לוח משרות דרושים מהנדסים, לחיפוש זה נמצאו 4,199 משרות

We are seeking a Sales Operations Director to lead global business operations, including sales processes, forecasting, processes, and systems. This senior role combines strategic leadership with hands on execution and cross functional influence
Responsibilities
What will you be doing:
Lead and develop a global Sales Operations team supporting regions and key accounts
Act as the global owner of end-to-end commercial processes
Drive integration of forecasting, planning, pricing, agreements, commissions, and customer lifecycle operations
Partner closely with Sales leadership, business divisions, and Finance
Enhance and standardize processes within Salesforce and Oracle ERP while ensuring data quality and system alignment
Define roles, KPIs, and accountability, and oversee day-to-day execution
Own commercial processes including quoting, pricing, agreements, sales orders, and evaluations
Establish and improve global processes, controls, and documentation, ensuring compliance across regions
Support planning, analysis, reporting, and executive reviews
Foster a culture of operational excellence, discipline, and data-driven decision-making.

We are seeking an experienced and innovative R&D System Scientist to join the System Engineering Stand-Alone team within the Research & Development organization. In this role, you will become an integral part of a multidisciplinary team of physicists and engineers responsible for developing advanced metrology technologies, from early-stage research through product delivery.
The team develops cutting-edge metrology solutions for the semiconductor industry, combining expertise in physics, optics, mechanics, electronics, motion control, algorithms, and software. You will lead complex system investigations, transform customer and business requirements into technical solutions, and drive scientific innovation that directly impacts our next-generation products.
Responsibilities
What you will be doing:
Perform theoretical and experimental systems engineering to support state-of-the-art new and existing multidisciplinary optical measurement products.
Define, lead, and oversee the implementation of innovative system solutions.
Collaborate with hardware, software, optics, and algorithm engineering teams to deliver multidisciplinary solutions.
Analyze complex datasets and perform advanced statistical evaluations to support product and technology development.
Investigate critical system behaviors, perform root-cause analysis, and establish robust mitigation and calibration methods.
Support product transfer to manufacturing, service, and production organizations while serving as a technical expert for complex challenges.
Translate customer needs and high-level requirements into detailed technical specifications and system designs.
Travel to customer sites worldwide as needed, approximately 2-3 times per year.

We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.
If you've built agents that actually made it to production - and you care as much about evaluation, guardrails, and reliability as you do about capability - we want to talk to you.
Responsibilities
Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
Optimize agents for latency, cost, and reliability at enterprise scale.
Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

We're looking for a smart and capable DevOps Engineer. You will be part of a small and agile team, working on well-built infrastructure, handling production workloads, building and maintaining infrastructure that supports continuous delivery. This job includes work across the devops stack, including agent development, CI/CD, networking, resource allocation, cloud architecture, security, developer experience, and more.
We work with enterprise customers, with the SLA and expectations that this dictates.
This position includes on-call shifts.
Our stack:
Kubernetes on AWS
Terraform and IAC
Github & Github Actions
Responsibilities
What will you DO:
Design and evolve our cloud multi-region architecture on AWS - networking, interconnects, IAM and high-availability topology - and express it entirely as code with Terraform, following GitOps as a first principle.
Build and own the CI/CD pipelines that plan, review, test and safely apply IaC changes - Policy-as-Code guardrails, drift detection and progressive rollout so infrastructure changes ship as confidently as application code.
Advance Platform-as-a-Product: build self-serve capabilities and paved paths so engineers can provision what they need
Strengthen our observability stack - metrics, logs, traces and alerting.
Troubleshoot and mitigate production incidents, participating in on-call rotations to ensure system health and stability.
Design and develop the next generation of AI agents to support higher pace and evolve the RnD productivity while maintaining security and engage the entire company to use AI for better solutions.

We are looking for a highly driven and experienced AI Engineer Team Leader to manage and mentor a core team of engineers while remaining 50% hands-on. In this critical role, you will lead the development of our enterprise Agentic AI platform, blending deep technical expertise in AI agent development with strong engineering leadership.
As a Team Leader, you will drive the technical agenda, plan sprints, and collaborate closely with Product Managers and cross-functional partners to turn powerful capabilities into reliable, safe, and fast product experiences. You must thrive in a high-pressure, dynamic startup environment characterized by a fast pace and frequent pivots, ensuring your team remains focused, agile, and aligned with business goals while executing at the highest level.
You won't just manage - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily, and iteration in front of enterprise customers.
Responsibilities
Team Leadership & Management (50%): Manage, mentor, and grow a team of AI and software engineers. Oversee task allocation, sprint planning, and daily agile ceremonies.
Hands-On Engineering (50%): Actively code, design, and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Technical Strategy & Architecture: Drive the technical agenda, architecture decisions, and best practices for developing scalable, LLM-driven applications grounded in our knowledge graph.
System Integration: Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Production Excellence: Build evaluation harnesses, guardrails, and safety/bias checks. Optimize agents for latency, cost, and reliability at enterprise scale. Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Cross-Functional Collaboration: Work intimately with Product Management, Data, and Design teams to translate customer needs into agent capabilities, define roadmaps, and prioritize tasks.
Agility & Execution: Lead the team through frequent pivots and rapid development cycles, ensuring high-quality delivery under pressure in a fast-paced startup environment.

