MLops Engineer

לפני 1 שעות

MLops Engineer

חברה חסויה

Location: Herzliya

Job Type: Full Time

Play a part in shaping the future of human-computer interaction. As an MLOps Engineer, you will be the backbone of the machine learning infrastructure that powers our speech, audio, and conversational AI teams - ensuring their models are trained on the best possible data.
You will bridge the gap between research, data science, and engineering, owning the full ML lifecycle from large-scale data pipelines and distributed GPU training through to low-latency, high-fidelity inference and optimization. You'll partner closely with Audio ML Engineers, Speech ML Engineers, and ML Data Scientists to remove friction across their workflows and accelerate the path from research to product.

The MLOps Engineer will drive end-to-end quality and operational excellence across data ingestion, model training, deployment pipelines, and MLOps tooling for our speech and audio ML platforms. This hire will build, deploy, and optimize production-grade systems with a strong emphasis on scalable, GPU-accelerated infrastructure. You will own the training infrastructure that powers distributed and self-supervised model training on HPC and Slurm-managed clusters, as well as the inference pipelines that bring low-latency, high-fidelity audio and speech models to production. You will establish standard methodologies for model integration, deployment, monitoring, and reproducibility using CI/CD principles.

Responsibilities
Design, build, and operate large-scale data pipelines for proprietary audio and speech datasets - supporting curation, quality monitoring, and validation at scale alongside our ML Data Science team.
Partner closely with Audio ML Engineers, Speech ML Engineers, ML Data Scientists, and product teams to define metrics, gather requirements, and bring new capabilities to life.
Build and operate distributed GPU training workflows, including job scheduling and resource management on Slurm-managed HPC clusters, for both supervised and self-supervised methods.
Optimize model inference for low latency and high-fidelity streaming across serving environments, including optimization for Apple silicon.
Design and maintain automated pipelines for model training, evaluation, versioning, and deployment, with special attention to speech, audio, and signal-processing workflows.
Identify and resolve bottlenecks in ML and data workflows, improving system reliability, latency, and throughput at scale.

Requirements:
Minimum Qualifications
3 years in software engineering with demonstrated experience in large-scale software system design and implementation.
Bachelor's Degree in Software Engineering, Computer Science, Electrical Engineering, Statistics, Machine Learning, Operations Research, or a related field.
Proven track record of shipping and maintaining production-grade ML systems end-to-end.
Hands-on experience with GPU-based model training and inference, including distributed/multi-node training.
Experience operating workloads on HPC environments and job schedulers such as Slurm.
Proficiency in Python and familiarity with deep learning frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications
Experience supporting speech and audio ML pipelines (e.g., ASR, TTS, speaker recognition, voice isolation, generative speech) and large-scale audio data processing.
Experience with infrastructure for self-supervised and large-model training.
Deep familiarity with GPU performance tuning, mixed-precision training, and distributed training frameworks.
Familiarity with data quality frameworks, model monitoring, drift detection, and observability practices in production
Experience optimizing models for on-device or Apple silicon inference

This position is open to all candidates.

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8678831

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לפני 21 שעות

Audio Machine Learning Engineer

חברה חסויה

Location: Herzliya

Job Type: Full Time

We are looking for a talented and curious Audio Machine Learning Engineer 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.

Redefine the future of human-computer interaction and the way people communicate. Contribute to products that shape mobile computing and create breakthrough technologies in the audio domain.
In this role, you will push the boundaries of audio solutions across the full stack - from data pipelines and model training to optimization for our silicon. You'll collaborate with world-class researchers and engineers to ship technology that reaches hundreds of millions of users, while upholding our unwavering commitment to privacy.

Responsibilities
Work with unique, proprietary datasets - developing algorithms to process them and devising metrics to evaluate and improve quality.
Design and implement machine learning models focused on the audio domain, for low-latency feedback and high-fidelity streaming.
Drive data quality insights and influence the design of our end-to-end system.
Conduct both cutting-edge research and product-oriented development.
Collaborate closely with researchers, engineers, and product teams to bring new capabilities to life.

Requirements:
Minimum Qualifications
BS or MS in CS, EE, or related degree.
3+ years of industry experience in deep learning through applied research roles.
Deep understanding of Machine Learning fundamentals.
Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, or JAX).
Collaborative skills for dependable and consistent steering of novel research alongside fellow teams.

