Overview

Technical leadership in the development and deployment of generative AI solutions, including large language models (LLMs), ensuring alignment with business objectives and industry best practices. Architects scalable data and ML pipelines.

Responsibilities

• Provide technical leadership in building generative AI solutions
• Architect scalable data and machine learning pipelines
• Lead cross-functional teams of data scientists, engineers, and product managers
• Drive project timelines, resource allocation, and delivering impactful AI-driven products and solutions
• Champion innovation by staying ahead of latest advancements in AI
• Mentor team members to elevate the organization’s data science capabilities
• Manage delivery of data science insights using complex algorithms and methods
• Develop new sophisticated algorithms and improve existing machine learning techniques
• Make business recommendations based on data that drive better decisions
• Collaborate with relevant business areas to identify projects and understand requirements

Qualifications

• 12+ years’ experience in machine learning, data mining, predictive modeling, statistical modeling, large-scale data acquisition, transformation, and cleaning
• Experience in data wrangling, visualization, and modeling in Python
• In-depth knowledge of deep learning methods including RNNs, LSTMs, recursive neural networks, autoencoders
• Experience with ML/NLP algorithms (supervised and unsupervised learning)
• Experience with machine learning frameworks: sci-kit-learn, Keras, TensorFlow, MXNet, PyTorch, MLlib
• Experience with Hugging Face Transformers and other open-source NLP/NLG modules
• Experience in generative LLM fine-tuning and prompt engineering
• Strong programming skills in Python
• Knowledge of containerization platforms like Docker is a plus
• Bonus if you have experience with Git and modern software development workflow

Nice to have

• Strategic consulting experience
• Leadership and collaboration capabilities across multi-office/team settings
• Business communication skills for technical/non-technical interactions

Education

• Bachelor/Master/PG/Ph.D in Artificial Intelligence, Analytics, Data Science, Computer Science, Engineering, Information Technology, Social Sciences or related fields preferred