AI Engineer II

Gopuff

72d • $175,000 - $220,000

About The Position

We are building the next generation of hyper-personal AI systems that fundamentally transform how humans interact with businesses. Led by our Chief AI Scientist, the Personal Superintelligence Lab at Gopuff develops cutting-edge agentic AI solutions that reason about complex user contexts, preferences, and real-world constraints to deliver superhuman performance in personalized shopping assistance. You will advance the state-of-the-art in prediction, alignment, grounding, and multi-agent orchestration while deploying these breakthroughs at massive scale.

Requirements

• MSc or PhD in Computer Science, Machine Learning, or equivalent research experience with significant contributions to AI/ML literature.
• Established experience in large-scale machine learning research with demonstrated impact on real-world systems.
• Deep expertise in transformer architectures, large language models, and modern pre- and post-training paradigms.
• Mastery of advanced fine-tuning techniques including LoRA/QLoRA, adapter methods, and parameter-efficient transfer learning.
• Research experience with agentic AI frameworks, multi-agent systems, and declarative programming approaches.
• Strong systems engineering capabilities with PyTorch, distributed training, and cloud-native ML infrastructure.
• Track record of publications in top-tier venues or equivalent industry impact.
• Commitment to responsible AI development and alignment research.

Nice To Haves

• Research background in reinforcement learning, multi-agent systems, or decision theory.
• Experience with formal verification, program synthesis, or automated reasoning.
• Contributions to open-source AI frameworks or foundational model development.
• Background in cognitive science, human-computer interaction, or behavioral economics.
• Experience with privacy-enhancing technologies, federated learning, or on-device AI.

Responsibilities

• Own core components of instant shopping personal intelligence—context engineering, grounding, alignment, and serving.
• Design context engineering strategies and real-time retrieval.
• Build SFT pipelines and implement reinforcement learning from human feedback (RLHF) and verifiable rewards (RLVR) using GRPO/GSPO.
• Use relevant APIs for data augmentation and ship low-latency, reliable inference with strong observability and safety.
• Run experiments end-to-end and deliver production models that drive measurable lifts in business KPI under privacy-by-design and rigorous evaluation.
• Pioneer novel architectures for multi-modal context integration across temporal, spatial, and behavioral dimensions.
• Develop foundational techniques for real-time knowledge grounding with dynamic constraint satisfaction.
• Research declarative programming paradigms (DSPy) for robust prompt compilation and systematic LLM behavior specification.
• Design and develop multi-agent orchestration systems that exhibit emergent reasoning capabilities.
• Advance reasoning-centered supervised fine-tuning methodologies with novel data curation, synthetic generation, and quality assurance frameworks.
• Develop and evaluate model reasoning to improve grounded recommendations and task completion under real-world constraints.
• Research parameter-efficient adaptation techniques including LoRA variants and dynamic adapter routing.
• Pioneer RLHF and RLVR with emphasis on scalable oversight.
• Develop next-generation policy optimization algorithms with formal safety guarantees.
• Research interpretability, controllability, and alignment verification for production agentic systems.
• Develop formal methods for safe exploration, reward hacking prevention, and distributional robustness.
• Pioneer privacy-preserving techniques and federated learning approaches for personal AI systems.
• Research efficient inference architectures including novel quantization, caching, and streaming paradigms.
• Develop evaluation frameworks that bridge offline metrics with online performance and safety criteria.
• Build foundational infrastructure for rapid experimentation and deployment of research breakthroughs.

Benefits

• Medical/Dental/Vision Insurance
• 401(k) Retirement Savings Plan
• HSA or FSA eligibility
• Long and Short-Term Disability Insurance
• Mental Health Benefits
• Fitness Reimbursement Program
• 25% employee discount & FAM Membership
• Flexible PTO
• Group Life Insurance
• EAP through AllOne Health

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree