Principal AI Engineer
Gainwell Technologies
AWSCloudDockerKubernetesPythonTerraform
AI Engineer III
Gopuff
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $215,000 - $275,000 per year
Job Level
SeniorLead
Tech Stack
CloudPyTorch
About the role
- Lead the design and deployment of agentic AI that reasons over rich, real‑world context and constraints.
- Define the architecture, standards, and evaluation strategy that connect research to real‑world lift.
- Mentor colleagues and influence cross‑functional roadmaps.
- Ship systems that deliver measurable improvements to core customer and business outcomes.
- Set the strategy for context engineering to maximize precision/recall of key order metrics across sessions, households, locales, and time.
- Architect multi‑modal context integration and real‑time grounding with dynamic constraint satisfaction.
- Establish retrieval freshness and memory policies; formalize context schemas and data contracts.
- Design multi‑agent orchestration patterns for robust emergent reasoning.
- Own the reasoning architecture and evaluation strategy for low-latency outcomes at scale.
- Drive parameter‑efficient adaptation strategies with clear criteria for specialization vs. generalization.
Requirements
- PhD in Computer Science, Machine Learning, or equivalent research experience with significant contributions to AI/ML literature.
- 7+ years of building and shipping large‑scale ML systems with significant ownership; proven impact in production LLM or RL‑driven products.
- 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.
- Deep expertise in transformer architectures, SFT, and RLHF; hands‑on leadership with RLVR and verifiable reward design.
- Mastery of policy optimization (DPO/PPO/GRPO/GSPO) and the ability to extend/regularize policies under safety, latency, and cost constraints.
- Strong grounding in offline evaluation, counterfactual estimators, and safe online ramp strategies.
- Systems fluency: PyTorch, distributed training, low‑latency serving, observability, and cloud‑native ML infra.
- Demonstrated leadership across cross‑functional teams, with clear communication and mentoring track record.
- Commitment to responsible AI: privacy, safety, and alignment principles embedded end‑to‑end.
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 (formerly Carebridge)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
agentic AImulti-agent systemsdeclarative programmingfine-tuning techniquestransformer architecturespolicy optimizationoffline evaluationcounterfactual estimatorslow-latency servingcloud-native ML infrastructure
Soft skills
mentoringleadershipcross-functional collaborationcommunicationstrategic thinkinginfluencesystems engineeringproblem-solvingadaptabilitycommitment to responsible AI
Certifications
PhD in Computer ScienceMachine Learning
