לוח משרות דרושים NLP/Machine Learning, לחיפוש זה נמצאו 74 משרות

Join our team as a Machine Learning Engineer and help shape the future of on-device AI. You'll research, design, and deploy cutting-edge deep learning models optimized for our silicon edge devices, working across the full ML lifecycle alongside hardware, software, and product teams.

We are looking for a talented and motivated Machine Learning Engineer to join our team. You will work within a collaborative, research-driven engineering culture that values innovation and rigor, with the opportunity to build impactful AI products deployed at scale on real devices. We offer competitive compensation, benefits, and opportunities for professional growth.

Responsibilities
Research and design state-of-the-art deep learning models optimized for resource-constrained our silicon edge devices.
Drive projects across the full ML lifecycle, from ideation and experimentation to production deployment.
Collaborate closely with cross-functional teams including hardware, software, and product.
Continuously evaluate and adopt new techniques to improve model performance and efficiency on-device.

Play a part in shaping the future of human communication technology. Contribute to a unique multidisciplinary system that models and understands human interaction, redefining what's possible with computer vision, physics, and signal processing at the edge.

In this role, you'll be at the forefront of a one-of-a-kind technical challenge, developing and implementing novel methods for processing and enhancing a proprietary sensor that models human communication. You'll work hands-on with exclusive data: designing the algorithms that process it, and defining the metrics that evaluate and drive its continuous improvement.

Your insights will carry real weight, directly informing sensor decisions and shaping the architecture of the broader system. You'll lead multi-level research efforts to advance a truly unique sensor, drawing on a rich and diverse technical toolkit spanning signal processing, computer vision, physics, and state-of-the-art deep learning. You'll own proprietary data collections using high-end computer vision techniques, studying signals from their raw-level behavior all the way through to their top-level impact on product performance.

This is a role that lives at the intersection of deep research and real-world impact. You'll conduct cutting-edge investigations and translate your findings directly into product outcomes, influencing decisions across the full stack, from hardware choices and algorithmic pipelines to the features that reach the final product.

Responsibilities
Develop and implement novel algorithms for modeling and understanding human communication, combining 2D/3D computer vision, signal processing, and deep learning.
Work with unique proprietary datasets - design large-scale data processing pipelines, define quality metrics, and provide actionable feedback to improve data collection and labeling workflows.
Devise and implement rigorous evaluation frameworks to measure model and data quality, and drive continuous improvement across the system.
Design neural network architectures optimized for SOTA accuracy and computational efficiency.
Stay current with the latest research across computer vision, signal processing, and efficient ML; evaluate and integrate relevant advances into the team's work.
Contribute to internal tooling and best practices for reproducible, scalable ML research and deployment.

We are looking for a talented and curious ML Data Scientist to join our growing Machine Learning team in Herzliya.

In this role, you will help create the full data lifecycle that underpins our models: from designing what data we collect, through curation and quality monitoring, to running rigorous experiments that drive model improvements. You will work closely with other ML and Data Engineering teams to ensure our models are trained on the best possible data, reaching the best accuracy, and that we deeply understand when and why they don't perform as expected.
Responsibilities
As an ML Data Scientist on this team, you will play a central role in shaping the data that powers our ML models. You will:
Investigate model failures - identify patterns, hypothesize root causes, and work with the team to implement fixes
Own data curation: evaluate, clean, and curate datasets to maximize model training quality
Design and execute experiments end-to-end: from defining the question and data collection escort, through analysis and statistical validation, to presenting clear conclusions and driving implementation
Define data collection strategies - collaborate with others to decide what data we should be collecting and why
Design and maintain monitoring solutions with others to ensure ongoing data quality and integrity at scale

We are looking for an experienced NLP Data Science Team Leader to lead a team of talented NLP Data Scientists and drive the development of cutting-edge NLP solutions at scale. This role combines hands-on technical leadership, people management, and strategic influence over product and research directions.



Responsibilities

Lead and grow a team of NLP Data Scientists
Manage, mentor, and support team members professional development
Foster a culture of excellence, ownership, and continuous learning
Own end-to-end delivery of NLP solutions
Oversee algorithmic features from ideation through research, development, and production
Ensure high-quality, scalable, and maintainable solutions
Drive technical direction and innovation
Guide research efforts and evaluate new NLP/ML technologies
Translate business needs into impactful NLP solutions
Collaborate cross-functionally
Work closely with Product, Engineering, and Business stakeholders
Align team priorities with company goals and product roadmap
Maintain hands-on involvement
Contribute to architecture, modeling, and critical algorithmic challenges
Review code, experiments, and methodologies
Scale impact
Improve processes, workflows, and best practices for research and production
Ensure efficient use of large-scale data and infrastructure

We are looking for a highly skilled Senior Machine Learning Engineer to lead our transition from on-demand, third-party LLM APIs to a fully self-hosted, scalable model ecosystem.
Our core product is an advanced, agentic support chatbot capable of complex reasoning, API tool calling, database lookups, and orchestrating specialized Small Language Models (SLMs) for targeted NLP tasks. As we scale, our current deployment infrastructure (AWS SageMaker) is becoming unsustainable. You will be responsible for architecting, deploying, and optimizing an infrastructure capable of supporting 50 to 100 distinct models ranging from 100M to 70B parameters.
What Youll Do:
Inference Optimization: Deploy and manage large-scale models using high-performance inference engines (like vLLM) to ensure low latency and high throughput for our agentic chatbot.
Agentic Workflows: Develop and refine the chatbot's agentic capabilities, ensuring reliable tool-use, routing, and interactions between massive LLMs and specialized SLMs.
Model Fine-Tuning: Design and execute fine-tuning strategies to improve model accuracy on specific domain tasks and tool-calling execution.
Rigorous Evaluation: Build comprehensive offline and online evaluation frameworks to constantly measure model performance and business impact through structured A/B testing.