Machine Learning Compiler Engineer, Annapurna Labs

Overview

Our team is responsible for the AWS Neuron Compiler, a cutting-edge deep learning compiler stack that powers Generative AI and other advanced ML workloads on AWS’s custom-built ML accelerators — Inferentia and Trainium. These accelerators deliver best-in-class performance and cost-efficiency for ML inference and training in the cloud. We’re building a new core group of engineers in TLV to drive innovation in compiler technology and systems-level ML software. As a Machine Learning Compiler Engineer, you’ll help shape the direction of the team from the ground up and work on high-impact compiler work across design and optimization.

This is a unique opportunity to be at the intersection of ML and systems within AWS, helping to build the future of AI infrastructure — right here in Tel Aviv.

Responsibilities

• Designing and optimizing compiler features for high-performance ML workloads.
• Solving complex challenges in areas like graph optimization, code generation, and hardware-software co-design.
• Collaborating across Runtime, Frameworks, and Hardware teams to maximize end-to-end performance.
• As part of the Backend Compiler Team, contribute to projects involving instruction scheduling, memory management, parallelism, graph partitioning, ISA design, and new hardware bring-up.

A day in the life

• Design and code solutions to help our team drive efficiencies in software architecture, create metrics, implement automation and other improvements, and resolve the root cause of software defects.
• Build high-impact solutions to deliver to our large customer base.
• Participate in design discussions, code review, and communicate with internal and external stakeholders.
• Work cross-functionally to help drive business decisions with your technical input.
• Work in a startup-like development environment, where you’re always working on the most important stuff.

Considering the technical requirements of this role, and to ensure fair and equal candidate consideration, we are conducting full interview loops. If you meet the basic qualifications, and the team is interested in moving forward, we will be in touch to coordinate your interviews.

About the team

• Diverse Experiences: Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
• Why AWS: Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from startups to Global 500 companies trust our products and services.
• Work/Life Balance: Flexible work hours and arrangements are part of our culture.
• Inclusive Team Culture: AWS values curiosity and connection. Our affinity groups promote inclusion and empower our people to take pride in what makes us unique.
• Mentorship and Career Growth: We’re committed to ongoing learning, mentorship, and career development resources.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

BASIC QUALIFICATIONS

• B.S. or M.S. in computer science or related field
• Proficiency with 1 or more of the following programming languages: C++ (preferred), Python
• 3+ years of non-internship professional software development experience
• 3+ years of experience developing compiler optimization, graph-theory, hardware bring-up, FPGA placement and routing algorithms, or hardware resource management

PREFERRED QUALIFICATIONS

• M.S. or Ph.D. in computer science or related field
• Strong knowledge in one or more areas: compiler design, instruction scheduling, memory allocation, data transfer optimization, graph partitioning, parallel programming, code generation, Instruction Set Architectures, new hardware bring-up, and hardware-software co-design
• Experience with LLVM and/or MLIR
• Experience with developing algorithms for simulation tools
• Experience in TensorFlow, PyTorch, and/or JAX
• Experience in LLM, Vision or other deep-learning models