Data Adaptation Research Engineer

Stellenbeschreibung:

Data Adaptation Research Engineer – Adaption

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About Us

We believe the future is adaptable, and not one‑size‑fits‑all. We will lead in real‑time efficient adaptation that combines algorithm with innovative interface design. Our global team—based in SF and beyond—brings together top talent in AI innovation. Backed by world‑class investors, we’re building Adaptable Intelligence.

Our Research Values

We are extremely driven and focused on one goal: building highly efficient, adaptable intelligence. We work as a single team, and place focus on a few key bets at a time. We are not driven by the goal of maximizing number of papers. We only publish when our work has a real‑world impact. If a simple method works well, we prioritize over a more complex and less performant method even if it is not as elegant. Our choices are always motivated by rigor and experimental success. We share back insights to the wider ecosystem to drive wider progress in the direction of continuous learning and highly efficient adaptable intelligence.

The Role

We believe one of the most profound paradigm shifts is allowing for malleable data spaces, and adaptation of data on‑the‑fly for better optimization. We are obsessed with efficiency— allowing for real‑time evolution of AI depends on making adaptable data and algorithms extremely efficient. We co‑design our algorithms with hardware requirements and serving in mind. We treat data as a first‑class citizen, and are obsessed with algorithms that enable better data quality for modeling the world around us. Every person from the most senior to the most junior inspects the data at every stage and knows what datasets fuel the algorithms.

Responsibilities

Innovation: take a leading role in our focused bets on data adaptation, which include innovating on algorithmic recipes that result in large improvements in data quality, downstream performance and data efficiency.
Research & Development: explore new research directions in data adaptation across modalities, data for different stages of the life cycle. This role is at the intersection of cutting‑edge AI research and practical application, with a focus on studying the adaptable data strategies critical for real‑time intelligence.
Hands‑on Impact: explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Adaptable Labs to drive innovation. This position requires creativity in addressing novel challenges related to data, interaction, and evaluation.

Qualifications

Deep expertise in at least one area: model efficiency, distributed systems, hardware acceleration, or algorithmic optimization.
Systems thinking ability to understand and optimize across the full ML stack.
Strong programming skills in Python. Experience with deep learning frameworks (PyTorch, JAX, TensorFlow).
Knowledge of model optimization techniques (RLHF, finetuning).
A plus is experience in an industry lab with computing at scale.
Nice to have: experience in a fast‑paced startup environment.