לוח משרות דרושים NLP/Machine Learning

We are seeking a highly motivated Senior Deep Learning Researcher to join our team! This is an outstanding opportunity to conduct impactful research and develop the next generation of large language model (LLM) inference algorithms. You will work on technologies that directly enhance NVIDIA's software, making the latest LLMs more efficient and accessible for users worldwide. By joining us, you will be part of a strategic effort to establish NVIDIA as the definitive platform for high-performance LLM inference. You will engage with skilled problem-solvers at NVIDIA and top organizations, crafting AI technology advancements.

What you'll be doing:
Research, invent, and implement groundbreaking algorithms for LLM inference to advance the state of the art in both low-latency and high-throughput scenarios.
Translate research into practical software solutions that directly impact NVIDIA's products and customers.
Collaborate with internal research, engineering, and product teams across the globe to drive the development of sophisticated inference technologies.
Analyze the performance of new algorithms on NVIDIAs latest hardware, identifying bottlenecks and opportunities for algorithmic optimizations.
Partner with leading scientific organizations and industry pioneers to remain at the forefront of technological advancements and integrate the latest innovations into practical applications.

Were on a mission to revolutionize how marketers, writers, and innovators create their marketing content. With tools like ChatGPT?? taking the world by storm, its clear that the spotlight is now shining on the Generative AI space. However, its ultimate hurdle is now a self-compounding problem: with infinite options for messaging now available to all marketers how do we know what will actually work? Your words matter, and Anyword was built to ensure that they resonate. Since 2021, weve been building a platform to help both the worlds largest brands and its next rising stars actually move, inspire, and drive their audiences forward. In reality, weve removed the uncertainty of writing performance copy, and are the first to bring copy intelligence into play. Weve combined our own language models, predictive analytics, custom AI, and branding-specific tools to help brands rise above the noise in ways they couldnt before. Weve built the brain behind all marketing messaging, no matter where it lives and how you create it (with AI or not). And now were looking to you to help change the world with us!
About the role Anyword is seeking a senior NLP data Scientist to lead our marketing language predictive modeling. Youll explore complex datasets, build and fine-tune advanced NLP /LLM models, and partner closely with engineering and product to integrate your work into Anywords AI content platform.
Responsibilities:
* Define and own the technical strategy and roadmap for Anywords marketing language predictive modeling.
* Analyze, process, and derive insights from our ever-growing data resources.
* Solve challenging prediction problems by applying the latest ML/ NLP techniques to build and fine-tune highly performant LLMs.
* Collaborate with engineers and product managers to ship models end-to-end, from research to production.
* Monitor and iterate on models using offline and online metrics.

Required Data Infrastructure Engineer
What Youll Do:
Design, implement, and enhance robust and scalable infrastructure that enables efficient deployment, monitoring, and management of machine learning models in production. In this role, you will bridge the gap between research and production environments, streamline data and feature pipelines, optimize model serving, and ensure governance and reproducibility across our ML lifecycle.
Responsibilities:
Decouple data prep from model training to accelerate experimentation and deployment
Build efficient data workflows with versioning, lineage, and optimized resource use (e.g., Snowflake, Dask, Airflow)
Develop reproducible training pipelines with MLflow, supporting GPU and distributed training
Automate and standardize model deployment with pre-deployment testing (E2E, dark mode)
Maintain a model repository with traceability, governance, and consistent metadata
Monitor model performance, detect drift, and trigger alerts across the ML lifecycle
Enable model comparison with A/B testing and continuous validation
Support infrastructure for deploying LLMs, embeddings, and advanced ML use cases
Manage a unified feature store with history, drift detection, and centralized feature/label tracking
Establish a single source of truth for features across research and production across research and production.

We are seeking an AI/ML Lead Engineer to join our R&D division and drive the adoption of advanced machine learning and AI solutions across our financial and operational domains. In this role, you will design and implement intelligent models that increase efficiency in collections and payments processing and build AI-driven tools that enhance call center performance and agent productivity.
We are looking for a hands-on, independent team player with strong foundations in data science, computer science, and backend engineering, combined with excellent analytical and algorithmic skills. This role is diverse and impactful, spanning machine learning development, data analysis, and backend engineering, with the opportunity to shape our AI/ML strategy for servicing and operations.
As part of the R&D group, you will work closely with engineers and product managers, leading and implementing AI/ML initiatives that directly align with our business goals and innovation vision.
Key Responsibilities:
Lead the design, development, and deployment of ML models to optimize collections and payments processing.
Develop and integrate AI-driven tools to improve call center efficiency and agent productivity.
Collaborate cross-functionally with engineers, product managers, and stakeholders to translate business needs into technical solutions.
Drive data analysis and modeling efforts, leveraging advanced algorithms to uncover insights and improve decision-making.
Ensure scalability, quality, and compliance of all AI/ML solutions within the financial and servicing domains.
Stay up to date with emerging AI/ML technologies and assess their potential impact on the companys strategy.
Mentor and guide team members, fostering knowledge-sharing and technical excellence.

