לוח משרות דרושים פיתוח אלגוריתמים, לחיפוש זה נמצאו 72 משרות

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

We are looking for a Software Engineer to join our core Algorithm team as an dedicated data-core / platform engineer. You will support the algorithm engineers developing detection algorithms to design and build the infrastructure they run on: the object-detection (OD) pipeline, its orchestration and deployment, its data and model catalog, and the benchmark and labeling systems that drive model improvement. This is a high-autonomy role with real, end-to-end ownership of production systems from day one.

The technologies listed in this description are examples of our day-to-day - not a rigid checklist. We care far more about how you think, how you plan, how you debug, and how fast you learn than about which specific tools you have already used. If you love the craft of making things work and want to go deep, you can learn the rest here.

In the AI era, being a strong engineer means more than writing great code. It means operating as an architect who directs AI agents - designing the solution with clarity, then guiding them to execute it at a level and speed that wasn't possible before. We are building a culture where this is the norm, and we're looking for someone who is excited to work and grow in that direction.



What You'll Do

Take on hard, open-ended infrastructure challenges and make them work - designing, building, decoupling, and hardening the systems behind our object-detection pipeline, from data and model management to benchmarking, so everything runs reliably at scale.
Architect and build the backbone of the OD pipeline - orchestration (Airflow on Kubernetes), data plumbing (S3 / PostGIS / SQS), CI/CD, and deployment across multiple environments - designing clean interfaces and data contracts the algorithm team can build on with confidence.
Debug across the whole stack, wherever the problem leads - a stuck DAG, a flaky pipeline stage, a slow query, a GPU/driver mismatch - and turn one-off firefights into lasting fixes and better observability.
Own the data and model lifecycle: versioned datasets and model weights with clear provenance, and the labeling → export → retraining loop that keeps the models improving.
Learn fast and go deep. Pick up new tools and new layers of the stack as the work requires, and raise the team's engineering and operational standards as you go.
Partner closely with algorithm engineers and the data-collection / labeling operations team to turn research prototypes into robust, scalable production systems.
Integrate AI tools into your workflow and grow into operating as an architect who directs AI agents - designing the solution, then guiding them to build it.

We're currently seeking a Data Researcher to join our Data Team and help proactively guide our business growth through the provision of strategic perspective, market insight, and experience with analytical tools and techniques. You will work closely with product managers, medical analysts, and the engineering team and bring your expert analytical ability to provide key insights, recognize key opportunities, and drive strategic initiatives forward.

Responsibilities
Build and maintain data pipelines and dashboards to improve data visibility and reporting in production environments
Implement AI-powered workflows for internal and external uses
Work with product, medical, and engineering teams to turn data into insights and recommendations.
Conduct exploratory analysis to identify opportunities for new features, model their impact, and drive performance improvements.
Analyze product performance, user behavior, and interactions to showcase product value.
Define, measure, and build monitoring tools for key KPIs.
Visualize insights clearly to improve understanding and decision-making.
Support roadmap planning by identifying trends, gaps, and opportunities.

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.

We're looking for a talented Robotics Algorithm engineer to join our team and develop cutting-edge perception and localization capabilities for autonomous systems. Design, develop, and optimize algorithms for SLAM, Mapping, Localization, Sensor Fusion, and State Estimation. Build robust solutions using data from LiDAR, Cameras, IMU, GNSS, and Odometry sensors. Implement and improve graph-based optimization and probabilistic estimation algorithms. Integrate Machine Learning and computer vision techniques into perception and navigation pipelines. Develop, TEST, and validate algorithms in simulation and real-world environments. Optimize software for Real-Time performance on Embedded and edge computing platforms.

As a Technical Policy researcher, you'll tackle some of the biggest and most complex questions of AI development and deployment. Your work outlining problems, solutions and principles for governments, frontier labs, and deployers will shape the emerging field of AI security.

Representative projects:

Threat modeling and fleshing out in what specific way could a strong cyber-capable model cause harm.

Taxonomies for dangerous AI capabilities or mitigations.

Policy proposals for models' refusal policy (which prompts models should refuse to follow).

Following up on publications and news on AI policy, AI risks and mitigations, and technical AI research.

Writing academic papers and blog posts detailing our research around evaluation theory or mitigation recommendations.

Publishing your research and/or delivering research to our customers.

As an AI Researcher on Research group, youll research, develop and productionize LLMs powered applications and AI-agents. Youll partner closely with Product and Engineering to turn open-ended data-security challenges into measurable experiments and shipped features. Youll own the end-to-end lifecycle - from problem framing and data strategy to evaluation, deployment, and ongoing monitoring - helping customers discover, protect, and govern their data at scale.