Own the technical integrations that connect us with retailers systems, making sure data flows are smooth, secure, and ready for scale.

Responsibilities
Manage data integrations with POS, ERP, and other systems.
Define and document technical requirements for new onboardings.
Work with APIs, SFTP, and database connections.
Troubleshoot and resolve integration issues with engineering.
Collaborate with retailers IT teams during setup.

Required Quality & Reliability Lead
What we are looking for:
The Quality & Reliability Engineer is responsible for driving product quality, manufacturing excellence, and reliability performance across our products and operations.
Working closely with Engineering, Manufacturing, Supply Chain, Service, and R&D teams, this role leads quality and reliability initiatives that improve process capability, manufacturing yields, product robustness, and customer satisfaction through data-driven decision making, structured problem solving, and continuous improvement methodologies.
The role is also expected to leverage AI and advanced analytics tools to accelerate insights, improve decision making, and enhance operational effectiveness.
Responsibilities
What will you be doing:
Responsibilities - Quality:
Lead quality improvement initiatives focused on yield enhancement, defect reduction, process stability, and continuous improvement across DMD operations.
Establish and maintain Statistical Process Control (SPC) and drive process capability analysis using statistical methods and data-driven quality metrics.
Lead root cause investigations utilizing methodologies such as 8D, 5 Why, Fishbone Analysis, Pareto Analysis, DOE, and FMEA.
Drive NCR, CAPA, and corrective action processes, identify trends, prioritize actions using evidence-based analysis, and verify effectiveness of implemented solutions.
Partner with Manufacturing, Engineering, Service, and Customer Support teams to resolve product quality issues, customer complaints, field incidents, and escalations.
Collaborate with suppliers to improve quality performance, drive supplier corrective actions, and reduce supplier-related quality risks.
Conduct supplier audits and assessments, including evaluation of manufacturing controls, process capability, inspection methods, and process discipline.
Review supplier quality documentation including CoC, CoT, ATR, inspection records, and quality reports to identify risks, trends, and improvement opportunities.
Lead internal and external audits, ensuring compliance and effective corrective actions.
Responsibilities - Reliability:
Partner with Engineering and R&D teams to define reliability qualification plans, test strategies, acceptance criteria, and reliability requirements for new and existing products.
Ensure reliability testing programs are properly executed and that test results are systematically reviewed, analyzed, and translated into actionable improvements.
Partner with Service and analyze reliability, field performance, MTBF, and MTTR data to identify trends, emerging risks, and improvement opportunities.
Lead investigations of reliability failures and support identification of physical, mechanical, electrical, optical, material, and process-related failure mechanisms.

Every camera and sensing system we ship is used, every day, by hundreds of millions of people who simply expect it to work. Ensuring our systems are worthy of that expectation is this team's goal. We challenge products through the physical world to prove it, and to feed real-world evidence back into system design - measuring and analyzing the performance of multi-disciplinary optical sensing systems. This role is the analytical core of that work. You will define what we measure and why, mine large volumes of measurement data for the effect that actually matters, and take a question that has never been answered to a defensible answer. It is highly collaborative: you will work directly with module, optics, algorithm and system teams, and your conclusions will be the basis of their decisions. You will work alongside our lead system engineer as a peer, with problems allocated between you according to where the issue actually sits. We are looking for someone who genuinely enjoys digging into data until it gives up what it knows, and who wants to take that on with us.
Responsibilities
Own the characterization of system performance end to end - from risk and failure mode mapping through methodology definition, execution, analysis and reporting
Define metrics, testing & measurement methodology
Mine large data sets to separate isolate performance root causes
Correlate physical measurement to human perception - where the HW meets the user
Build the analysis capability the work requires - pipelines, tooling methods
Present and defend findings to module, optics, algorithm and system teams

The Production team is looking for a Production Integration Engineer to join the integrated metrology line and work on state of the art tools in the semiconductor industry.
Your role will be to manufacture the company products while maintaining highest quality and on-time delivery.
As part of your job you will interact and work with the Engineering, R&D and QA departments to solve complicated on tool problems and test new tools and features as part of the transfer to production process.
Responsibilities
What will you be doing:
Lead tool manufacturing process from start to end (1-2 weeks project).
Integration of multidisciplinary systems (optical, electronic, pneumatic, computing, and mechanical) according to predefined procedures.
Ability to solve complex system challenges, constantly learning and striving to independence.
Working with engineering and R&D to address systems/production process challenges.
Addressing quality issues and repair recommendations for suppliers by nonconformance report.
Working in an organized way using digital procedures and flow management system.
Always striving to reduce cycle time and improve working process.
Helping and consulting team members to overcome challenges on their tools.

