pi-labs provides cutting-edge cybersecurity and intelligence solutions to governments and enterprises, helping them stay ahead of emerging cyber threats driven by the rapid adoption of AI. We specialize in developing advanced tools that safeguard digital ecosystems and ensure trust, safety, and authenticity.

At pi-labs, you’ll work with a team of passionate experts at the forefront of AI-powered security technologies. Join us to build impactful solutions, solve complex challenges, and contribute to protecting the digital world as it evolves.

About the Role

ownership

This role requires a combination of strong technical leadership, architectural-level thinking, and the ability to guide a cross-functional team in developing scalable, enterprise-grade AI solutions.

Key Responsibilities

Own the end-to-end AI technology strategy and roadmap for the product.
Lead design and development of AI/ML models and LLMs, and RAG pipelines.
Architect and optimize inference systems using Triton Inference Server and GPU-based deployments.
Drive model lifecycle management: training, fine-tuning, evaluation, versioning, monitoring, and continuous improvement.
Ensure production readiness of AI solutions including scalability, security, and reliability.
Collaborate with product, engineering, and business teams to translate requirements into technical deliverables.
Mentor and guide a team of AI engineers and researchers.
Stay ahead of emerging AI trends and evaluate cutting-edge technologies for integration.

Required Skills & Experience

8–10 years of total experience with at least 3 years in AI/ML product development.
Proven track record of taking AI-based products from concept to production.
Strong expertise in:
Deep Learning frameworks (TensorFlow, PyTorch)
Large Language Models (LLMs) - training, fine-tuning, prompt engineering
Retrieval-Augmented Generation (RAG) workflows
Triton Inference Server for scalable inference deployment
Hands-on experience with cloud platforms , on-premise deployments and GPU optimization.
Strong programming skills in Python, and proficiency in MLOps pipelines, containerization (Docker, Kubernetes).
Understanding of distributed training, vector databases (e.g., FAISS, Milvus, Pinecone), and model optimization techniques (quantization, pruning).
Excellent problem-solving skills with a product-oriented mindset.
Strong leadership qualities with experience in mentoring teams.

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