דרושים » הנדסה » Applied Algorithms & Operational Researcher

a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc.). The company offers an award-winning disruptive solution; a sensor free approach to smart infrastructure. The company is VC backed and in the revenues stage. Combining pioneering technology in optical fiber sensing with state-of-the-art Machine Learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly. We are looking for a talented, self-driven, and hands-on DSP Researcher to join our Photonics R&D team. In this role, you will research and develop next-generation distributed fiber-optic sensing technologies, focusing on signal processing, system modeling, simulations, and experimental validation. Working at the intersection of physics, electro-optics, fiber-optic sensing, and DSP, you will transform complex physical phenomena into robust sensing solutions for real-world applications. You will tackle challenging physical and algorithmic problems, contribute to cutting-edge sensing products, and collaborate closely with multidisciplinary R&D teams. This role is ideal for someone who thrives in a fast-paced environment, enjoys working across disciplines, and is excited to take ideas from research and lab validation to large-scale deployment.
 
What Youll Do:
* Conduct experimental and theoretical R&D for next-generation distributed fiber-optic acoustic sensing systems.
* Develop, implement, and validate DSP algorithms for coherent optical sensing systems.
* Build end-to-end expertise across the full sensing pipeline, including optical signal generation and propagation, coherent detection, signal acquisition, DSP, and advanced data analysis.
* Design and run laboratory experiments to validate new concepts, improve system performance, and support current and future product generations.
* Develop simulations, models, and analysis tools using Python and/or C ++ for lab experiments, field data analysis, signal processing, and system -level performance evaluation.
* Work with field experiment data to identify performance gaps, validate models, and improve sensing capabilities.
* Collaborate with R&D teams across disciplines to develop, validate, and integrate new sensing capabilities.
* Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

We are a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc). The company offers an award-winning disruptive solution; a sensor free approach to smart infrastructure. The company is VC backed and in the revenues stage. Combining pioneering technology in optical fiber sensing with state-of-the-art Machine Learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly.
We are looking for a talented, self-driven, and hands-on Electro Optics Systems Engineer to join Photonics R&D team. In this role, you will develop and advance next-generation distributed fiber-optic acoustic sensing (DAS) systems, combining electro-optic system design, performance modeling, simulations, experimental validation, and field data analysis. You will tackle complex physical and engineering challenges, contribute to next-generation product development, and collaborate closely with multidisciplinary teams to bring innovative sensing technologies from concept to real-world deployment. This role is ideal for someone who thrives in a fast-paced, hands-on R&D environment, enjoys working across disciplines, and wants to see their work translate into real-world impact.
What Youll Do:
* Lead experimental and theoretical R&D efforts for the development of Prismas next-generation distributed fiber-optic acoustic sensing systems.
* Design, evaluate, and optimize electro-optic interrogation systems for distributed acoustic sensing applications.
* Develop system -level models and simulations for optical signal generation, fiber propagation, coherent detection, system noise, SNR, and sensing performance.
* Build software tools and simulations in Python, C ++, or similar languages for system evaluation, signal processing, field data analysis, and performance modeling.
* Plan, execute, and analyze laboratory and field experiments to validate system performance and support product development.
* Gain unique end-to-end expertise across the full sensing system pipeline, spanning fiber optics, electro-optics, coherent detection, DSP algorithms, and advanced data analysis.
* Lead product development activities from ideation and proof of concept through design, qualification, validation, and deployment.
* Collaborate closely with multidisciplinary R&D teams, including physicists, software engineers, algorithm developers, and hardware engineers.
* Communicate effectively with both technical and non-technical stakeholders, translating complex system behavior into clear insights and actionable recommendations.