Preferred Qualifications
Ph.D. in CS, EE or a related field.
Advanced background and hands-on experience in speech ML technology (e.g., multi-modals, speaker embeddings, voice isolation, ASR, multichannel sensor fusion, generative speech).
Background in digital signal processing (DSP) for audio signals.
Experience training large models using both supervised and self-supervised methods.
Track record of shipping ML features in a production environment.

This position is open to all candidates.

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8677379

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לפני 21 שעות

Machine Learning Engineer - Speech

חברה חסויה

Location: Herzliya

Job Type: Full Time

Play a part in shaping the future of human-computer interaction. Contribute to products that are redefining mobile computing and creating breakthrough technologies in conversational AI, speech recognition, and natural language understanding and generation.

We are seeking a passionate and experienced Machine Learning Engineer to join our team. In this role, you will push the boundaries of on-device speech recognition and NLP, working across the full stack - from data pipelines and model training to optimization for our silicon. You'll collaborate with world-class researchers and engineers to ship technology that reaches hundreds of millions of users, while upholding our unwavering commitment to privacy.

Responsibilities
Work with unique, proprietary datasets - developing algorithms to process them and devising metrics to evaluate and improve quality.
Design and implement machine learning models spanning speech recognition and NLP domains.
Drive data quality insights and influence the design of our end-to-end system.
Conduct both cutting-edge research and product-oriented development.
Collaborate closely with researchers, engineers, and product teams to bring new capabilities to life.

Requirements:
Minimum Qualifications
M.Sc. in Computer Science or a related field, or equivalent practical experience.
Deep understanding of Machine Learning fundamentals.
Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, or JAX).
3+ years of industry experience in deep learning through applied research roles.
Hands-on experience with the full deep learning lifecycle at scale, including dataset curation, architecture design, distributed training, error analysis, and production deployment.
M.Sc. in Computer Science or a related field, or equivalent practical experience.

Preferred Qualifications
Ph.D. in Computer Science or a related field.
Advanced background and hands-on experience in speech technology (e.g., ASR, TTS, speaker recognition).
Background in NLP, including language modeling, text processing, and linguistic understanding.
Experience training large models using both supervised and self-supervised methods.
Track record of shipping ML features in a production environment.

This position is open to all candidates.

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8677375

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לפני 21 שעות

Machine Learning Engineer - Edge AI & On-Device Optimization

חברה חסויה

Location: Herzliya

Job Type: Full Time

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.

Requirements:
Minimum Qualifications
M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field - or equivalent practical experience.
Strong foundation in deep learning theory and hands-on experience training large-scale models.
Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow/JAX.
Hands-on experience with model compression and optimization techniques (quantization, pruning, distillation, etc.).
Familiarity with on-device inference frameworks such as Core ML, TensorFlow Lite, ONNX Runtime, or TensorRT.
Experience working with multimodal data (e.g., images, audio, time-series, or sensor fusion).
Strong analytical and problem-solving skills; ability to translate research ideas into production-quality code.

Preferred Qualifications
Experience deploying models to embedded systems, mobile devices, or custom silicon (NPU/DSP).
Familiarity with hardware-aware neural architecture search (NAS) or AutoML techniques.
Exposure to low-level optimization techniques such as mixed-precision training or operator fusion.
Hands-on experience with our Neural Engine and Core ML for on-device inference.
Publications or open-source contributions in efficient deep learning or edge AI.
Experience with MLOps workflows and CI/CD pipelines for model development.

This position is open to all candidates.

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8677372

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לפני 21 שעות

Machine Learning Data Scientist

חברה חסויה

Location: Herzliya

Job Type: Full Time

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

Requirements:
Minimum Qualifications
M.Sc. in Computer Science, Electrical Engineering, Computational Biology/Neuroscience, Mathematics, Statistics, or a related field.
5+ years of industry experience in applied machine learning, data science, or a related field.
Strong hands-on experience with Python, PyTorch and SQL for large-scale data analysis and pipeline development.
Hands-on experience with the full ML experimentation cycle: problem definition, data collection, statistical analysis, and conclusion-driven iteration.
Proven ability to analyze model failures and translate findings into concrete improvements.
Strong analytical thinking and ability to independently define and drive research directions.
Excellent cross-functional communication skills - ability to work effectively with other ML and Data Engineers.

Preferred Qualifications
Experience with applied speech, audio or signal processing ML systems.
Experience with data-efficient training strategies.
Experience with continual or online learning.
Familiarity with data quality frameworks, monitoring pipelines, and data validation at scale.
Strong statistical foundation - hypothesis testing, uncertainty quantification, evaluation metrics design.
Ph.D. n Computer Science, Electrical Engineering, Computational Biology/Neuroscience, Mathematics, Statistics, or a related field.

