AI Recruitment

Ai

We’re living through the most thrilling inflection point in tech history. AI is accelerating at breakneck speed, transforming the world around us in real time and turning tomorrow’s possibilities into today’s reality.

As models get bigger and pipelines more complex, the talent you need is rare, technical, and in demand. From LLMs and multimodal systems to production-ready infrastructure, it’s no longer about finding someone qualified, you need someone who can lead from day one.

Whether you're pre-product or scaling globally, Impax delivers the engineers, scientists, and strategists who turn AI ambition into execution.

The Impax of Precision Hiring

We streamline hiring without sacrificing rigour, every profile is vetted for technical depth, mission alignment, and cultural fit. From transformers to diffusion models, we assess candidates with real-world, domain-specific fluency. Our talent pipeline includes research scientists, ML engineers, and AI leads from DeepMind, OpenAI, FAANG, and frontier startups building at scale.

Whether you're in stealth mode or scaling post-Series C, we align talent strategy with your product roadmap, engineering velocity, and technical debt, ensuring each hire accelerates delivery, not delays.

Key Roles We Hire For

AI Research Scientists

Experts in LLMs, Diffusion Models, Reinforcement Learning, and Multimodal systems. Often hold PhDs and contribute to cutting-edge AI breakthroughs in academia and industry.

AI Engineers

Production-focused engineers who build and scale AI-powered features, including model integration, fine-tuning pipelines, vector search, and inference infrastructure.

Machine Learning Engineers

Design and implement model training workflows, feature stores, performance optimization, and evaluation pipelines using frameworks like PyTorch and TensorFlow.

MLOps Engineers

Experts in LLMs, Diffusion Models, Reinforcement Learning, and Multimodal systems. Often hold PhDs and contribute to cutting-edge AI breakthroughs in academia and industry.

NLP Engineers

Experts in LLMs, Diffusion Models, Reinforcement Learning, and Multimodal systems. Often hold PhDs and contribute to cutting-edge AI breakthroughs in academia and industry.

Data Scientists

Work on forecasting, experimentation, A/B testing, causal inference, customer segmentation, and turning data into actionable product or business insights.

AI Product Managers

Lead AI-driven product development with a strong understanding of the ML lifecycle, model feasibility, data dependencies, and strategic roadmap ownership.

Responsible AI / AI Ethics Specialists

Focus on fairness, interpretability, explainability (XAI), and regulatory compliance. Skilled in frameworks like SHAP, LIME, and Model Cards.

AI Infrastructure Engineers

Design and scale ML infrastructure including distributed training environments, inference APIs, container orchestration, and GPU optimization using tools like Ray or Triton.

Applied AI Scientists

Bridge research and real-world applications. Fine-tune foundation models, implement transfer learning, and adapt LLMs for production-grade use cases.

Generative AI Specialists

Experts in prompt engineering, retrieval-augmented generation (RAG), model alignment, and GenAI use cases across content, code, and multimodal interfaces.

Computer Vision Engineers

Build and optimize vision-based models for object detection, image segmentation, OCR, and 3D modelling using tools like OpenCV and YOLO.

Director / Head of AI

Lead AI teams across research, infrastructure, hiring, and compliance. Often responsible for aligning AI strategy with product and business outcomes.

Fractional AI Advisors

Senior consultants or operators who embed part-time to advise on model architecture, scaling, team strategy, or investor-facing technical guidance.