Shape the Future of Cybersecurity with Us Are you driven by curiosity, innovation, and the desire to turn cutting-edge research into real-world impact? Join Cynet, an established but rapidly growing cybersecurity startup, where you'll be part of a small, elite team building groundbreaking AI-powered security products from the ground up. Work alongside top minds in security research, R&D, product, and data engineering to drive innovation and create real value for global customers. This is your chance to contribute to a foundational mission - developing AI technology that proactively protects against todays most sophisticated cyber threats.

What will you do:
As a data Scientist at Cynet, youll play a central role in shaping our future technology. Youll: Own AI product creation end-to-end - from the initial concept through building prototypes to full-scale production. Drive innovation by developing and integrating ML and Generative AI solutions into Cynets core cybersecurity products: Endpoint, XDR, Network Detection, and Posture Management. Analyze massive volumes of security data to uncover hidden patterns, threats, and insights. Develop and fine-tune models with state-of-the-art optimization strategies and performance metrics. Contribute to and expand our AI infrastructure, including data pipelines, evaluation tools, and deployment frameworks. Conduct rigorous experimentation, explain and monitor the real-world performance of your models. Write production-ready code that makes it into our deployed AI systems.

We are looking for a unique, hands-on Machine Learning / AI Developer to design and implement AI-powered solutions that improve business processes across the company. This role focuses on delivering custom-built tools and workflows that off-the-shelf products cannot provide, working closely with multiple departments such as Customer Success, Sales, HR, and more.

Responsibilities:

Collaborate with stakeholders across global teams to identify opportunities where AI can enhance business processes.
Design, develop, and deploy AI-based solutions tailored to organizational needs (e.g., customer success agents, HR process automation, sales optimization).
Build workflows, agents, and ML pipelines, ensuring solutions are production ready.
Integrate diverse data sources and leverage multiple data types to create actionable insights.
Work closely with business units' management to address specific operational challenges.

We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our Machine Learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind. You will work closely with data scientists, Machine Learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance. Key Responsibilities: Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators. Support reproducibility and consistency across model training environments. Implement and manage Artifactory. Establish and maintain model registries to track versions, metadata, and lineage. Automate model promotion through staging, testing, and production environments. Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback. Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments Optimize GPU/CPU resource utilization and cost efficiency. Implement auto-scaling and load balancing strategies for ML workloads. Manage version control systems (e.g., Git) and integrate with experiment tracking tools. Handle Storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.

Were looking for a Director of Training to build and lead our comprehensive training strategy and execution across customers and internal teams. Youll be the go-to expert ensuring our global workforce and customers can maximize the value of our maritime AI solutions.

Youll be diving deep into maritime domain expertise and product knowledge to create world-class training experiences that scale globally.

Reports to: VP Business Services

What Youll Own

Training development

Build ongoing product and solutions training curricula to keep customers and internal teams current with our evolving AI solutions
Manage certification programs and compliance training requirements
Create maritime domain training for non-maritime team members
Develop and adjust to role-specific training tracks (customer success, support, sales etc.)
External Customer Training

Lead customer education strategy from onboarding through advanced use cases
Build scalable training programs for our diverse global customer base
Create self-service training resources and knowledge bases
Design certification programs for customer power users
Deliver executive-level training sessions and workshops
Strategic Training Operations

Partner with Product, R&D, Product Marketing and Customer Success to stay ahead of feature releases
Build training analytics and success metrics to measure program effectiveness
Manage training technology stack and platforms use advanced AI tools
Scale training delivery across multiple time zones and languages

Were looking for a Product Analyst to join our Product team and play a critical role in unlocking the power of maritime data. Youll dive deep into complex datasets, ensuring quality, uncovering insights, and shaping the foundation for products and workflows built on AI. Your work will directly contribute to product innovation, customer impact, and the next generation of AI-driven maritime solutions.

What will you do?

Extract, analyze, and interpret maritime data using Python, SQL, and other data tools, working across sources such as Rockset, MongoDB, and S3.
Ensure data quality, accuracy, and consistency, supporting both product development and Generative AI-powered workflows.
Identify patterns, anomalies, and emerging risks within large, complex datasets to drive actionable insights for customers and internal stakeholders.
Collaborate with product managers, engineers, and data scientists to optimize data pipelines, workflows, and models.
Support the development of strategies for handling structured and unstructured data, contributing to scalable, automated solutions.
Visualize and communicate findings effectively, using tools such as Matplotlib, Grafana, or Redash, tailored for technical and non-technical audiences.
Apply domain knowledge of the maritime industry to contextualize data and generate meaningful insights for product workflows.
Conduct data integrity and QA checks, ensuring reliability for both operational use and AI model training.

We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our machine learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind.
You will work closely with data scientists, machine learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance.
Key Responsibilities:
Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators.
Support reproducibility and consistency across model training environments.
Implement and manage Artifactory.
Establish and maintain model registries to track versions, metadata, and lineage.
Automate model promotion through staging, testing, and production environments.
Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback.
Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments.
Optimize GPU/CPU resource utilization and cost efficiency.
Implement auto-scaling and load balancing strategies for ML workloads.
Manage version control systems (e.g., Git) and integrate with experiment tracking tools.
Handle storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.