This position is open to all candidates.

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8677335

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לפני 21 שעות

Machine Learning Engineer - Vision

חברה חסויה

Location: Herzliya

Job Type: Full Time

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.

Requirements:
Minimum Qualifications
M.Sc. in Computer Science, Electrical Engineering, or a related field, with a thesis in AI, computer vision, data science, or an equivalent discipline.
At least 3 years of hands-on experience in machine learning.
At least 3 years of hands-on experience in image processing and computer vision.
Strong foundation in deep learning theory and practical experience training large-scale models.
Proficiency in Python and deep learning frameworks such as PyTorch.
Background in signal processing and physics-based modeling.
Practical experience with large-scale data processing, pipeline design, and performance evaluation.
Experience utilizing modern frameworks and keeping up with recent research.

Preferred Qualifications
Knowledge and experience with 3D data (e.g., point clouds, depth sensing, 3D reconstruction).
Ph.D. in a relevant field.
Hands-on experience with model compression techniques (quantization, pruning, distillation).
Experience with MLOps workflows and CI/CD pipelines for model development.

This position is open to all candidates.

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8677363

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20/05/2026

Machine Learning Research Engineer - Wireless Technologies & Ecosystems

חברה חסויה

Location: Herzliya

Job Type: Full Time

We are seeking a Machine Learning expert to join our wireless FW software group and explore innovative applications of ML algorithms in embedded wireless systems and protocols. This role focuses on cutting-edge research to integrate machine learning into wireless firmware architectures as well as protocol design, validation, and performance optimization. The position emphasizes experimental research, algorithm development, and proof-of-concept implementations in the wireless FW domain. This role offers the opportunity to develop novel solutions that bridge the gap between theoretical machine learning capabilities and practical wireless system implementations.
Responsibilities:
Research & Development: Design, develop, and evaluate machine learning algorithms optimized for real-time wireless communication systems operating under strict real-time, power and computational constraints.
Protocol Innovation: Create novel wireless protocols that intelligently incorporate ML techniques for enhanced performance, efficiency, and adaptability.
Algorithm Optimization: Adapt existing wireless algorithms (e.g. Link Quality, QoS, Scheduling etc) by integrating ML approaches while maintaining real-time performance requirements.
Data Collection & Analysis: Gather, analyze, and curate statistics from existing wireless devices and networks to enable ML model training and validation. Design and implement data collection frameworks for various wireless environments and use cases.
System Integration: Develop lightweight ML models suitable for deployment on resource-constrained wireless devices, including edge computing scenarios.
Performance Analysis: Conduct comprehensive performance evaluations through simulation, theoretical analysis, and experimental validation.
Research Publication: Publish findings in top-tier conferences and journals, and present research at industry conferences.
Collaboration: Work closely with hardware engineers, system architects, and product teams to ensure research translates into practical solutions.
Technology Scouting: Stay current with emerging trends in ML, wireless communications, and edge computing technologies.

Requirements:
Minimum Qualifications
Minimum: Master's degree (MSc) in one of the following fields: Computer Science or Mathematics with specialization in Machine Learning, Signal Processing and Telecommunications Engineering.
Real-time Systems: Experience in real-time computing constraints and low-latency system design.
Machine Learning: Deep understanding of ML algorithms, particularly those suitable for real-time applications (online learning, federated learning, reinforcement learning, neural networks).
Wireless Communications: Strong foundation in wireless communication principles, protocols.
Programming: Proficiency in Embedded C, Python, MATLAB, C++, and ML frameworks.
Optimization: Experience with convex optimization, resource allocation algorithms, and constraint satisfaction problems.
Research Experience: Demonstrated track record of independent research through publications, patents, or significant project contributions.
Knowledge of edge computing and distributed ML systems is advantageous.
Personal Attributes: Self-Motivated: Ability to work independently, set research priorities, and drive projects from conception to completion.
Analytical Thinking: Strong problem-solving skills with ability to tackle complex, multi-disciplinary challenges.
Innovation-Oriented: Creative approach to research with ability to think outside conventional boundaries.
Communication Skills: Excellent written and verbal communication skills for technical documentation and presentations.
Collaborative Spirit: Ability to work effectively in cross-functional teams while maintaining independent research focus.

Preferred Qualifications
Ph.D. in related field.

