עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!

במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.

מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.

חברה בתחום הייטק / חומרה / תוכנה / סייבר

רעננה

חברה בתחום הייטק / חומרה / תוכנה / סייבר

רעננה
מלאה
25,000-35,000 ₪ הערכה מבוססת AI ולא שכר שהתקבל מהמעסיק
הערכה מבוססת AI ולא שכר של המעסיק

In this role, you will be a key contributor to the design and implementation of our companys AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the AI Graph Compiler software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

Requirements:
3 years of experience in building high-quality embedded software using C/C++.
BSc/MSc in Computer Science, Electrical Engineering, or equivalent.
Proven experience developing and maintaining complex embedded systems, including multi-component software stacks, tight HW/SW integration, and system-level debugging.
Experience in designing and implementing software based on product & hardware specifications.
Experience working under tight memory, power, and real-time constraints.
Excellent interpersonal and communication skills, with a proven ability to work well in a team.
Advantages:
Experience in data-flow optimization using profiling tools.
Interaction with AI compilers / graph optimizers.
Familiarity with fixed-point / quantized inference is a strong plus.
Familiarity with neural network open-source frameworks such as PyTorch and TensorFlow.
Proficiency in Python coding.

This position is open to all candidates.