AI Research Scientist/Manager – Adaptive Intelligence

P-1 AI

AI Research Scientist/Manager developing innovative methods for AI continual learning at P-1 AI. Collaborating within a small elite team focused on physical applications of AI.

Posted 6/30/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $200,000 - $385,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in continual learning, meta-learning, and memory systems within large-scale AI systems, with proficiency in Python and modern ML frameworks like PyTorch or JAX. Capable of owning the full development pipeline from research to product integration while thriving in collaborative environments.

Highest-signal resume keywords

PhD In Computer ScienceResearch In Continual LearningFluent In PythonExperience With PyTorchPublications In Top-Tier Venues

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Continual LearningMeta-LearningMemory SystemsModel AdaptationTransfer LearningReinforcement LearningOnline LearningData GenerationEvaluationProduct Integration

Soft Skills

Creative Problem SolvingClear CommunicationHigh OwnershipCollaborationAdaptability

Tools & Technologies

PyTorchJAXDistributed Training Frameworks

Industry Keywords

AI SystemsKnowledge RetentionKnowledge ConsolidationTest-Time AdaptationSelf-Improvement

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Research and develop approaches for continual learning, fast adaptation, memory formation, knowledge retention, and transfer learning in large-scale AI systems.
Own the full development pipeline from data generation to evaluation to product integration.
Contribute to both research strategy and technical implementation—this is a hands-on role. Have ownership over your own applied research stream.
Investigate topics such as continual learning, online learning, test-time adaptation, memory architectures, meta-learning, self-improvement, and knowledge consolidation.

Requirements

What you’ll need

A PhD (or equivalent experience) in Computer Science, Robotics, Engineering, Math, or a related field.
Have conducted research in one or more areas such as continual learning, lifelong learning, meta-learning, online learning, reinforcement learning, memory systems, model adaptation, transfer learning, or related fields.
Are fluent in Python and modern ML stack such as PyTorch or JAX, and distributed training frameworks.
Creative approach to bringing definition and solutions to under-specificed challenges.
Are excited by fundamental questions around how intelligent systems acquire, retain, and use knowledge over time.
Thrive in fast-moving, collaborative environments, and communicate technical matters with clarity.
Take a high-ownership, “make it work” approach to problem solving.
Publications in top-tier venues.

Benefits

Comp & perks

Competitive salary
Meaningful equity ownership
Healthcare
Dental
Vision
401(k) match
Unlimited PTO