Job Title

Compensation: INR 2 crore per year including incentives Strictly please do NOT apply if you have not built 1-2 SLM for clients before.Multiplier AI is a leader in AI accelerators for life sciences and is due for listing.About the RoleWe are seeking a seasoned and forward-thinking Head for AI and SLM to spearhead Small Language Model (SLM) implementation projects across enterprise and industry-specific use cases. This is a high-impact leadership role that combines deep technical expertise with strategic consulting to deliver scalable, efficient, and secure SLM solutions.Key ResponsibilitiesLead end-to-end design and deployment of Small Language Models (SLMs) in production environments.Define architecture for on-device or private-cloud SLM deployments, optimizing for latency, token cost, and privacy.Collaborate with cross-functional teams (data, MLOps, product, security) to integrate SLMs into existing systems and workflows.Select and fine-tune open-source or custom SLMs (e.g., Phi-3, TinyLlama, Mistral) for targeted business use cases.Mentor engineering and data science teams on best practices in efficient prompt engineering, RAG pipelines, quantization, and distillation techniques.Act as a thought partner to leadership and clients on GenAI roadmap, risk management, and responsible AI design.Required Skills & ExperienceProven experience in deploying Small Language Models in production (not just large-scale LLMs). this is essential do not apply if not done itStrong understanding of transformer architecture, tokenizer design, and parameter-efficient fine-tuning (LoRA, QLoRA).Hands-on with HuggingFace, ONNX, GGUF, and GPU/CPU/edge model optimization techniques.Experience integrating SLMs into real-world systems—mobile apps, secure enterprise workflows, or embedded devices.Background in Python, PyTorch/TensorFlow, and familiarity with MLOps tools like Weights & Biases, MLflow, and LangChain.Strategic mindset to balance model performance vs. cost vs. explainability.Preferred QualificationsPrior consulting experience with AI/ML deployments in pharma, finance, or regulated sectors.Familiarity with privacy-preserving AI, federated learning, or differential privacy.Contributions to open-source LLM/SLM projects.What We OfferLeadership in shaping the future of lightweight AI.Exposure to cutting-edge GenAI applications across industries.Competitive compensation and equity options (for permanent roles).