Join our team in a pivotal role where you'll own the entire IP-level netlist generation and timing convergence journey from synthesis to sign-off.
You'll drive synthesis, UPF power intent, scan insertion, and external IP integration while architecting timing constraints for both standard and complex custom designs that ensure sign-off quality from day one.
Working at the intersection of multiple disciplines, you'll partner closely with RTL designers to deeply understand design intent and clock architecture, collaborate with CAD teams to shape and optimize cutting-edge flows, and team with Physical Design engineers to achieve flawless timing sign-off.
We're seeking an innovative thinker who brings fresh perspectives to timing analysis methodologies and proactively identifies and resolves timing challenges to eliminate pessimism and accelerate convergence, ultimately making their mark on next-generation chip design.

We are looking for a DevOps Engineer to own and scale the infrastructure behind our AI systems.

What you'll do
Own cluster reliability, availability, monitoring, alerting, capacity planning, and incident response.

Configure, maintain, and troubleshoot GPU servers, networking equipment, switches, InfiniBand fabrics, storage, and related infrastructure.

Deploy, maintain, and improve infrastructure around Slurm, Kubernetes, and GPU workload orchestration.

Manage and improve our cloud environment, including compute, networking, storage, IAM, security groups, cost visibility, and production infrastructure.

Build, maintain, and improve CI/CD pipelines.

Work closely with engineers to understand infrastructure bottlenecks and improve development, training, inference, and deployment velocity.

Contribute to security best practices across cloud, network, CI/CD, access control, secrets management, and production systems.

We are looking for a Deep Learning Engineer to help design, implement, optimize, and scale the training and inference systems behind our models.

What you'll do
Collaborate with cross-functional teams to bring research breakthroughs into production environments.

Build tools, abstractions, and infrastructure that make model training, evaluation, and deployment faster and more reliable.

Analyze and overcome performance and scalability challenges in large-scale distributed training.

Debug complex issues across the full ML stack: data loading, model code, distributed execution, GPU utilization, memory usage, networking, checkpointing, and serving.

Work with modern training and inference frameworks such as Megatron, TorchTitan, PyTorch, and vLLM.

We are seeking talented, creative and disciplined engineers to join the best-in-class team that plays a significant part in the development of new silicon for our eco-systems by engaging in a dynamic, highly collaborative environment with the focus on the following goals.

Deep understanding of components/modules within wireless communication systems and the corresponding calibration and impairment reduction techniques - Develop methods/algorithms to alleviate hardware induced impairments by calibration, cancellation and other applicable techniques - PHY firmware architecture and design, including calibrations, real-time processing flows, collaboration with RF hardware, microcode, and MAC layer.

Develop highly efficient designs delivering outstanding performance, optimizing power and memory footprints while meeting hard-realtime latency requirements.

Debug real-time systems with limited visibility, working hands-on with development boards and lab equipment.

Collaborate with Radio, MAC, and Systems engineering teams to architect, define and implement innovative algorithms, calibrations, and protocols.

Support pre-silicon validation efforts, including simulation, emulation, and FPGA prototyping.

Develop SoC test and calibration capabilities for chip, module, and product factories.

Support post-silicon bringup, validation, performance characterization, system integration and debugging. - Repeatedly measure and optimize results using various test harnesses - Automate calibration and verification processes

We are looking for a Product Engineer to own and ship the products that put this capability in the hands of engineers, data scientists, and researchers.

What you'll do
Own product features end-to-end: scope, build, ship, measure, and iterate - across CLI, IDE integrations, web surfaces, and the AI pipeline behind them.

Talk directly to users - engineers, data scientists, ML practitioners - and let their feedback shape what you build next.

Define what AI-powered code optimization and verification feels like as a developer experience: the interaction model, the feedback loops, the trust signals. There is no established playbook; you will create the conventions.

Craft interfaces that feel fast, focused, and effortless for technical users who have zero patience for friction.

Collaborate with researchers to translate model breakthroughs into polished, reliable tooling that developers can depend on in production.

Build evaluation infrastructure and product metrics that measure whether the tools are actually getting better.

Work directly with the founding team on product strategy and roadmap.