דרושים » הנדסה » Software Middleware Team Lead - Q

Somewhere between the physics of a sensor and the software people touch, there is a layer that decides whether a breakthrough actually works. That layer is yours.
We're a small, truly multidisciplinary team that spans high-level software down to low-level physics, and we're building the foundation for our next big technology. As a Senior Software Engineer, you'll build the iOS- and macOS-based, low-latency application layer of our data collection and research system. It is the infrastructure that turns raw, real-world signals into the data that trains and validates the next line of our AI products. You'll write the code that makes it all work, and you'll help shape the applications built on top of it.
This is a rare chance to work on something new, from day one, alongside people who see the whole stack.

Responsibilities
Help create the next line of our AI products by building the infrastructure and laying the groundwork they will stand on.
Design and build low-latency middleware components for our-platform applications (iOS and macOS) supporting data collection and research workflows.
Own end-to-end implementation: architecture, coding, debugging, and performance tuning across the application layer.
Contribute to the design and implementation of downstream applications that consume the middleware (not just the plumbing - the product too).
Write robust, production-quality code in C++, Objective-C/C++, and/or Swift for performance-critical and system-level components, and Python for tooling, data processing, and automation.
Collaborate closely with firmware, data, and research teams to ensure the middleware correctly reflects real-world device and sensor behavior.
Use modern AI-assisted development tools as a core part of your workflow - for code generation, debugging, test authoring, and accelerating iteration.
Participate in design reviews, code reviews, and architectural decisions for the broader system.

Were looking for a software developer with a real passion for hardware. You enjoy the moment when code makes a physical device do something, youre comfortable standing at a lab bench, and you take a problem from a vague request to a working solution that people actually use.

Responsibilities
Design and build macOS tools and applications, primarily in Python and Swift, for hardware test setups, lab research setups, and lab automation.
Develop company-wide tools used by multiple teams for dedicated proprietary hardware research, and support them as real products with real users.
Own problems end to end: understand the need with the people at the bench, design the solution, implement, deploy, and iterate until it works in the lab.
Integrate with instruments, sensors, and custom hardware over USB, serial, Bluetooth, network, and other lab interfaces.
Build supporting infrastructure as needed: cloud dashboards, databases, data pipelines, and reporting for test and research results.
Implement algorithms and data-processing logic that turn raw measurements into usable results.
Support Windows environments when lab equipment or vendor software requires it.
Make advanced AI coding tools a core part of how you build, and help the team move faster with them.
Take part in design and code reviews, and help raise the quality and maintainability of the teams tools.

We're seeking a passionate and skilled Embedded Firmware Engineer to play a pivotal role in delivering the next generation of us. In this highly visible position, you'll be at the intersection of hardware and software, collaborating closely with logic designers to deeply understand system-level operations and performance requirements for hardware validation. In this role, you will develop critical low-level embedded firmware specifically designed to validate hardware functionality, ensure conformance, and drive performance during the bring-up and testing phases of new silicon. This involves designing, developing, and integrating complex drivers, diagnostic tests, and infrastructure essential for SoC bring-up, post-silicon validation, and debugging activities. Ultimately, you'll lead hands-on firmware development, system-level validation, and problem-solving at the hardware-software interface in a dynamic, collaborative environment, with your work directly enabling the successful launch of future products by ensuring our silicon meets the highest standards.

We're seeking a passionate and skilled Embedded Firmware Engineer to play a pivotal role in delivering the next generation of us. In this highly visible position, you'll be at the intersection of hardware and software, collaborating closely with logic designers to deeply understand system-level operations and performance requirements for hardware validation.

In this role, you will develop critical low-level embedded firmware specifically designed to validate hardware functionality, ensure conformance, and drive performance during the bring-up and testing phases of new silicon. This involves designing, developing, and integrating complex drivers, diagnostic tests, and infrastructure essential for SoC bring-up, post-silicon validation, and debugging activities. Ultimately, you'll lead hands-on firmware development, system-level validation, and problem-solving at the hardware-software interface in a dynamic, collaborative environment, with your work directly enabling the successful launch of future our products by ensuring our silicon meets the highest standards.

Play a part in shaping the future of human-computer interaction. We're looking for an Engineering Program Manager (EPM) to turn advanced machine learning in speech, audio and computer vision into features that ship to customers.
You'll work across ML research, data collection, silicon, FW, and the device and companion SW teams that bring these features to our customers. Your work will cover every stage, from the first dataset to the final release.

You'll own the plan for taking ML features from research to release. That covers data planning, model training and evaluation, optimization for our silicon, integration with SW teams, and release. You'll keep teams aligned, make risk visible early, and help leadership decide when model quality, performance and schedule pull in different directions. You'll be comfortable with how uncertain research is, and disciplined about delivering what ships.

Responsibilities
Own the delivery plan for ML features, from research and prototyping through integration, validation and release.
Partner with data teams to build the data strategy and plan, making sure it covers what the models need and supports program milestones: what data, at what scale and coverage, and by when.
Align model milestones with HW builds, pre-silicon validation (simulation and FPGA), and silicon bring-up, ensuring models are ready at each gate.
Lead integration with SW groups, including model handoff, interfaces, integration schedules and release timing.
Align ML teams, MLOps and data science on priorities, compute capacity and dependencies.
Track model quality, latency, memory and power against product targets, and lead trade-off decisions.
Set up model release practices: readiness gates, versioning, regression tracking and post-integration monitoring.
Summarize ML progress into clear, data-driven recommendations for leadership.