We are looking for an ML Engineer to join our Data department. In this role, you will be responsible for the infrastructures needed to train models, serve them and do other ML magic.
What Youll Do:
Develop, integrate and optimize end-to-end ML solutions (data pipelines, training workflows, and serving infrastructure)
Plunge into a world of data, analytics, ML, high-paced and high-scale user and market movements
Work closely with Data Scientists to understand the business from top-to-bottom and turn their dreams into reality

Required Senior MLOps Engineer - AI Infrastructure
Tel Aviv
As a Senior MLOps Engineer, you will be pivotal in designing, implementing, and maintaining our AI cloud infrastructure. You will join a highly technological team responsible for developing our model-serving platform, optimizing inference, and ensuring reliability and cost efficiency. In this role, you will collaborate with key stakeholders across the company, including product engineering teams, internal clients (both researchers and engineers), and Security and DevOps, to automate processes, streamline operations, and drive impactful changes in our model-serving strategy.
Key Responsibilities:
AI Infrastructure Design & Implementation: Lead the design and implementation of our cloud-native infrastructure, ensuring it is performant, scalable, and cost-effective.
Automation & Streamlining: Help automate and streamline our AI operations and processes, enhancing efficiency and reducing manual intervention.
Cross-Functional Collaboration: Work closely with product engineering teams, including internal clients (both researchers and engineers), security, DevOps, and more, to ensure adoption of our AI platform.
Impactful Contribution: Play a major part in shaping the companys AI serving strategy, focusing on innovation and long-term success.

Required Senior ML Backend Engineer
Tel Aviv
As a Senior Machine Learning Backend Engineer, you'll architect and build the high-performance backend systems that power our AI at massive scale, craft real-time ML serving innovative solutions, and play a pivotal role in our mission to revolutionize the way companies understand their customer interactions. We're seeking a Java professional who can leverage their deep knowledge to drive our backend development to new heights.
You will be responsible for:
ML Serving Architecture: Design and implement high-performance inference APIs and model serving backends using Java & Python.
Model Lifecycle Management: Build systems for model versioning, A/B testing, canary deployments, and automated rollbacks.
Integration Platform: Create robust APIs and SDKs that enable product teams to seamlessly integrate AI capabilities.
Observability & Monitoring: Build comprehensive metrics, logging, and tracing systems for ML workloads.
Cross-team Leadership: Mentor engineers & researchers, drive technical decisions, and influence platform architecture across the organization.

We are a cutting-edge cybersecurity lab dedicated to addressing next-generation threats through advanced AI and machine learning. Our work spans multiple domains, including endpoint protection, cloud security, and AI-driven defense technologies. Our mission is to invent and implement breakthrough solutions that provide Huawei with a strategic edge in the global cyber defense landscape. By bridging research and engineering, our teams transform innovative concepts into real-world solutions that safeguard enterprises and critical infrastructure. We also maintain close collaborations with leading universities and international innovation hubs.
Role Overview
We are seeking a Senior Applied Machine Learning / AI Engineer with at least 5 years of hands-on experience in designing, developing, and deploying machine learning models, specifically for cybersecurity applications. This role combines applied ML engineering with innovation and research, requiring someone who can move seamlessly from proof-of-concept to production, and lead initiatives that drive our AI-driven security strategy.
Key Responsibilities
Lead the design, training, and deployment of advanced ML/DL models for cybersecurity use cases (malware detection, anomaly detection, network behavior analytics, adversarial ML defense, etc.)
Drive innovation by developing proof-of-concepts, exploring novel AI techniques, and translating research findings into practical, scalable solutions
Collaborate with cross-functional teams (security researchers, software engineers, product managers) to bring ML-driven features into production environments
Analyze large-scale, heterogeneous cybersecurity datasets (logs, network traffic, endpoint telemetry, threat intel)
Implement robust model monitoring, explainability, and optimization for real-world environments
Stay at the forefront of advances in AI, data science, and cybersecurity; identify emerging opportunities and mentor junior engineers/researchers
Represent the company in external collaborations, conferences, and innovation forums.

We're looking for a Senior Machine Learning Engineer to design and build scalable ML models that power critical business decisions. You will focus on building ML expertise from experimentation to production in one or more areas that improve the company's overall ML strategy. This role is based in Tel Aviv and involves collaboration across global teams, requiring strong communication and coordination skills.

Responsibilities:

Build and deploy end-to-end machine learning solutions from research to production by leveraging advanced algorithms and mathematical techniques to deliver highly predictive models in the fintech space.
Design and run experiments to evaluate new data sources and continuously improve the performance of existing models.
Implement, maintain, and monitor production models using machine learning platform, ensuring scalability, reliability, and long-term performance.
Evaluate model effectiveness both offline and in live environments, with a focus on real-world impact and business relevance.
Act as a technical leader, mentoring teammates, guiding design decisions, and collaborating with global cross-functional partners to drive ML initiatives forward.