לוח משרות דרושים NLP/Machine Learning, לחיפוש זה נמצאו 68 משרות

As a Senior AI&ML Researcher in our Workforce Management group, you will be part of a cross-sectional team working at the intersection of machine learning, GenAI, agentic AI, ML-Ops and Operations Research. You will develop the next generation of our companys Workforce Management solution for our customers contact centers - forecasting work volume, scheduling agent shifts, managing time-off requests, and owning the full lifecycle of the work schedule, in a high-stakes production environment serving many customers. Our solution has been recognized as the market leader for over 10 years.
How will you make an impact?
Developing end-to-end ML systems, tailored to specific project needs, to train and serve production-level models in a high-stakes environment.
Deploying GenAI and agentic AI systems to customers in production, improving on existing solutions or creating new services from scratch.
Designing and building agentic AI flows - tool use, multi-step reasoning, and orchestration.
Forecasting work volume and optimizing shift schedules using time-series methods and mathematical optimization.
Integrating new features and solutions into large existing software systems, stringing multiple disciplines together.
Running unstructured evaluation processes - finding noteworthy phenomena, experimenting, and feeding conclusions back to the team.
Owning projects end-to-end, leading team members and colleagues to efficient planning and delivery.

we are looking for a Director of AI.
The Director of AI will lead the companys AI organization, including algorithm development teams, embedded algorithm engineers within product squads, and the Data Operations team.
This role combines strategic leadership with execution ownership, driving the development, deployment, and continuous improvement of AI-powered products across power transmission, border security, and critical infrastructure monitoring.
The Director of AI is accountable not only for algorithm innovation, but also for ensuring successful production deployment and measurable customer impact. This leader will establish a customer-first culture across the organization, aligning AI development priorities with customer needs, product objectives, and business outcomes.
The ideal candidate is a visionary yet execution-oriented leader who can bridge cutting-edge AI research with scalable production systems, build high-performing teams, and deliver measurable customer value.
Success in this role will be measured not only by algorithm performance, but by the ability to deliver AI capabilities into production and generate measurable value to our customers.
What Youll Do:
Lead the AI group, including algorithm development teams, embedded algorithm engineers, and data operations.
Build and mentor high-performing teams, fostering a culture of ownership, collaboration, continuous improvement, and customer focus.
Define and execute the AI roadmap in alignment with company strategy, customer needs, and product objectives.
Lead the development and deployment of AI, Machine Learning, Deep Learning, and Signal Processing solutions.
Own the full AI lifecycle, from research and experimentation through production deployment, monitoring, and continuous optimization.
Lead the Data Operations function, ensuring efficient annotation, labeling, and quality processes that support AI development.
Partner closely with Product, Engineering, and business leaders to maximize AI impact across the organization.
Engage with customers and stakeholders to understand challenges, identify opportunities, and drive measurable business value.
Communicate AI strategy, progress, opportunities, and risks to executive leadership.
Contribute to company strategy, product direction, and technology leadership.

We are looking for a Software Engineer specializing in ML Systems Engineering to join Development department.
While vision and language models have become increasingly commoditized, proprietary deep learning models are unique, fast-evolving, and deployed in live trading across the worlds most efficient and sophisticated financial markets. Operating in this environment presents distinct scaling challenges and continuous opportunities for optimization. Success in this role requires first-principles thinking and a deep understanding of the engineering trade-offs behind high-performance DL systems.
This is a pivotal role within engineering organization. You will work closely with researchers and engineers across the company, running deep learning models on massive compute clusters and adapting them for production serving under strict and non-trivial constraints.

We are looking for an experienced Data Science Manager to lead and grow our Data Science team. This is a managerial role focused on leading a team of Data Scientists while driving the strategy, execution, and delivery of impactful AI and ML initiatives across our SaaS platform.

You will be responsible for both people leadership and technical direction - ensuring high standards of execution, mentoring team members, and aligning data science efforts with product and business goals. This role requires a strong hands-on background combined with proven team management experience.

What You Will Do
Lead, mentor, and manage a team of 7-10 Data Scientists, fostering a culture of ownership, excellence, and continuous learning.
Own the teams roadmap, prioritization, and delivery of AI initiatives.
Provide technical and architectural guidance across projects.
Drive end-to-end execution of data science solutions - from problem definition and research to modeling, evaluation, deployment, monitoring and enhancement cycles.
Collaborate closely with Product, Engineering, and Business stakeholders to translate business needs into scalable AI solutions.
Ensure production-grade standards, model performance monitoring, and continuous improvement.
Stay up to date with advances in machine learning, GenAI, and LLM technologies, and translate them into business impact.
Take responsibility for hiring, onboarding, and developing top data science talent.

we are looking for a Researcher.
As an ML researcher you will collaborate with our R&D team to execute live trading strategies. If you are looking to make an impact by putting into practice successful ideas and seeing immediately the outcome, make influence on Finals financial performance this is a great opportunity.
In this role you will:
Mange and lead independent research applying ML/DL methods to a wide variety of datasets.
Creatively find new trading strategies
Work with other team members to optimize Finals Algorithms

Required ML-Engineering Lead
Were seeking passionate professionals who thrive in a fast-paced, creative, and collaborative environment - those who want to be part of the next generation of airspace security innovation.
Join us and help make the world a safer place.
Work with the worlds leading cyber-takeover counter-drone technology provider and shape the future of safe airspace.
What You Will Do:
End-to-End Ownership: Lead the full technical execution of ML projects, ensuring every stage-from data acquisition to deployment-meets our rigorous standards.
R&D Collaboration: Partner closely with R&D departments to design data collection strategies and integrate ML-based tools and agents into their specialized workflows.
Versatile Implementation: Develop models and intelligent systems for a variety of use cases, ranging from real-time field performance to autonomous research-support tools.
Technical Authority: Act as a founding voice for ML implementation and strategy within the CTOs office.