Required Chip Test Engineer
About The Position
The Chip Test Engineer plays a crucial role in designing, developing, and implementing automated test for IC chips and systems for Automotive industry. The Test Engineer is responsible to define and develop tests, design test features, program test scripts, and analyze test results to ensure the quality and functionality of products. The Test Engineer collaborates with cross-functional teams to troubleshoot issues, improve test processes, and support product development efforts.
Responsibilities:
Develop and implement test strategies, plans, and procedures for ATE systems to ensure comprehensive testing of ICs.
Design and develop test features, test programs, and test scripts for automated test environment (ATE) based on product specifications and requirements.
Collaborate with design engineers, product manager, production vendors and manufacturing teams to understand product functionality, performance requirements, and testability considerations.
Conduct feasibility studies and risk assessments to identify potential challenges and develop mitigation strategies for test development and implementation.
Develop test program based on code languages C++ ,Java and Python.
Debug, troubleshoot, and resolve issues with ATE hardware, software, and test scripts to ensure reliable and accurate test results.
Analyze test data and results to identify trends, anomalies, and potential defects, and provide feedback to design and development teams for product improvement.
Develop and maintain documentation for test procedures, specifications, and configurations.
Collaborate with vendors and suppliers to evaluate and select ATE equipment, components, and software tools that meet project requirements and performance standards.
Stay abreast of industry trends, advancements in test technologies, and best practices in automated testing to drive continuous improvement in test processes and methodologies.

We are looking for a Senior Algorithm Developer with experience in NLP and LLMs, who is highly motivated, collaborative, and results-driven individual who can work both independently and as part of a multidisciplinary team. The ideal candidate has a strong can-do attitude, excellent problem-solving skills, and a passion for leveraging AI to solve meaningful challenges in text analysis in the medical domain.

As part of the AI team you will:

Design, develop, implement, and evaluate robust, scalable AI algorithms and agentic workflows tailored to real-world challenges in clinical settings.

Prepare, process, and analyze complex medical data to support algorithm development and validation.

Ensure the reliability, performance, and accuracy of algorithms in production, including troubleshooting, testing, monitoring, and continuous improvement.

Collaborate closely with Product Managers and Clinical Specialists to translate clinical and business needs into data-driven solutions.

Research, develop and integrate cutting-edge text based alogirthms on medical text.

Apply NLP and Large Language Models (LLMs) to extract insights from medical texts and develop intelligent agents for optimized clinical decision support.

Stay up to date with cutting-edge advancements in GenAI, LLMs, and Deep Learning.

Organize and actively participate in seminars, book clubs, and conferences.

Main Technical Stack:

NLP/LLMs: Pydantic, Hugging Face Transformers, spaCy, Amazon Bedrock

Infrastructure: AWS, Docker

Programming Languages: Python

Deep Learning Frameworks: TensorFlow, Keras, Pytorch

Our Network Architecture, Modeling and Performance Insights group is seeking a skilled and driven hands-on Network Modeling Architect to conduct advanced network research and optimization while utilizing and enhancing our advanced simulation tools.

In this role, you will be a key contributor to defining the architecture and improving network performance for AI and High Performance Computing (HPC) workloads. You will be responsible for modeling advanced network topologies, configurations, logic and traffic patterns, and analyzing their effect on end-to-end performance. You will develop expertise in our simulation tools and write code daily to contribute directly to their development road map and prioritization, develop core features in the simulator, and expose the capabilities to additional users. You will take part in complex architecture decisions, define and verify the modeling assumptions, and put them to the test vs. real HW and SW performance. If you're passionate about tackling intricate challenges and contributing to comprehensive systems and working on innovative solutions, we want to hear from you.

 

What you'll be doing:

Analyze and model our AI and High Performance Computing offerings, deep dive into network behavior for training and inference and generate insights to directly impact the architecture of next-generation of AI systems. Conduct advanced network modeling, research and optimization using innovative simulation tools.

Write production-quality C++ and Python code daily. Hands-on modeling of advanced network topologies, configurations and traffic patterns representing real life AI workloads, and analyze their effect on the system's performance. Actively develop the simulator software solution while contributing modular and scalable code.

Actively support the HW and SW development life cycles, map existing and candidate features into the simulation domain to enable their analysis, impact assessment and optimization.

Take full independent ownership of the performance modeling roadmap for a defined set of features. Interface directly with internal clients, communicate the analysis conclusions effectively and iterate on them. Drive projects from concept to completion.

