Applied Ai Researcher
15 hours ago
About QpiAI
QpiAI is a deep-tech company pioneering the convergence of AI and Quantum Computing. Our mission is to solve some of the world’s most complex challenges by building intelligent systems with real-world impact across domains such as Drug Discovery, Decision Intelligence, Chip Design, and Quantum Simulation. With QpiAI Pro and a research-first mindset, we aim to push the boundaries of what intelligent systems can achieve.
About the Role
We are seeking a highly skilled and motivated Applied AI Researcher to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions.
Key Responsibilities
Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration
Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains
Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases
Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness
Explore post-training optimization, fine-tuning, and domain adaptation methods
Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions
Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities
Document and communicate findings through technical reports, presentations, and publications
Required Qualifications
Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field
4+ years of experience in applied AI research or equivalent industry R D experience
Strong foundations in optimization, probability, and linear algebra
Expertise in Python and frameworks like PyTorch or JAX
Experience with RL and post-training methods (e.g., SFT, DPO, RLHF)
Proficiency in building and aligning small language models (SLMs), including reasoning-specific models
Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks
Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node)
Experience in designing evaluation metrics and performance analysis methodologies
Preferred Experience
Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.)
Exposure to multimodal models and VLMs
Experience with open-ended systems and emergent behavior in agent-based learning
Background in computational science (chemistry, physics, EE, or applied math)
Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow
Experience with domain adaptation, interpretability, and model optimization for deployment
Contributions to open-source AI projects
Expertise in building GPU-accelerated pipelines and optimizing inference at scale
What We Offer
Access to high-performance computing resources
A collaborative, intellectually stimulating environment
Autonomy to explore novel ideas aligned with our mission
Competitive salary, benefits, and opportunities for growth
Pay: ₹2,500,000.00 - ₹3,000,000.00 per year
Work Location: In person
**Speak with the employer**
+91 9008078505
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