דרושים » מחשבים ורשתות » MLOps Engineer

We are looking for an MLOps Team Leadto drive the development of an internal machine learning platform for a group of ML teams. This is a hands-on leadership role: you will guide a small team of MLOps engineers that builds the automation and infrastructure powering our research (R&D) workflows and runs our pipelines to production. You will take ownership of end-to-end initiatives and drive the team toward critical infrastructure and model-lifecycle milestones, while staying close enough to the code to set technical direction and raise the bar by example.

You will be responsible for building and maintaining the models and data pipelines behind our data science workflows, ensuring the accuracy, consistency, and efficiency of the data used for training and inference, working across structured and unstructured data from many sources on a large-scale, distributed platform.

WHAT YOU WILL DO

- Lead, mentor, and grow a team of MLOps engineers, owning delivery and technical quality.

- Take end-to-end ownership of infrastructure and pipeline initiatives across the LMM group, from design through production.

- Stay hands-on: contribute to design and code, review work, and set engineering standards.

- Drive the team through critical milestones in ML model-lifecycle and infrastructure ownership.

- Partner with R&D and other stakeholders to translate research needs into robust, scalable systems.

- Help evolve the platform, including our ongoing migration from Dask to Ray.

We are seeking a detail-oriented and collaborative Senior ML Engineer to help support and maintain our machine learning capabilities. This role is ideal for someone who enjoys working closely with production systems, ensuring reliability, scalability, and explainability of models while enabling research teams to deliver impact faster.



Responsibilities



Collaborate with cross-functional teams to ensure ML systems remain robust, explainable, and aligned with business needs.
Monitor and report on ML model performance, reliability, and explainability metrics.
Participate in model retraining procedures, implement automation and optimization of MLOps pipelines.
Extend and scale monitoring pipelines, including support for new features in development.
Investigate, troubleshoot, and resolve issues in production ML workflows (tiered support from initial triage to root-cause analysis with model owners).
Develop and maintain repositories for feature engineering, inference monitoring pipelines, and artifact monitoring tools.
Perform exploratory data analysis (EDA) on historical datasets to identify quality issues and maintain data health.
Implement and oversee production based adjusters across customer deployments.
Evaluate and track critical ML artifacts such as explainability files, coverage metrics, and alignment of features.
Support development and maintenance of internal tools (e.g., interfaces, registries, and feature monitoring frameworks).
Build and maintain static and temporal features, including seasonality, event-based, and price-related features.

We are seeking a talented and self-driven experienced Data Scientist to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact.

Responsibilities:

Develop and implement state-of-the-art econometric and machine learning models for demand forecasting.
Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability.
Collaborate with cross-functional teams (including product, data engineering, MLOPS and Platform) to deploy ML systems in production.
Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives.
Requirements

Were looking for a technical professional, with proven experience for building secure, scalable artificial intelligence systems as well as data-for-AI solutions. In this role you will develop our cutting-edge AI Data platforms used by world-leading brands.
Responsibilities:
Data Pipelines: Clean, preprocess, and analyze large datasets to ensure high-quality inputs and results.
Deployment & Integration: Help deploy AI agents into production environments and integrate them into existing workflows.
Monitoring & Optimization: Evaluate model performance, test for accuracy, and tweak algorithms for continuous improvement.
Documentation: Maintain clear documentation for AI model architectures, data pipelines, and deployment processes
Scale: Build highly scalable solutions that can leverage large data sets effectively

We are looking for an experienced and leadership-oriented ATE Software team leader to lead our software ATE development team. In this role, you will manage a team of software engineers, overseeing the design and execution of advanced ATE software for electronic cards and calibration systems used in our cutting-edge AESA radar technology The ideal candidate will combine strong software management skills with a deep understanding of RF systems and hardware-software integration. Key Responsibilities:
* Lead, mentor, and manage a team of ATE software engineers.
* Lead the design and development of automated TEST software for electronic cards and radar calibration.
* Oversee the full software development lifecycle, from requirements definition to deployment on the production line.
* Collaborate closely with Hardware, system, and RF engineers to ensure seamless integration of software with complex testing equipment.
* Drive technical excellence, code quality, and the implementation of best practices within the team.
* Manage project timelines, milestones, and resource allocation to meet delivery goals.

