Machine Learning Data Scientist

This is your opportunity to work at the cutting edge of Generative AI, data engineering, and large-scale deployment, while collaborating with world-class teams to shape the future of intelligent systems.

Key Responsibilities:

• Develop & Enhance AI Models: Create, refine, and implement Generative AI systems and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and Llama-Index.
• Data Engineering: Build scalable data workflows, manage ETL processes, and integrate both structured and unstructured data for AI-driven applications.
• Production Deployment: Deliver models into production, collaborating with DevOps to ensure performance across cloud and on-prem environments.
• Collaborate Across Teams: Work closely with Engineers, product owners, and business leaders to ensure AI solutions drive measurable value.
• Innovate & Research: Stay current with emerging architectures, frameworks, and methodologies, contributing to innovation and thought leadership.

Job Experience and Skills Required:

• Education:
• Degree in Computer Science, Data Science, Machine Learning, or a related field.
• Experience:
• 3+ years of professional experience in AI/ML, including at least 12 years in Generative AI.
• Practical experience with deep learning frameworks (TensorFlow and PyTorch) and generative AI libraries.
• Familiarity with cloud platforms (AWS, GCP, and Azure) and container technologies (Docker and Kubernetes).
• Skills:
• Strong programming ability in Python and SQL, plus experience with libraries like Pandas and NumPy.
• Solid understanding of machine learning algorithms, neural networks, and generative models.
• Knowledge of large-scale data storage (Hadoop, Spark, and Vector databases).
• Understanding of MLOps practices, including model lifecycle management, monitoring, and retraining.

Apply now!

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