Senior AI/ML Consultant

What we offer

Possibility to be part of growing one of the most successful tech consultancies in the industry.

Diverse client landscape, including some of the most innovative tech companies & exciting projects with lots of room for professional development.

Access to an international network of 2,000+ highly talented individuals.

An experienced mentor and a professional coach to guide you throughout your career.

An international & diverse working environment with a central and modern office space.

Competitive and transparent salary model with equal pay regardless of the assignment, biannual salary reviews, and attractive benefits (e.g. company shares, Deutschlandticket, parental benefits & much more).

The freedom to shape your own path in terms of clients, domains, and roles, supported by a global community.

Access to Netlight's Edge network with its competence cells, conferences, and a culture where sharing knowledge is as valued as acquiring it. You are encouraged to contribute to Netlight's thought leadership within Data & AI.

Minimum qualifications

Master's Degree in Engineering or Technology (e.g., Computer Science, Machine Learning, Mathematics, Statistics, or similar).

Verbal and written fluency in English.

2–4 years of full-time work experience in machine learning engineering, applied AI, or a closely related field. Experience working in agile product or delivery teams, gained after completing your Master's degree.

Strong hands-on experience with the full ML lifecycle: data preparation, feature engineering, model development, evaluation, deployment, and monitoring.

Practical experience building and deploying solutions on at least one major cloud platform (AWS, Azure, or GCP), including managed ML services (e.g., SageMaker, Vertex AI, Azure ML).

Hands-on experience with LLMs and generative AI, including prompt engineering, RAG architectures, and integrating foundation model APIs into production systems.

Experience with MLOps practices and tools, including experiment tracking, model registries, CI/CD for ML, and model serving infrastructure.

Proficiency in Python and relevant ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain, or LlamaIndex).

Demonstrated ability to collaborate with diverse stakeholders — including data engineers, product owners, analysts, and business leaders — in client-facing settings.

Preferred qualifications

Experience designing agentic AI systems, including tool use, orchestration frameworks, and multi-agent architectures.

Depth in responsible AI and governance, including fairness, explainability, bias detection, and AI risk frameworks.

Experience fine-tuning or instruction-tuning foundation models (e.g., LoRA, RLHF, PEFT).

Familiarity with vector databases and semantic search infrastructure (e.g., Pinecone, Weaviate, pgvector, Qdrant).

Background in NLP, computer vision, or time-series forecasting in applied production settings.

Experience with data and AI platform architecture, including feature stores, data lakes, and lakehouse patterns.