About the Role
We are looking for a Senior Applied AI / ML Engineer to join our team and contribute to the research, development, and implementation of advanced AI and Machine Learning solutions.
In this role, you will work with traditional Machine Learning, Large Language Models (LLMs), Knowledge Graphs, and Agentic AI. You will explore new technologies, build proof of concepts, evaluate different approaches, and turn successful experiments into reliable, production-ready solutions.
We are looking for someone with strong Python and ML fundamentals, a hands-on approach to modern AI technologies, and a passion for research, experimentation, and innovation.
What You'll Do
- Research and experiment with emerging AI/ML technologies and frameworks.
- Design, develop, and implement AI/ML solutions using Python.
- Apply Machine Learning techniques and evaluate different models and approaches.
- Explore and implement LLM-based, agentic, and hybrid AI solutions.
- Work with Knowledge Graphs, ontologies, and semantic modeling.
- Build proof of concepts, evaluate results, and recommend suitable technical solutions.
- Support the transition of AI/ML experiments into scalable, production-ready applications.
- Apply MLOps/LLMOps practices for model tracking, versioning, deployment, and monitoring.
- Collaborate with Software Engineering, Data, Cloud/DevOps, QA, and Architecture teams.
- Communicate technical findings and share knowledge with internal teams and clients.
What We're Looking For
- Strong Python programming skills and experience writing production-quality code.
- Solid Machine Learning fundamentals, including classification, regression, clustering, and model evaluation.
- Experience with ML libraries and frameworks such as scikit-learn, Pandas/Polars, PyTorch, or similar.
- Practical experience with LLMs, embeddings, and foundation models, including the ability to compare and evaluate different approaches.
- Knowledge of Knowledge Graphs, ontologies, and semantic modeling, with experience using Neo4j, RDF/OWL, SPARQL, or similar technologies.
- Hands-on experience with Agentic AI and tool-using systems, with familiarity with Claude Code, GitHub Copilot, Cursor, or similar tools.
- Understanding of MLOps/LLMOps practices and experience with tools such as MLflow, Kubeflow, or similar.
- Strong R&D mindset, with the ability to independently research, experiment, build PoCs, and evaluate technical solutions.
- Excellent communication and collaboration skills, including the ability to explain complex technical concepts to different audiences.
- Excellent spoken and written English, including confidence in client-facing discussions and workshops.
Nice to Have
- Experience with RAG, semantic search, and vector databases.
- Experience with open-source/local models or model fine-tuning.
- Experience with cloud AI services, particularly Azure, AWS, or GCP.
- Familiarity with Docker, Kubernetes, and container-based AI workloads.
We appreciate the interest of all applicants. Please note that only those whose qualifications align closely with the position requirements will be contacted for the next steps in the selection process. - All applications will be handled with confidentiality.
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