Data Science Manager

Summary

Join Netomi AI, a leading AI company backed by top investors, as a Data Science Manager. You will lead a team of data scientists, driving the design, development, and deployment of advanced AI models. This high-impact role involves defining and executing the AI/ML strategy, collaborating with various teams, and overseeing model training and fine-tuning. You will also focus on scalability, ML Ops, and AI governance. The ideal candidate possesses extensive experience in data science, NLP, deep learning, and LLM fine-tuning, along with strong leadership and communication skills. This is a fast-paced, high-impact role within a dynamic and growing team.

Requirements

• 5+ years of experience in Data Science, with a focus on NLP, Deep Learning, or LLMs
• 3+ years of experience managing data science teams
• Strong Python programming skills and experience with ML libraries (TensorFlow, PyTorch, sci-kit-learn)
• Expertise in LLMs, deep learning, NLP, and chatbot development
• Strong knowledge of statistical modelling, probability, and experimental design
• Experience with LLM fine-tuning, RAG, LoRA, and transformer models (GPT, BERT, etc.)
• Ability to rapidly comprehend and implement research papers in AI/NLP
• Experience in ML Ops, model deployment, and optimization techniques
• Strong communication skills to collaborate with technical and non-technical stakeholders

Responsibilities

• Lead, mentor, and scale a high-performing team of Data Scientists
• Define and execute the AI/ML strategy, aligning it with business objectives and product goals
• Collaborate with engineering, product, and business stakeholders to deliver AI-driven solutions
• Architect and deploy conversational AI models, including LLM fine-tuning using LoRA (Low-Rank Adaptation) and other parameter-efficient tuning techniques
• Develop Multimodal AI models (MLLMs) integrating text, images, and other data sources
• Develop NLP/NLU models optimized for customer service and personalization
• Optimize AI/ML pipelines for speed, scalability, and cost-efficiency
• Design AI governance frameworks, including model monitoring, bias mitigation, and explainability
• Oversee data collection, annotation, and preparation for model training
• Implement state-of-the-art fine-tuning methods to enhance LLM performance
• Leverage Retrieval-Augmented Generation (RAG) and knowledge distillation to enhance AI capabilities
• Work with engineering teams to deploy models using scalable ML Ops practices
• Optimize data pipelines, including RDS, Elasticsearch, and vector databases for AI applications
• Ensure continuous model monitoring, retraining, and performance optimization
• Implement AI model governance, compliance, and risk mitigation strategies
• Develop ethical AI frameworks for fairness, transparency, and security
• Ensure PII (Personally Identifiable Information) masking and anonymization for privacy protection

Preferred Qualifications

• Familiarity with vector databases, RDS, and Elasticsearch for AI applications
• Knowledge of Multimodal AI, Speech Recognition, and NLG (Natural Language Generation)
• Background in AI security, model governance, and bias mitigation strategies