AI/ML Senior Engineer

Our client is a rapidly growing tech company operating at the intersection of cybersecurity and sustainability. They are developing an innovative platform that enables organizations around the world to assess, monitor, and manage cybersecurity risks across their entire supply chain. By combining cutting-edge technology with deep domain expertise, the platform helps businesses ensure compliance with global cybersecurity standards and build more resilient, trustworthy partnerships. The team works in a collaborative, agile environment, and is passionate about delivering secure, scalable, and impactful solutions to clients in diverse industries.

Your Impact:

As a Senior AI/ML Engineer, you’ll play a key role in shaping and building our product’s AI backbone. You’ll work across the entire AI stack — from model research and development to cloud-based deployment and infrastructure management.

You’ll have ownership and influence over the AI roadmap, architecture, and implementation of intelligent solutions such as RAG pipelines, agentic workflows, and knowledge graph-enhanced systems.

What You Will Do

Architect AI Solutions

🔹Design and implement end-to-end AI/ML architecture (data pipelines, model serving, tech stack).

🔹Select models, tools, and frameworks based on metrics and use cases.

🔹Collaborate with engineers to integrate AI microservices into the core application.

Build Scalable AI Services

🔹Train, evaluate, and deploy ML models for features like document intelligence and semantic search.

🔹Own the full AI workflow: from structured/unstructured data prep to production deployment.

🔹Build robust microservices and APIs to serve ML models at scale.

🔹Set up and manage CI/CD pipelines for model lifecycle automation.

🔹Write clean, tested, maintainable code and monitor features in production.

Solve Practical ML Problems

🔹Apply NLP and ML to extract insights from cybersecurity documents.

🔹Build RAG-based systems for semantic search and Q&A.

🔹Work with text, tables, and visuals — explore multi-modal approaches.

🔹Use advanced prompt engineering and LLM evaluation techniques.

Establish Best Practices

🔹Help define standards in MLOps, model evaluation, and responsible AI.

🔹Conduct code reviews and mentor teammates.

🔹Share knowledge through workshops and discussions.

Research & Collaborate

🔹Stay up to date with NLP and document AI (e.g., knowledge graphs, advanced RAG).

🔹Collaborate with the CTO and product team to define the AI roadmap.

🔹Translate business needs into technical solutions.

Requirements

🔸8+ years in software development with a strong track record in scalable, production-grade systems.

🔸5+ years of hands-on AI/ML experience in real-world products.

🔸Deep knowledge of algorithms, data structures, and practical ML concepts.

🔸Expert in Python or similar, and familiar with key ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).

🔸Experience with NLP, including transformer models like BERT/GPT and information retrieval techniques (RAG, semantic search).

🔸Understanding of LLMs, fine-tuning, prompt engineering, and their limitations.

🔸Strong experience with structured/unstructured data, and capable of building and organizing datasets.

🔸Fluent English and excellent communication skills.

🔸A proactive, ownership-driven mindset and ability to thrive in a fast-paced, collaborative environment.

Nice to Have:

🔹Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field.

🔹Experience with transformer models (e.g. BERT, GPT), RAG, semantic search.

🔹Background in Document AI, multi-modal models, knowledge graphs.

🔹Familiarity with cloud platforms (especially Azure), DevOps pipelines, and SQL/NoSQL databases.

🔹Familiarity with CI/CD, MLOps tools (e.g., Azure DevOps, GitHub Actions), and microservice-based APIs.

🔹Awareness of security and compliance risks in AI systems.

What we offer

🔸 Personal development and career advancement opportunities

🔸 A vibrant, innovative, value-based, international work environment

🔸 Training budget

🔸 Private medical care

🔸 Co-financing of the sports card

Remote work, but if you're interested, working from the office is also an option.