לוח משרות דרושים סטודנטים - מדעי המחשב משרה מלאה, לחיפוש זה נמצאו 18 משרות

we are looking for students for a part-time Technical support Representative position.

The position is part-time, in shifts that include nights, weekends and holidays.

Location: Poleg, Netanya

Responsibilities
Providing Bright Data's customers with timely and accurate technical support
Independently understanding and solving technical problems using internal documentation
Clarifying problem solutions to customers and providing them with the best workflows
Interacting with other departments to clarify issues and escalate them when required

We are looking for a software student that will take part in our software projects and practical research activities.

You will have the opportunity to learn and gain experience related to many aspects of software and hardware. In addition, we encourage you to have your final academic project done here.

responsibilities:

Maintaining, updating and debugging existing software tools, primarily in Python. This part is around 70% of the expected activity.

Taking part in architectural research and development. Including: developing test cases, executing and presenting results.

Modeling, running, and analyzing AI neural networks to evaluate their behavior and performance on Cevas DSP processors and AI accelerators.



As a research student , you will work on one of the teams core challenges in modern LLM-based systems, such as:

Agentic RAG
Advanced retrieval strategies, hybrid search, query rewriting, context optimization, and LLM-driven reasoning pipelines
Automatic Evaluation of Agents
LLM-as-a-Judge, scoring frameworks, hallucination detection, and robust evaluation methodologies
Agents for Knowledge Creation
Building agents that autonomously generate, refine, and maintain enterprise knowledge bases
Ontology-Grounded RAG
Enhancing models with domain-specific knowledge and structured representations
Data Analysis Agents
Agents capable of analyzing complex operational, product, and support data at scale
Fine-tuning LLMs for customer domain adaptation
Automatic agent improvement from user feedback including learning from errors, evaluations, and human signals
You will work one day per week, embedded directly in the Ask-AI research group, collaborating closely with senior researchers and engineers.

As a Software Engineer Intern in the MSC IL AI Innovation team, you will contribute to the design, development, testing, and delivery of AI-powered features and services for our Specialized Clouds organization. You will work with mentors and engineering team members to build reliable, secure, and responsible software, while learning modern AI engineering practices across prompts, retrieval, agents, evaluation, observability, and cloud-native development.

This internship is designed for entrepreneurial, creative, and highly motivated students who are passionate about building AI-native products, taking ownership in ambiguous 0 to 1 environments, and using AI throughout the engineering lifecycle to solve complex, high-impact problems in sovereign and regulated cloud environments.


Responsibilities
Develop, test, debug, and maintain software components for AI-powered products, services, or internal tools.

Contribute production-quality code that is maintainable, secure, performant, and aligned with team standards.

Partner with mentors, engineers, product managers, and stakeholders to understand user requirements and translate them into engineering tasks.

Contribute to AI features such as agents, tool/API integrations, prompt flows, retrieval workflows, evaluation harnesses, and monitoring capabilities.

Help define and run tests, evaluations, and quality checks for AI behavior, including accuracy, relevance, groundedness, and reliability.

Investigate issues using logs, traces, test results, and debugging tools, and incorporate feedback into improved solutions.

Learn and apply engineering best practices across code quality, security, responsible AI, CI/CD, documentation, and observability.

Document work clearly and share implementation details with team members to support continuity and knowledge sharing.

Collaborate effectively with team members in a dynamic, ambiguous environment; adapt quickly across technologies, stacks, and engineering tasks; proactively seek and incorporate feedback; and contribute to shared goals while building technical depth.