לוח משרות דרושים מהנדסים משרה מלאה

Responsibilities:
Review of Contract ,Customer SOW and SPEC requirements to ensure compliance of design and production.
Approve gates review at R&D
PLCM (Project Life Cycle Management) - process control, full partnership in project management during the development, testing, production, customer delivery and customer support phases throughout the product life
Identifying regulatory Gaps in new and carrent projects
Perform Internal and External Audits
QA presence in R&D process (capacity) and ability to prevent errors in design
Follow up after R&D corrective and preventive actions and Improvement Plans
Transfer products from development to NPI and serial production (QA activities)
Review and approval ECO / MCO / ATP/ATR, Waiver relate to R&D , ENG
Writing QA procedures
FRACAS Management
Quality Assurance Program Plan (QAPP) and the Quality Allocation Tasks for the program.
Customer complince - relate to NPI , Pre production , design errors
Perform Quarterly data analysis for QBR.

Responsibilities:
Overall responsibility for precision tracking technical project management at R&D including planning and monitoring of all R&D activities, planning and monitoring of project R&D budget (material and hours), lead of technical activities with the customer including design reviews, acceptance testing and system assimilation.
Overall responsibility of the system level architecture of complex systems
Overall responsibility for System, Software and Hardware level specifications and requirements.
Overall responsibility and active participation in the Integration and Proof of Design phases.
Overall responsibility for electrical connectivity design between LRUs.

Responsibilities
Design of new, and support of existing airborne, marine and stationary pedestals to meet with environmental requirements.
Produce designs meeting performance, cost and manufacturability goals
Create fabrication and assembly drawings as well as related documentation
Support prototype assembly, assist in integration and test.

Responsibilities
Design of new, and support of existing airborne, marine and stationary pedestals to meet with environmental requirements.
Produce designs meeting performance, cost and manufacturability goals
Create fabrication and assembly drawings as well as related documentation
Support prototype assembly, assist in integration and test

Founded in Tel Aviv in 2016, we are a computer vision and data company that creates automatic vehicle inspection systems to encourage road safety and increase transparency across the automotive industry. With key partnerships including General Motors, Volvo, and CarMax among others, our technology is utilized in manufacturing plants, dealerships, wholesale auctions, delivery fleets, security checkpoints, and more. Want to be an essential part of setting the standard for safety in the auto industry? Check out the description below to see if youre a great fit! UVeye is seeking a highly skilled and innovative system Engineer to join our R&D team. The ideal candidate will have a strong background in systems engineering, particularly in optical sensors and visible light cameras. You will play a crucial role in the development and optimization of our multidisciplinary system, ensuring its high performance across various applications.
Heres what youll be doing:
* Develop innovative solutions to challenging customer use cases
* Define system architecture for new products through collaboration with optics, mechanics, electronics, SW and algorithm teams.
* Design and integrate system features, calibrations, and performance optimizations.
* Support existing products, including root cause analysis and solutions to customer issues.

Our data science team is seeking a highly skilled AI researcher with expertise in modern AI methods (e.g., multi-agent architectures, reinforcement learning on LLMs) and a passion for transforming theoretical challenges into real-world products.
In this role, you will leverage our unique clinical datasets to design and build groundbreaking solutions that provide medical benefits to millions of people. You will take full end-to-end ownership of your models - from ideation and research to production deployment and ongoing monitoring.
Working across both research and production environments, you should have proven experience in developing and deploying machine learning algorithms, along with strong interpersonal and collaboration skills. We value independent thinkers who are also proactive doers.

What Youll Be Doing:
Develop clinical AI models to support Ks clinic workflows, with a focus on patient-facing applications
Design and implement scalable, efficient pipelines for data preprocessing, information extraction, and model training
Stay up to date with the latest AI research and best practices, and translate them into production-ready solutions
Communicate complex technical concepts and solutions to non-technical stakeholders
Collaborate with MLE and AI engineering teams to deploy scalable, robust solutions

We are looking for a motivated and experienced Machine Learning Platform Engineer to join our dynamic team.

In this role, you will collaborate closely with data scientists and DevOps professionals to design and build the infrastructure, ecosystem libraries, and pipelines that power our data science initiatives. You will take ownership of model development, monitoring, and maintenance, working hand-in-hand with data scientists on a daily basis.

If youre passionate about AI, machine learning, and writing high-quality code-and are eager to contribute to innovative, impactful do good projects in the digital health space-wed love to hear from you!

What you'll be doing:
Design, develop, and maintain our machine learning ecosystem libraries.
Build and manage data science code, Docker images, and Kubeflow Pipelines (KFP).
Create and maintain CI scripts to ensure seamless integration and delivery.
Conduct thorough code reviews to uphold high-quality standards.
Collaborate closely with data scientists, understanding and addressing their evolving needs.
Work alongside software developers to seamlessly integrate machine learning models into production systems.
Stay current with the latest advancements in machine learning, leveraging innovative techniques to enhance the companys products and services.

In this key engineering role in one of our multidisciplinary product teams, you will take end-to-end ownership of the engineering discipline and tasks that will bring the most impact and joy to millions of learners. All this while quickly learning and adapting to do whatever it takes to solve the unsolvable.

We are looking for an experienced ML/AI engineer to anchor our ML Platform team. You will lead the effort to productize our Large Language Models, transforming experimental code into robust, efficient services. Your goal is to build the infrastructure that allows our Data Scientists to move fast without breaking production.

What you'll be doing:
Model Development & Optimization

Fine-tuning & Engineering: Develop and fine-tune LLMs/classic models for specific medical tasks (condition detection, dialogue systems) using internal datasets.
Research to Production: Partner with Data Scientists to develop experimental code into scalable, production-ready modules.
Platform Engineering & Infrastructure

Pipeline Orchestration: Build and maintain complex ML workflows using Kubeflow Pipelines (KFP) or similar orchestration tools.
Internal Tooling: Develop and manage the internal Python ecosystem-libraries, SDKs, and utilities-that the Data Science team uses for daily development.
CI/CD & Automation: Write and maintain CI/CD scripts to automate the testing, versioning, and deployment of machine learning artifacts.
Production Standards & Integration

System Integration: Work with backend developers to integrate trained models/agents into the core application architecture.
Code Quality: Enforce high engineering standards through code reviews, ensuring that research code meets production reliability and maintainability requirements.
Requirements Engineering: Translate evolving data science requirements into concrete infrastructure and platform features.