Data Engineer – Applied ML

About the role

We are looking for a Data Engineer with a strong applied machine‑learning focus to join the R&D team at Similarweb. You will turn massive product, brand and category data from retailers and marketplaces into a unified, trusted view, enabling our Retail Intelligence products to serve billions of records.

Key responsibilities

• Design and build LLM‑powered and ML‑based pipelines that classify, normalize, structure and match product, brand and category data.
• Develop agentic workflows (e.g., LangGraph) that automate complex data tasks end‑to‑end.
• Select appropriate techniques—LLMs, embeddings, fine‑tuned models, classical classifiers or rule‑based systems—balancing accuracy, cost and latency.
• Scale solutions to run efficiently over billions of records using Spark, Databricks and cloud infrastructure.
• Build evaluation frameworks, ground‑truth datasets, labeling processes and monitoring pipelines.
• Take prototypes to production and own the pipelines after launch.
• Collaborate with product, data scientists and other R&D teams to define requirements and best practices.

Required profile

• B.Sc. or M.Sc. in Computer Science, Data Science, Mathematics or a related field.
• 4+ years of hands‑on experience as a data engineer, ML engineer or data scientist with production‑grade solutions.
• Strong Python programming skills and ability to write production‑quality code.
• Experience building LLM‑based applications in production (prompt engineering, RAG, embeddings, evaluation).
• Solid understanding of text classification and NLP methods, both classical and modern.
• Proficiency processing large‑scale data with Spark/PySpark, Databricks or similar on AWS or another cloud.

Required skills

• Python
• LLM provider APIs (OpenAI, Anthropic, etc.)
• LangGraph or LangChain
• Hugging Face models and vector stores
• Spark / PySpark
• Databricks
• AWS or comparable cloud platforms
• Text classification, NLP, embeddings, Retrieval‑Augmented Generation

What we offer

• Work on a leading digital intelligence platform used by global brands.
• Opportunities to bring big ideas to life with open dialogue and resources.
• Competitive compensation, benefits and regular team outings.
• Career development programs, coaching and learning resources.
• Inclusive culture that values diversity and authentic self‑expression.