Are you a master of the AI lifecycle who can thrive at the intersection of deep learning research, cybersecurity and large-scale production systems? Do you possess the rare ability to jump into a complex technical crisis, diagnose a bottleneck in a Small Language Model (SLM), and lead a team to a production-ready solution?
As a Distinguished AI/ML Architect, you will be the premier technical authority across the Cortex AI/ML organization. You will serve as the "force multiplier" for multiple AI & ML teams, ensuring that our AI strategy - from endpoint-deployed DL/ML models to cloud-scale agentic products - is executed with world-class precision. You will operate as the primary technical architect and hands-on leader for our most ambitious and difficult initiatives.
Key Responsibilities
Operate at the forefront of AI and cybersecurity, leveraging vast datasets to design and deploy innovative defense mechanisms.
Provide horizontal technical leadership across endpoint, cloud, and agentic AI teams to ensure architectural excellence.
Oversee the design and deployment of different model architectures to guarantee scalability and high-performance standards.
Spearhead high-difficulty initiatives and new research frontiers, moving them from ambiguity to production.
Resolve complex technical bottlenecks across the stack, optimizing model efficiency and runtime performance.
Align research and engineering efforts to transform advanced models into robust, production-grade products.

our company's ML Platform group builds and operates the core infrastructure that powers large-scale AI workloads across on-prem bare-metal GPU clusters and multi-cloud environments. Our goal is to deliver the modern infrastructure and tooling that accelerates our company's entire algorithm development lifecycle - from a researcher's first experiment to a production deployment.
We are a small, independent group of engineers with diverse skills across software, infrastructure, and systems. We set the standards, build the cross-company products, and take end-to-end ownership of everything we ship.
What will your job look like?
Design, develop, and maintain the Python framework that enables algorithm developers across our company to train, validate, quantize, and deploy deep learning models - locally, on-prem, and across cloud providers - through a single unified interface
Build high-performance data streaming libraries that feed large-scale distributed training pipelines in Rust with Python interfaces
Set the standard for reliable, reproducible research at scale - experiment tracking, configuration management, checkpoint handling, and multi-node training
Work directly alongside algorithm researchers to understand friction, propose solutions, and ship them - without layers of process in between
Contribute to open source when the right fix/feature belongs upstream.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
** The role includes working on-site at our Jerusalem office several days per week.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.
This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C++, ML infrastructure, model integration, performance optimization, and production delivery.
What will your job look like:
Lead end-to-end development of features - from design and implementation to integration, testing, and deployment
Build ML pipelines for data-based diverse dataset creation and efficient model inference
Design data selection and sampling strategies to ensure coverage of rare and critical scenarios
Partner with algorithm teams to translate model weaknesses into data curation criteria
Develop validation and diagnostics to measure dataset quality-not just pipeline health but training effectiveness
Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing
Bring models from research/prototype stage into robust, production‑ready deployments
Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments
Contribute to deployment flows (e.g., model conversion, profiling, optimization)
Build and improve CI/CD pipelines, automated testing, and development workflows.

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.

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed at our company.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We are seeking a motivated MSc student to join our R&D team as a Machine Learning Engineer focusing on medical image processing (CT, MRI). In this role, you will support the development and optimization of deep learning models for image segmentation and analysis, leveraging U-Net and 3D U-Net architectures.
This is a hands-on opportunity to work on real-world clinical data and contribute to next-generation solutions for diagnostic and procedural planning workflows.
How you will make an impact:
Model Development:
Assist in designing and implementing deep learning models for medical image segmentation using U-Net, 3D U-Net, and nnU-Net frameworks.
Support optimization of models for volumetric CT/MRI datasets.
Data Handling & Processing:
Develop preprocessing pipelines (normalization, augmentation, resampling).
Integration & Experimentation:
Support integration of models into research pipelines using tools like MONAI and 3D Slicer.
Run experiments, evaluate model performance, and document results.
Collaboration:
Work closely with engineers, data scientists, and clinical teams.
Participate in technical discussions and contribute ideas for improving model performance.
Research & Innovation:
Stay updated on state-of-the-art methods in medical imaging AI and segmentation.
Explore improvements in model architecture and training strategies.

Required Research Scientist - Audiovisual Understanding, Model Foundations
Team & role
The Core Generative AI team is a unified group of researchers and engineers dedicated to developing our generative foundational models that serve LTX Studio, our AI-based video creation platform. Our focus is on creating a controllable, cutting-edge video generative model by merging cutting-edge algorithms with exceptional engineering. This involves enhancing machine learning components within our sophisticated internal training framework, crucial for developing advanced models. We specialize in both research and engineering that enable efficient and scalable training and inference, allowing us to deliver state-of-the-art AI-generated video models.
As a Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.
What you will be doing:
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.