לוח משרות דרושים סטודנטים - מדעי המחשב משרה חלקית, לחיפוש זה נמצאו 50 משרות

looking for talented students to help us develop the semiconductor platform which is based on revolutionary architecture.
Take part in the development of innovative products within disruptive system architecture. Youll have the opportunity to work on the technologies that power the worlds largest Cloud provider, within a dynamic, open, and fast-paced environment. Our Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world.

Key job responsibilities
As Post Silicon Dev Student you will be exposed and learn wide range of expertise such as: C++ programing, hardware design, data mining, Verilog simulations, working with various high end test equipment and more
If paving new roads on edge of technology within a strong and dynamic team is what you seek, your place is with us.

We are seeking a versatile, highly motivated Engineering student to help us develop 3D graphical simulation software solutions focused on robotics and automation systems for industries like Automotive, Electronics, Aerospace, and more. This is an excellent opportunity to apply your technical knowledge, gain real-world experience, and grow within a global software leader while working on complex industrial challenges.

Key Responsibilities

Develop and complete system validation tests ensuring compliance with customer business needs
Prepare customer focused demos and tutorials
Support customer projects and engagements driving new capabilities and technologies deployment
Contribute to the advancement of robotics and automation solutions using 3D simulation and computer vision technologies

We are looking for a highly motivated AI Research Student for our Robotics & Simulation AI team. You will be passionate about data science, AI quality measurement, and the intersection of AI with high-accuracy industrial domains. This role is ideal for someone who grows with challenging existing assumptions, defining rigorous evaluation methodologies, and pushing AI systems toward measurable reliability. You will combine strong data science and research skills with hands-on experimentation in a production AI product that controls robotic manufacturing simulations.

Key Responsibilities

AI Quality & Stability Research

Define and implement metrics to measure the stability, accuracy, and reliability of our production AI Copilot (PSCoPilot)
Design evaluation frameworks for AI agents operating in safety-critical robotics and simulation environments
Build observability and tracing pipelines using platforms like Langfuse to monitor Copilot performance, token usage, latency, and tool-calling success rates
Analyze failure modes, hallucination patterns, and tool-calling accuracy across 48+ MCP-exposed robotic operations
Develop automated regression and benchmark pipelines to track Copilot quality over time

Data Science & Experimentation

Conduct statistical analysis on Copilot interactions (tool selection accuracy, collision detection correctness, path planning success rates)
Research and apply techniques from AI evaluation literature (LLM-as-judge, human-in-the-loop validation, domain-specific benchmarks)
Leverage LangChain and similar orchestration frameworks to prototype evaluation chains, structured agent workflows, and comparison experiments
Explore how multi-layer agent architectures (fast triage + deep execution) affect accuracy and cost trade-offs
Challenge the team with data-driven insights on where the Copilot underperforms and why

Domain AI Research

Investigate how to improve AI reasoning for robotics tasks requiring high precision (welding, clearance checking, reachability analysis)
Research grounding techniques that reduce errors in domains with zero tolerance for incorrect outputs
Explore and apply new AI technologies (GenAI tools, AI coding assistants, agents, MCP-based solutions) to enhance Copilot capabilities
Validate technical feasibility through hands-on experimentation with our production MCP bridge and two-layer streaming agent engine

Communication & Documentation

Document findings, benchmarks, and technical recommendations
Present results to technical and business partners
Collaborate with the team to translate research insights into production improvements

As we expand our presence in Israel, we are seeking a motivated Physical Design Student to join our founding local engineering team.

This is a unique opportunity to kickstart your career in the semiconductor industry. Working alongside senior industry veterans, you will gain hands-on experience in backend execution and advanced methodologies for cutting-edge chips that power the world's largest AI clusters. If you are passionate about silicon hardware, eager to learn, and thrive on solving complex engineering challenges, this role offers the perfect bridge between your academic studies and a high-impact career.


Key Responsibilities

Guided Implementation & Learning
Partner with and learn from senior engineers to support the physical implementation journey, including synthesis, floorplanning, Place & Route (P&R), and Clock-Tree Synthesis (CTS).
Assist in macro-level implementation and develop hands-on skills in complex layout routing.
Participate in deep-submicron process challenges under close professional mentorship.

Signoff & Design Integrity Support
Assist in running engineering checks for design integrity, including Static Timing Analysis (STA), Physical Verification (DRC/LVS), and Reliability analysis (EMIR).
Learn to apply Logic Equivalence Checking (LEC) to help guarantee design correctness.
Gain exposure to the rigorous flows required to ensure first-pass silicon success.

Scripting & Cross-Functional Collaboration
Leverage and develop scripting tools to automate repetitive tasks and optimize the engineering environment.
Collaborate with Architecture, Design, and DFT teams to understand how different chip design disciplines intersect.
Actively participate in team reviews and technical discussions to ramp up backend methodologies.