Senior ML Scientist - Hardware-Aware AI Systems

Amazon; Cupertino (CA); Presencial; USD 192.000 - 260.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

401(k) matching

Paid time off

Parental leave

Descripción de la vacante

Annapurna Labs (U.S.) Inc. in Cupertino, CA is seeking Applied Scientists to push hardware-aware ML for Trainium and Inferentia. You will own research-to-production, collaborate with silicon teams, publish results, and mentor junior scientists in a strategic AWS area.

Responsibilities include end-to-end problem ownership, writing production-grade PyTorch/JAX code, and partnering across model, engineering, and hardware teams. A PhD or Master’s with 6+ years is required.

Formación

• PhD or Master’s degree and 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• 3+ years of building machine learning models for business application experience.
• Experience with neural deep learning methods and machine learning.

Responsabilidades

• Own scientific problems end-to-end - from research through production impact.
• Develop production-quality code in PyTorch or JAX and integrate components into large-scale training systems.
• Partner with model, engineering, and hardware teams to inform Trainium and product stack.
• Mentor fellow scientists and interns; participate in reviews and roadmap planning.
• Publish research at top venues and engage the broader scientific community.

Conocimientos

Java

C++

Python

Educación

PhD

Master's degree

Herramientas

PyTorch

JAX

Descripción del empleo

Annapurna Labs (U.S.) Inc. in Cupertino, CA is seeking Applied Scientists to push hardware-aware ML for Trainium and Inferentia. You will own research-to-production, collaborate with silicon teams, publish results, and mentor junior scientists in a strategic AWS area.

Responsibilities include end-to-end problem ownership, writing production-grade PyTorch/JAX code, and partnering across model, engineering, and hardware teams. A PhD or Master’s with 6+ years is required.