United States onlyMission
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.
Scope and Impact
You will own core components of our instant shopping personal intelligence—context engineering, grounding, alignment, and serving—so technology accelerates customers to their goals, leveraging our unparalleled delivery speed. You’ll 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. You’ll use relevant APIs for data augmentation and ship low‑latency, reliable inference (batching, caching, quantization, streaming) with strong observability and safety. In close partnership with Engineering and Data Science, you’ll run experiments end‑to‑end and deliver production models that drive measurable lifts in business KPI under privacy‑by‑design and rigorous evaluation.
Research Areas & Contributions
Advanced Context & Grounding Research:
- 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 (LangChain, LangGraph, CrewAI, Autogen, LlamaIndex) that exhibit emergent reasoning capabilities
Alignment & Learning Systems:
- Advance reasoning-centered supervised fine-tuning methodologies with novel data curation, synthetic generation, and quality assurance frameworks
- Develop and evaluate model reasoning (task decomposition, tool-use, and self-correction) to improve grounded recommendations and task completion under real-world constraints.
- Research parameter-efficient adaptation techniques including LoRA variants, Text-to-LoRA synthesis, and dynamic adapter routing
- Pioneer RLHF and RLVR with emphasis on scalable oversight
- Develop next-generation policy optimization algorithms beyond GRPO/GSPO with formal safety guarantees
Safety & Robustness:
- 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
Systems & Deployment:
- 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
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 (DSPy, LangChain ecosystem)
- Strong systems engineering capabilities with PyTorch, distributed training, and cloud-native ML infrastructure
- Track record of publications in top-tier venues (NeurIPS, ICML, ICLR, AAAI) or equivalent industry impact
- Commitment to responsible AI development and alignment research
Preferred Qualifications:
- 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
What We Offer:
- Opportunity to shape the future of personal AI and human-machine collaboration
- Access to world-class compute resources and datasets
- Collaboration with leading researchers across academia and industry
- Publication support and conference travel for research dissemination
- Competitive compensation with significant equity upside in breakthrough AI applications
Compensation
- Gopuff pays employees based on market pricing and pay may vary depending on your location. The salary range below reflects what we’d reasonably expect to pay candidates. A candidate’s starting pay will be determined based on job-related skills, experience, qualifications, interview performance, and market conditions. These ranges may be modified in the future. Exceptions may be made for exceptional individuals. For additional information on this role’s compensation package, please reach out to the designated recruiter for this role.
- This role is eligible for a discretionary annual cash bonus and participation in Gopuff’s equity incentive plan.
- Base Salary Range: $175,000 - $220,000
Benefits Overview
- 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 (formerly Carebridge)
The only predictable thing about life is that it’s wildly unpredictable. That’s where we come in.
When life does what it does best, customers turn to Gopuff to deliver their everyday essentials, and to get through their day & night, work day and weekend.
We’re assembling a team of thinkers, dreamers & risk-takers...the kind of people who know the value of peace of mind in an unpredictable world. (And people who love snacks.)
Like what you’re hearing? Welcome to Gopuff.
The Gopuff Fam is committed to an inclusive workplace where we do not discriminate on the basis of race, sex, gender, national origin, religion, sexual orientation, gender identity, marital or familial status, age, ancestry, disability, genetic information, or any other characteristic protected by applicable laws. We believe in diversity and encourage any qualified individual to apply. We are an equal employment opportunity employer.
Portugal only
