Data Scientist – Machine Learning & Generative AI

SUMMARY:
Data Scientist – Machine Learning & Generative AI

My client is not looking for someone who just plugs into APIs.
They want a builder—a mind that thrives on solving complex problems at the frontier of AI using code, mathematics, and raw creativity.
This is your chance to shape the next generation of conversational AI, transcription systems, and intelligent assistants—from the ground up.

POSITION INFO:

What You’ll Work On

• Building Large Language Model (LLM) solutions (GPT, LLaMA, Mistral, Claude, Falcon—but tuned for real-world business impact).
• Training and fine-tuning transformer architectures (BERT, T5, GPT-3/4, etc.) on domain-specific datasets.
• Designing speech-to-text pipelines (Whisper, wav2vec, Hugging Face speech models).
• Creating conversational AI systems that actually talk and think—beyond simple FAQ chatbots.
• Developing retrieval-augmented generation (RAG) pipelines with vector databases (Pinecone, Weaviate, FAISS, Milvus).
• Owning the end-to-end ML lifecycle: data wrangling, training, evaluation, deployment (Docker, Kubernetes, AWS/Azure/GCP).

What We’re Looking For

• 2–6 years’ experience in Data Science / ML (MSc or PhD preferred in AI, CS, Data Science, Applied Math, or similar).
• Strong grounding in deep learning & NLP (transformers, embeddings, attention mechanisms).
• Hands-on experience fine-tuning or deploying LLMs and transcription models.
• Solid coding skills in Python, with experience in PyTorch, TensorFlow, Hugging Face.
• Exposure to MLOps, deployment pipelines, and cloud platforms.
• A true problem-solver and innovator—someone who loves building new things, not just wrapping tools together.

Why Join?

• Be part of a team solving real problems with cutting-edge AI.
• Work in an environment that values experimentation, bold ideas, and real impact.
• Build systems that will be used every day—not just prototypes that collect dust.
• Hybrid setup with flexibility and growth opportunities.