets for training and inference;
- Applied ML & Modeling: Builds, trains, and evaluates ML models (classification, regression, clustering, information extraction) where they are the right tool, and selects the most suitable approach for each problem;
- Technical Leadership: Sets technical direction, defines best practices, reviews code and designs, and mentors engineers; partners with product stakeholders to assess feasibility and turn business challenges into experiments;
- Ethical & Compliant AI: Ensures AI/ML solutions comply with medical regulations and ethical data practices.
Key qualifications:
- BSc or MSc in Computer Science, Mathematics, Data Science, or equivalent practical experience;
- 5+ years of professional experience in machine learning or data science, including production AI/ML systems;
- Strong proficiency in Python, SQL, along with the modern AI/ML ecosystem (e.g. NumPy, pandas, scikit-learn, PyTorch or TensorFlow);
- Solid foundation in classical machine learning and data science - classification, regression, clustering, feature engineering, model evaluation, and statistics (e.g. neural networks, random forests, SVM, k-means);
- Working knowledge of NLP and transformer models (e.g. BERT and variants) for tasks such as text classification, entity/relationship extraction, and information retrieval;
- Experience integrating LLM provider APIs (e.g. OpenAI, Anthropic, Azure OpenAI) and serving models via FastAPI or similar;
- Proven experience building agentic and LLM-based applications with frameworks such as LangChain, LangGraph, or LlamaIndex, including prompt engineering, tool/function calling, and multi-agent orchestration;
- Strong grasp of RAG patterns, embeddings, and vector databases (e.g. pgvector, Pinecone, Weaviate, OpenSearch, or Elasticsearch);
- Experience with AWS cloud, Docker/Kubernetes, CI/CD, and MLOps/observability tooling (e.g. MLflow, LangSmith/LangFuse, Weights & Biases);
- Working knowledge of relational databases (e.g. PostgreSQL) and data processing for model-ready datasets;
- Security and observability awareness, including best practices for monitoring, compliance, and reliability in AI systems;
- Demonstrated ability to lead technical initiatives end-to-end and mentor other engineers;
- Excellent communication and interpersonal skills;
- Good command of the English language, both written and spoken.
Nice to have:
- Experience in healthcare, medical, or other regulated domains (e.g. HIPAA);
- Familiarity with healthcare data standards or medical billing/coding and revenue workflows;
- Experience with MLOps tooling and model monitoring in production;
- Experience with data platforms such as Databricks or Spark for large-scale data processing;
- Experience with semantic search, recommendation systems, or fine-tuning of transformer models;
- Experience working with distributed systems and microservices architectures.
We offer:
- Highly talented and professional team;
- Optional work from home or office (you decide);
- Flexible working hours;
- Work on our own product;
- Private health insurance;
- Sport activities refund;
- Social activities and a very friendly working environment.
If you believe that you are the right candidate for this position, you can apply by sending us your CV.
All applications will be considered with full confidentiality, and only candidates who are shortlisted will be contacted.
