We are looking for a Data Science Manager to drive the design, development, and deployment of advanced AI models. This role focuses on driving the AI & Product roadmap on the following areas:
LLM Fine-tuning (LoRA & other efficient tuning techniques).
Multimodal AI models integrating text, images, and structured data.
NLP/NLU-based models for customer support automation and personalization.
AI governance frameworks (model monitoring, bias mitigation, explainability).
Scalability & ML Ops, optimizing inference pipelines for production.
This is a high-impact research & development leadership role that will require close collaboration with engineering, product, and business teams to integrate AI innovations into Netomi s offerings.
Key Responsibilities:
Leadership & Strategy - 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.
AI/ML Research & Development - Architect and deploy conversational AI models, including LLM fine-tuning using LoRA (Low-Rank Adaptation) and other parameter-efficient tuning techniques. Multimodal AI models (MLLMs) integrating text, images, and other data sources. 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.
Model Training & Fine-Tuning - 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.
Scalability & ML Ops - 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.
AI Governance & Security - 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.
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.
Experience working with a startup is strongly preferred. We need someone who can thrive in a fast-moving, high-impact environment, driving AI initiatives from concept to production at scale
Good-to-Have (Bonus) Skills:
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.