Principal Data Scientist - AI & ML

Lead the design and implementation of advanced machine learning and generative AI models for large-scale AI projects.

Collaborate with data scientists and software engineers to build and deploy scalable, production-grade ML and GenAI solutions.

Drive the end-to-end deployment of machine learning and GenAI models, ensuring seamless integration into production environments and monitoring their performance post-deployment.

Conduct in-depth data analysis and feature engineering to extract meaningful insights from complex, high-volume datasets.

Optimize and fine-tune machine learning and generative AI models to enhance accuracy, efficiency, and performance.

Stay current with the latest advancements in machine learning, generative AI (such as LLMs, diffusion models, and GANs), and apply them to improve existing systems.

Work with cross-functional teams to define project requirements and deliver high-quality, innovative AI solutions on schedule.

Requirements:

Bachelor’s or master’s degree in computer science, Data Science, or a related field.

7–10 years of professional experience in data science, machine learning, or AI-related roles.

Hands-on experience with AWS Cloud Stack.

Expert-level proficiency in Python and experience with machine learning and GenAI libraries such as Hugging Face Transformers, or scikit-learn.

Strong coding skills, including robust machine learning code and version control (preferably Git).

Experience across the project lifecycle, from business analysis to deployment.

Experience working with databases (e.g., SQL).

Deep understanding of machine learning, generative AI (LLMs, NLP, GANs).

Proven track record with large-scale machine learning projects, and distributed computing frameworks

Skilled in data manipulation, preprocessing, and feature engineering.

Strong analytical and problem-solving abilities.

Excellent communication and teamwork skills.