Job Overview
Location
United States
Job Type
Full-time
Category
Data Science
Date Posted
June 2, 2026
Full Job Description
đź“‹ Description
- • Build models that continuously evolve with real-world data, focusing on efficiency, gradient-free exploration, real-time learning, and interface design to enable dynamic adaptation.
- • Co-design serving systems, algorithms, and user interfaces as an integrated whole to maximize system-wide efficiency and enable real-time interaction with the environment.
- • Drive innovation by moving quickly on high-conviction research ideas that intersect with measurable product impact, prioritizing real-world utility over publication count.
- • Collaborate across software, hardware, and algorithmic domains to identify and unlock system-level efficiency gains in machine learning pipelines.
- • Design and implement ML systems where the model’s ability to interact with the world is the primary metric of success, not static accuracy or benchmark scores.
- • Translate research into working products; ensure every idea is validated through deployment and user impact, not theoretical metrics alone.
- • Apply deep expertise in one or more areas: model efficiency, real-time alignment, or algorithmic optimization to advance the state of continual adaptation.
- • Leverage systems thinking to optimize across the full ML stack—from data ingestion and training to inference and user feedback loops.
- • Write production-grade code in Python using deep learning frameworks such as PyTorch, JAX, or TensorFlow to prototype, train, and deploy adaptive models.
- • Apply model optimization techniques including RLHF, fine-tuning, and other alignment methods to improve model behavior in dynamic environments.
- • Work within an industry lab environment that operates at scale, with access to significant computational resources and real-world deployment pipelines.
- • Contribute to the research community by sharing meaningful advancements that move the field forward, not just incremental improvements.
- • Operate with urgency and conviction as part of a unified team focused on a few high-impact bets, avoiding dilution of effort across low-priority projects.
- • Embrace a culture of talent density: collaborate with highly driven individuals who challenge assumptions, propose bold ideas, and make work feel lighter through mutual support.
- • Maintain adaptability and openness to feedback; prioritize growth and iteration over perfection, and be willing to pivot based on empirical results.
- • Contribute to a vision of AI that is flexible, personalized, and accessible to everyone by building efficient intelligence that evolves continuously, not statically.
🎯 Requirements
- • PhD or equivalent research experience in a computer science field
- • 4-5+ years of industry experience
- • Publishing record at ICML, NeurIPS, ACL, ICLR, or EMNLP
- • Deep expertise in at least one area: model efficiency, real-time alignment, or algorithmic optimization
- • Systems thinking ability to understand and optimize across the full ML stack
- • Strong programming skills in Python; experience with PyTorch, JAX, or TensorFlow
🏖️ Benefits
- • Flexible work: In-person collaboration in the Bay Area, a distributed global-first team, and team offsites
- • Adaption Passport: Annual travel stipend to explore a country you've never visited
- • Lunch Stipend: Weekly meal allowance for take-out or grocery delivery
- • Well-Being: Comprehensive medical benefits and generous paid time off
Skills & Technologies
About Adaption Inc.
Adaption is a company focused on revolutionizing the way businesses manage their digital assets and workflows. They provide a comprehensive platform designed to streamline content creation, collaboration, and distribution processes. Their solution caters to various industries, enabling organizations to enhance efficiency, reduce operational costs, and improve overall productivity. By leveraging advanced technology, Adaption empowers teams to work more cohesively and deliver high-quality digital experiences. The company's core mission is to simplify complex digital operations, making them accessible and manageable for businesses of all sizes.
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