This position is open to all candidates.

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8659163

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20/05/2026

AI Systems & Applications Engineer

חברה חסויה

Location: Herzliya

Job Type: Full Time

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

Requirements:
Minimum Qualifications
BSc in Computer Science, Software Engineering, or related field - or equivalent industry experience.
Strong programming, system design, and API design skills with a focus on scalability and production-readiness.
Proficiency in Python for automation, API development and pipeline engineering.
Experience building automation frameworks, internal developer tools, and shared platforms at scale.
Solid understanding of prompt engineering, retrieval strategies, context management, and model orchestration.
Hands-on experience building and deploying LLM-powered systems: agentic pipelines, RAG, tool-use, and function-calling.
Strong debugging skills across the full AI stack; familiarity with LLM safety and responsible AI practices.
Experience designing and running AI evaluations - automated and human-in-the-loop - and embedding quality gates into CI/CD release workflows.

Preferred Qualifications
Experience leading projects end-to-end - from initial scoping and stakeholder alignment through delivery- coordinating across engineering, product, design, and domain teams.
Practical systems management experience: configuration management, dependency resolution, and deployment tooling across cloud and on-prem environments.
Ability to design sustainable automation systems serving a large, diverse engineering user base.
Hands-on experience with orchestration frameworks and managing the full development lifecycle of complex, multi-component systems.
MA in Computer Science, Software Engineering, or related field.

This position is open to all candidates.

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8659216

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14/05/2026

Senior Machine Learning Engineer (MLE)

חברה חסויה

Location: Herzliya

Job Type: Full Time

At our company, we see the world of cybersecurity differently. Instead of chasing threats, we believe the most practical approach is protecting data from the inside out. Weve built the industrys first fully autonomous Data Security Platform to help our customers dramatically reduce risk with minimal human effort.
At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details. Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
Responsibilities
Design and Build ML Infrastructure: Develop and maintain scalable, production-ready infrastructure for both traditional ML (anomaly detection, user behavior analytics) and LLMs across enterprise environments.
Optimize Model Performance: Analyze and optimize LLM and ML performance using techniques like knowledge distillation, quantization, and efficient data structures to boost efficiency and lower resource costs.
Deploy and Integrate: Collaborate heavily with software and data engineers to integrate models into production pipelines, cloud-native environments, and on-premises workflows.
Drive MLOps & Tooling: Manage the complete model lifecycle (monitoring, retraining, deployment) and actively build custom tools from scratch to improve the team's ML workflows.
Elevate Engineering Standards: Perform rigorous code reviews, ensure robust Python production standards, and provide technical guidance to data scientists and junior engineers.
Cross-Functional Partnership: Partner with cybersecurity researchers and product teams to translate research insights and threat analysis features into highly performant production code.
Open-Source Engagement: Actively engage with the open-source community by contributing code and expertise to relevant ML/LLM projects.

Requirements:
Experience: 5+ years of experience in a backend, ML engineering, or MLOps role with a demonstrable track record of successfully deploying and maintaining code in high-volume production environments.
Programming Mastery: Strong proficiency in Python with a deep understanding of software engineering principles, design patterns, and debugging.
Applied ML/LLM Knowledge: Hands-on experience developing and fine-tuning models using frameworks like PyTorch, HF ecosystem and deepspeed, alongside practical experience with LLMs, prompt engineering, and vector databases.
Data & MLOps Infrastructure: Strong experience with Data/MLOps tools (e.g., MLflow, Airflow, DVC) and deployment technologies (CI/CD, Kubernetes, containerization).
Big Data & Cloud: Proficiency with big data platforms (like Databricks or PySpark) and a solid understanding of public cloud platform architectures.
Ownership: Exceptional problem-solving skills with the ability to take full ownership of complex tasks from the design phase through to full production implementation.
Advantages
Prior experience building cybersecurity, data protection, or enterprise threat detection products.
Familiarity with user behavior-based anomaly detection or metadata analytics.
Experience with advanced retrieval-augmented generation (RAG) frameworks.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8651740

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מייל

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שליחה

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לפני 1 שעות

Senior Audio - Voice Processing & Environmental Test Engineer

חברה חסויה

Location: Herzliya

Job Type: Full Time

We are looking for a highly skilled Senior Audio - Voice Processing & Environmental Test Engineer to join our team in Herzliya.

