Key Responsibilities:
* Design, develop, and deploy machine learning models with a focus on generative AI (e.g., LLMs, diffusion models, GANs).
* Apply generative AI for use cases such as text generation, summarization, classification, synthetic data creation, and intelligent assistants.
* Collaborate with data engineers and ML engineers to build scalable pipelines.
* Lead experimentation and validation of new GenAI models and tools.
* Support prompt engineering and fine-tuning of foundation models where applicable.
* Ensure compliance with data privacy, security, and ethical AI standards.
* Present findings and models to stakeholders in clear, actionable formats.
Required Skills & Experience:
* 5+ years of experience as a Data Scientist or ML Engineer.
* Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain).
* Deep knowledge of foundational models, LLMs (GPT, Claude, LLaMA, Mistral, etc.), and associated tooling.
* Hands-on experience with fine-tuning or customizing generative AI models.
* Solid grounding in classical ML (supervised/unsupervised learning), statistics, and NLP.
* Familiarity with deploying models via REST APIs, Docker, and cloud services (e.g., AWS, Azure, GCP).
* Experience working with enterprise data in complex environments (structured/unstructured).
* Strong problem-solving skills and ability to communicate technical concepts to non-technical audiences.
Nice to Have:
* Experience with vector databases (e.g., FAISS, Pinecone, Weaviate).
* Familiarity with GenAI enterprise platforms (e.g., OpenAI, Azure OpenAI, Cohere, Anthropic).
* Experience in regulated industries (e.g., healthcare, finance, public sector).
* Knowledge of European data protection regulations (e.g., GDPR).