Data Science Engineer

Job description

. As a Data Scientist specializing in generative AI, you will architect and implement advanced artificial intelligence solutions, focusing on the creation and optimization of predictive and prescriptive models to drive meaningful improvements in user engagement and operational processes for streaming services. Your responsibilities will include end-to-end stewardship of the machine learning lifecycle, from identifying analytical opportunities and designing robust algorithms to deploying scalable systems and conducting ongoing performance monitoring and iterative refinement.

Key Responsibilities:

• Data Scientist (DS-3) with generative AI expertise to contribute to the development and implementation of advanced AI solutions
• Create and maintain optimal predictive and prescriptive data models.
• Design and deploy ML solutions that will help improve the user experience and operational efficiency across streaming products.
• Own the ML lifecycle end-to-end: from problem framing, feature engineering, and model training through to inference, monitoring, and iteration.
• Drive technical excellence by defining modeling standards, mentoring other data scientists, and advocating best practices in reproducibility, experimentation, and causal inference.
• Advance foundational ML capabilities (e.g., scalable training/inference pipelines, reusable modeling frameworks, evaluation/monitoring systems).

Required Skills:

• Strong programming skills: Python (primary), plus experience with .Net is a plus.
• Expert knowledge of ML frameworks: PyTorch, TensorFlow.
• Strong understanding of modern ML approaches and apply to large datasets to support business.
• Hands-on experience with NLP, LLMs, deep learning.
• Experience deploying ML models in production at scale.
• Expert in vector DBs, design and modelling like PostgreSQL
• Model Development: Build and tune generative AI models using frameworks like LangChain and LangGraph with proper regularization techniques
• Response Generation: Develop components for generating structured responses by combining AI and ML models.
• Assemble large, complex data sets that meet functional/non-functional business requirements.
• Familiarity with vector databases, RAG systems, and fine-tuning LLMs.
• Strong experience with chatbot implementations and tuning the chat agent responses.