Responsibilities
Test and validate the performance and tuning of core voice processing blocks
Execute validation under diverse acoustic conditions, speaker configurations, and signal scenarios.
Collaborate with algorithm teams to provide data-driven feedback for tuning and optimization.
Conduct objective voice quality assessments using standardized metrics, including POLQA (ITU-T P.863) and PESQ (ITU-T P.862).
Organize and manage subjective "golden ear" listening panels to assess voice naturalness, intelligibility, and overall quality.
Define evaluation criteria and scoring methodologies aligned with industry standards and internal quality benchmarks.
Design and execute WER-based testing for scenarios involving voice transcription and speech recognition.
Correlate WER results with upstream audio processing quality to identify degradation sources.
Conduct testing in specialized laboratories that replicate real-world acoustic scenarios, including: Moving vehicles ,Noisy public environments - cafés, restaurants, crowded spaces Windy outdoor settings and Combined environmental stressors.
Measure and track Time to First Word (TTFW) and round-trip audio latency.
Establish performance baselines and monitoring frameworks for continuous tracking across firmware and software iterations.
Design and maintain automated test suites to detect audio artifacts - including glitches, pops, clicks, distortions, and dropouts.
Build regression frameworks that validate audio quality across new firmware and software updates.

Requirements:
Minimum Qualifications
BSc in Electrical Engineering, Computer Engineering, Acoustics, Audio Engineering, or a related field.
7+ years of experience in audio testing, voice quality evaluation, or acoustic system validation.
Proven experience working within or alongside professional audio/acoustic test laboratories.
Demonstrated ability to design repeatable, controlled test environments and methodologies.
Experience with both objective measurement tools and subjective listening evaluation protocols.
Strong system-level understanding with the ability to isolate quality issues to specific processing stages.
Deep understanding of audio signal processing fundamentals - frequency domain analysis, filtering, spectral characteristics, and time-domain behavior
Hands-on experience with voice quality measurement tools and standards (POLQA, PESQ, 3QUEST, ETSI standards).
Familiarity with HEAD acoustic test equipment - measurement microphones, artificial heads (HATS), mouth simulators, and anechoic/semi-anechoic chamber setups.
Strong proficiency in Python for test automation, data analysis, audio signal processing, and framework development.
Experience with audio acquisition systems, DACs/ADCs, and real-time audio streaming architectures.
Understanding of latency measurement methodologies in real-time audio systems.

Preferred Qualifications
MSc in Acoustics, Audio Signal Processing, Electrical Engineering, or a related discipline - considered a significant advantage.
Experience with speech recognition systems and WER evaluation methodologies.
Background in psychoacoustics or subjective audio evaluation research.
Experience with environmental simulation lab design and commissioning.
Knowledge of ITU-T P-series recommendations and ETSI test specifications.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8678752

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שליחה

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מודים לך שלקחת חלק בשיפור התוכן שלנו :)

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לפני 21 שעות

ML Research Engineer - Physics - Informed AI

חברה חסויה

Location: Herzliya

Job Type: Full Time

We are looking for an ML Engineer to join a research-oriented group developing physics-informed neural networks for advanced sensing and optical measurement systems. The role focuses on training, validating, and improving neural network models that combine data-driven learning with physical modeling, simulation, and experimental measurements.

Responsibilities
Develop, train, and evaluate neural network models for physics-based sensing and reconstruction tasks.
Incorporate physical knowledge into ML models through data generation, model architecture, loss functions, constraints, or regularization.
Work with simulated and experimental datasets, including data. preprocessing, augmentation, validation, and error analysis.
Build robust training pipelines using Python and modern ML frameworks such as PyTorch.
Compare model predictions against ground-truth data from simulations, optical experiments, or measurement systems.
Collaborate with physicists and optical engineers to understand underlying physical models and translate them into ML workflows.
Analyze model performance, identify failure modes, and improve generalization from simulation to real-world data.
Design experiments to evaluate model robustness, sensitivity, uncertainty, and accuracy.

Requirements:
Minimum Qualifications
MSc or PhD in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or a related field.
Hands-on experience with machine learning and deep learning.
Proficiency in Python and PyTorch or a similar deep learning framework.
Strong communication skills and proficiency in English.
Ability to work well in a collaborative, highly cross-functional, and fast-paced environment.

Preferred Qualifications
Solid understanding of physics and the ability to apply physical principles to machine learning problems.
Strong understanding of optimization, model training, validation, and debugging of neural networks.
Experience with scientific computing libraries such as NumPy, SciPy, pandas, or similar tools.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8677354

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