The position is based in Netanya, with occasional travel required to the production facility in Beit She'an.

We are looking for a Software Automation Engineer to join our QA team and to take part in the testing process from planning to execution.
Responsibilities:
Responsible for QA processes, testing and release to production of multiple SaaS products.
Build the test plan for the products.
Identify the risks and appropriate test coverage to validate new features as well as regression and develop test plans and cases.
Lead the test execution and preparation for release.
Execute test cases, manually or in an automated fashion, capture and analyze the results, document issues and prepare test reports.
Work with the R&D and Product to deliver high-quality tested SaaS products.
Write test automation for APIs, UI and stress-testing, as an integrated member of an agile R&D team, building a robust application.
Take responsibility for the quality delivery of product releases.
Participate in defining and optimizing the R&D work processes.

Required Developer Advocate
This role sits at the intersection of engineering, product, and the global developer community. Youll translate our technical work across all domains, repositories, security, release management, pipelines, distribution, metadata, AI/ML, and ecosystem integrations, into content, demos, talks, and conversations that developers trust. Youll also bring community insights back into our R&D and business teams to influence product direction.
As a Developer Advocate you will:
Represent us across developer, DevOps, security, and platform-engineering communities through conferences, meetups, webinars, podcasts, and online conversations
Create high-quality technical content: deep-dive articles, demos, hands-on guides, screencasts, code samples, and social content
Build compelling demos and storytelling around our core domains: Artifactory, Xray, Curation, Distribution, Pipelines, Workers, Fly, AI/MCP, and ecosystem integrations like GitHub
Collaborate closely with R&D, Product, Security, Solutions Engineering, Architecture, and Customer Success to deeply understand new capabilities and provide practical feedback
Engage with open source and developer communities, finding new channels and conversations where we should have a voice
Partner with Marketing to strengthen messaging while preserving technical credibility
Monitor and report impact across community engagement, content performance, OSS participation, and broader DevRel KPIs.

Join GenAI team to build and extend the AI assistant embedded across our product suite. The platform is a production LLM agent system that's integrated into multiple host applications, backed by a RAG knowledge base and an evaluation-driven development workflow.

You'll work end-to-end: agent design, tool implementation, retrieval quality, integration into existing product UIs, cloud infrastructure, and evaluation/observability. The platform already ships to customers - you'll extend it, raise its quality bar, and help define where it goes next.

What you'll do

Design and evolve agents - build LLM agents with tool use, routing, and human-in-the-loop flows.
Implement tools and integrations - expose product capabilities to the agent, with multi-tenant context, via internal APIs and MCP servers.
Own retrieval quality - contribute to our RAG pipeline end-to-end: ingestion, embeddings, vector search, and reranking.
Define and evolve host integration contracts - collaborate with host application teams to integrate the assistant into product UIs built on different frontend stacks. You own the shared remote module and the integration API; host teams own their stacks.
Drive evaluation-led development - write evaluators (rule-based, LLM-as-judge, multi-turn), maintain CI eval gates, and use traces and feedback to debug production behavior.
Operate the platform - own deployments, observability, and the performance and cost of LLM-backed services.
Establish engineering practices** for AI-specific work: prompt versioning, eval coverage, testing, and code review.

We are looking for a Senior DSP Software Engineer who will lead design and implementation of our innovative signal processing algorithms on the industry cutting-edge target platform, consisting of embedded cores, DSPs, and dedicated accelerators.
What will you do:
Perform analysis, design, implementation and validation of innovative MIMO imaging radar algorithms for next generation ADAS and autonomous
vehicles on our target platform
Participate in SW architecture design and perform signal processing algorithm porting & optimization
Address real-time constraints in a challenging memory/compute bound framework
Be part of a goal-oriented workgroup and dynamic research & development environment
Work in close collaboration with CTO and SW architecture team