Improve the quality of the simulation as a software product, ensuring robustness and reliability.

we are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of primary products. This involves working on core systems, such as POS underwriting models, models for merchant operations, Fraud investigator AI agents and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / fraud / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g. providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Analyze 15+ different data sources in order to train models and agents to catch fraudulent patterns.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

Were looking for a talented Hardware Engineer to join our innovative team.
Responsibilities
Design, develop, and validate hardware boards for advanced radar and chip-based systems, with a strong focus on digital circuitry and power supply design.
Perform hands-on lab work (HO), including board bring-up, debugging, troubleshooting, repair, and continuous improvement of existing hardware.
Define, write, and execute comprehensive test plans and test setups for board-level validation.
Analyze test results, characterize performance, and document findings, including detailed test reports, failure analysis, and corrective actions.
Support schematic design activities and contribute to the development and maintenance of design environments and databases for EDA tools.
Experience with SI/PI simulation tools.
Collaborate closely with lab technicians, engineers, and cross-functional teams to ensure efficient execution of lab activities and project goals.
Take an active role in prioritizing tasks, driving technical decisions, and owning deliverables end-to-end.

we are looking for a AI Algorithm Tech Lead.
This is a role in core AI group, which specializes in developing cutting-edge AI solutions in healthcare, enhancing medical imaging and diagnostics. As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
Responsibilities:
Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects.
Design and conduct research and experimentation to improve algorithm performance and accuracy.
Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team.
Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives.
Provide strategic direction and technical mentoring to elevate the capabilities of the AI team.

We are looking for an outstanding Senior Networking Software Architect to join the NIC/DPU Software and Firmware Architecture group. In this role, you will help define the next generation of our datacenter and AI networking platforms, with focus on DPU management, QoS, performance, telemetry, and software architecture across stacks. You will work closely with hardware designers, firmware/kernel driver teams, system engineers, validation, product management and customers. The role spans early architecture definition, pre-silicon design, bring-up, and production readiness for large-scale AI and cloud datacenter deployments.

What Youll Be Doing:

Own software and system architecture for next-generation DPU management, QoS, performance, telemetry, and observability features.

Define end-to-end control and management flows across DOCA, host drivers, embedded firmware, BMC, management controllers and external management systems.

Specify telemetry and observability requirements, including counters, logs, traces, events, health monitoring, debug data, and streaming telemetry.

Define management interfaces and APIs for configuration, provisioning, lifecycle operations, diagnostics, and field serviceability.

Write clear architecture specifications, interface definitions, flow diagrams, and design documents for software, firmware, and system teams.

Partner with R&D teams to translate high-level architecture into implementable designs and guide features through development, validation, silicon bring-up, and production.

Analyze system performance bottlenecks, interoperability issues, telemetry gaps, and customer-reported issues, then feed learnings into future architecture.

Collaborate with system and cluster architects to ensure NIC/DPU features fit end-to-end AI datacenter and cloud networking designs.

In this role, you will be a key contributor to defining the architecture and improving network performance for AI and High Performance Computing (HPC) workloads. You will be responsible for modeling advanced network topologies, configurations, logic and traffic patterns, and analyzing their effect on end to end performance. You will develop expertise in our simulation tools and contribute directly to their development road map and prioritization, develop core features in the simulator, and expose the capabilities to additional users. You will take part in complex architecture decisions, define and verify the modeling assumptions, and put them to the test vs. real HW and SW performance.

If you're passionate about tackling intricate challenges and contributing to comprehensive systems and working on innovative solutions, we want to hear from you.

What you'll be doing:

Analyze and model our AI and High Performance Computing offerings, deep dive into network behavior for training and inference and generate insights to directly impact the architecture of next-generations of AI systems. Conduct advanced network modeling, research and optimization using innovative simulation tools.

Implement modeling of advanced network topologies, configurations and traffic patterns which represent real life AI workloads, and analyze their effect on the systems performance. Actively develop the simulator software solution while contributing modular and scalable code.

Actively support the HW and SW development life cycles, map existing and candidate features into the simulation domain to enable their analysis, impact assessment and optimization.

Take full independent ownership of the performance modeling roadmap for a defined set of features. Interface directly with internal clients, communicate the analysis conclusions effectively and iterate on them. Drive projects from concept to completion.

Improve the quality of the simulation as a software product, ensuring robustness and reliability.