What Youll Do

Responsible for the end-to-end research process. This includes identifying problems, preparing data, tuning and developing models, deploying to production, and analyzing outcomes.
You will be a hands-on domain leader, laying the foundations of our data science workflows and algorithms. This is an excellent opportunity to work with endless amounts of data and creatively generate insights that will increase the ability to classify tons of data.
Develop, evaluate, and maintain deep learning and NLP solutions to enhance core capabilities in sensitive data classification.
Design and architect production-grade agentic workflows. Establish rigorous evaluation pipelines to benchmark agent accuracy, latency, and cost, ensuring reliable, scalable solutions for real-world customer problems
Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification.
Join a full stack AI group, including research engineering, MLEs, data operations, and security researchers. You will accelerate the path from research to production, ensuring results are both quick and precise.

We are looking for
For our Aerospace Division site in Haifa, we are looking for an Architect with extensive experience in signal processing and 3D imaging to join a multidisciplinary systems and algorithms group developing an innovative and groundbreaking Imaging Radar solution for airborne platforms
This is a unique opportunity to be part of the development of advanced defense technologies, work on complex multidisciplinary systems, and contribute to cutting-edge radar imaging capabilities with real operational impact
In this role you will
Develop and implement advanced radar signal processing algorithms and 3D image reconstruction capabilities
Define, execute, and analyze laboratory, field, and flight experiments
Analyze data and derive conclusions for implementation within the product
Develop and operate dedicated simulation tools for algorithmic research
Integrate complex systems
Work within a multidisciplinary team environment
Collaborate closely with technical management, mechanics, software, hardware, operational research, system engineering, and product management teams.

The GNC Team Lead will oversee a small, high‑impact group responsible for developing and validating advanced Guidance, Navigation, and Control (GNC) algorithms within our companys defense‑technology product line. This role combines hands‑on technical expertise with early-stage leadership responsibilities, managing simulation specialists while driving innovation, system performance, and reliability.
The ideal candidate brings strong domain knowledge in GNC, autonomy, or aerospace systems, alongside proven ability, formal or informal, to guide and mentor technical staff in a fast‑paced startup environment.
Why Join us?
This is a unique opportunity to be at the heart of a defense-tech startup during its most exciting growth phase!
Responsibilities
Leading simulation engineers and providing technical direction, mentoring, and day‑to‑day guidance.
Developing and validating GNC algorithms, including guidance laws, navigation filters, and control loops.
Maintaining and improving high‑fidelity simulation environments that support robust modeling and system analysis.
Collaborating with software, hardware, and system engineering teams to integrate algorithms into the full system architecture.
Reviewing technical outputs, refining methodologies, and ensuring high-quality documentation and analysis.
Supporting field tests, analyzing performance data, and iterating on algorithms based on real-world results.
Identifying technical risks, opportunities, and long-term development needs within the GNC domain.

our company is looking for a talented Computer Vision Researcher to join advanced R&D activities for defense electro-optical systems. The role includes research, development, and Real-Time implementation of computer-vision algorithms for operational systems. What you will do: Develop and implement computer-vision algorithms for Real-Time electro-optical systems. Work with video streams, object detection, tracking, stabilization, calibration, and sensor fusion. Integrate algorithms into operational systems and support lab, integration, and field testing.

We are looking for a Senior Algorithm Engineer to lead the design and development of large scale ML inference and data processing systems in production. In this role, you will work at the intersection of algorithms, data systems, and machine learning infrastructure, building scalable and efficient solutions that support high throughput model inference and large scale data processing. The position involves close collaboration with ML researchers and infrastructure teams to design robust systems that power production ML workloads.
What will your job look like:
Design and optimize algorithms and pipelines for large scale model inference
Build scalable systems for high throughput data processing and streaming
Develop data transformation and preprocessing components for ML workloads
Improve performance, efficiency, and reliability across distributed inference systems
Work closely with ML researchers, infrastructure, and platform teams
Drive architectural decisions for production ML and data systems.

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

Required Experienced Deep Learning Algorithm Developer - Perception Solutions
Join our Perception Solutions team, working on significant computer vision challenges and solving them with cutting-edge neural networks combined with heuristic solutions.
In this role, you will join at the beginning of an end-to-end development cycle, leveraging advanced approaches to enable direct vision modeling beyond traditional image-processing pipelines and help advance the next generation of autonomous driving technology.
What will your job look like:
Contribute to building a new deep learning project from scratch, with real impact on production systems.
Work on end-to-end model development, including problem formulation, data understanding, model design, training, evaluation, optimization, and deployment.
Develop and train state-of-the-art deep learning models for computer vision tasks.
Explore and define the best technical approach in an open, research-driven environment, where solutions are not predefined.
Tackle real-world challenges where model performance is critical and directly impacts product capabilities.