We are seeking a highly skilled and motivated ML Deployment Engineer to join our on-device AI team. In this role, you will take state-of-the-art machine learning models and make them run efficiently on Apple silicon - compressing, compiling, and optimizing them to deliver intelligent experiences that run entirely on-device, with the performance, power, and privacy our users expect.

Responsibilities
Own the model deployment pipeline from trained checkpoint to on-device execution, ensuring models meet product-quality bars for accuracy, latency, memory, and power.
Apply model compression techniques - quantization (post-training and calibration-based), palettization, pruning, and mixed-precision - and validate the accuracy/size/latency trade-offs of each.
Convert and compile models to the Core ML stack and target the Apple Neural Engine, GPU, and CPU.
Analyze and maximize accelerator (ANE) residency; diagnose why operations are rejected or dispatched to fallback compute units, and work with the graph to resolve them.
Profile end-to-end inference on real hardware, identify bottlenecks, and optimize compute-unit placement, memory footprint, and energy consumption.
Collaborate closely with ML research and applied ML to co-design models that are efficient to deploy and to feed hardware constraints back into model architecture decisions.
Build and maintain tooling and automation for reproducible compression, compilation, benchmarking, and numerical validation.
Stay current with the latest advances in efficient ML inference, model compression, and accelerator architectures.

As a member of our ML group, you will research and build AI systems that change how our silicon is designed. Many of these problems are still open: the right way to frame the problem isn't known yet, and the data is scarce or noisy.

We are looking for a strong researcher who enjoys working closely with design teams to turn open-ended questions into well-posed research problems, and who wants to see the results used in real projects. Success in this role means models and agents that measurably improve designed chip metrics (Power, Performance, and Area) and design turnaround. You will join a growing team of AI and software engineers working with our chip design teams.

Responsibilities
Research and develop AI methods for the physical design flow, from floorplanning and placement through routing and timing closure, combining predictive models, optimization, and generative AI.
Design and build agentic workflows that connect LLMs to EDA tools, design data, and internal infrastructure, to automate and speed up tasks such as flow setup, debug, design exploration, and analysis.
Work with design teams to turn open-ended problems into well-defined research questions with clear metrics, baselines, and success criteria.
Develop robust AI methods for limited, noisy, or imbalanced data, leveraging domain knowledge and advanced learning techniques.
Own data end to end: extract useful signal from EDA tool outputs and design databases, validate and clean it, and build datasets and benchmarks where none exist.
Run careful experiments and evaluations for both models and agents, and report clearly what works and what doesn't.
Work with software engineers and design teams to bring promising prototypes into production flows, and improve them based on feedback from real projects.
Help shape new research directions as our work grows, follow the AI and EDA literature, and bring relevant ideas to the team.

the company is known for its massive backend production. at any given moment thousands of servers are consuming 200+ billion mobile app events daily, crunching our users' data, serving requests, and communicating on a massive scale. to achieve such scale, our data & microservice architecture is built with the best and latest cutting-edge technologies such as Node.js, go, kafka, graphql, neo4j, redis, bigquery, aws, and many more
the saaslab group is part of the afos (the company operating system ) unit which owns the saas platform and control plane of the company - the foundational layer that manages users, accounts, billing, api gateway, authentication, permissions, and business integrations. saaslab's systems serve as the backbone for every product and feature at the company, handling millions of api calls daily and supporting thousands of enterprise customers worldwide.
we are looking for an exceptional team leader to lead the domain team within saaslab. the domain team owns the company's core entities - accounts, apps, and users - as well as the onboarding experience. this is a foundational domain that every other product and team at the company depends on. you will drive the technical execution and architectural evolution of these systems while ensuring their reliability and scalability as the company continues to grow.
the position requires a strong hands-on engineering leader with a solid architectural mindset, experience owning platform-level services, and the ability to balance day-to-day team leadership with long-term technical direction.
what you'll do
lead and mentor a team of engineers, fostering growth in design, architecture, and technical craft
own the domain team's systems end to end - ensuring high availability, security, and operational excellence for the core entities (accounts, apps, users) and onboarding flows that underpin every the company product
drive the design and delivery of scalable backend systems and data flows, including decoupling from legacy data stores, building a resilient domain model, and adopting modern patterns like graphql federation where relevant
work closely with product managers and cross-functional stakeholders, taking accountability for team deliveries and ensuring the team ships on time with excellent quality
stay hands-on and involved in architecture discussions, design reviews, and code reviews
lead technical initiatives, processes, and architectural decisions within the team
drive adoption of ai-powered tools and modern sdlc practices to improve team velocity and quality
be an active and engaged member of the saaslab leadership group, contributing to the unit's engineering vision, processes, and culture

Our team is new, growing, and evolving quickly, and we are hiring across multiple disciplines. We work at the intersection of machine learning, hardware, and software, creating technologies that reshape how people communicate and experience the world around them in everyday life.

We are looking for someone who operates independently and leads projects, not someone who waits to be handed a task. You will be part of a development team, working closely with the central Platform Engineering group to deliver reliable cloud infrastructure, backend services, pipelines, and observability for the team's products. You will collaborate with developers and mentor other engineers along the way. This role is fully onsite.

Responsibilities
Own the CI/CD, cloud infrastructure, and operational health of your team's applications and services.
Build and operate cloud backend services, tooling, and automation in Python and Go.
Partner with the Platform Engineer to adopt shared tooling and contribute improvements back to the platform.
Design and manage cloud infrastructure as code.
Build observability (metrics, alerting, dashboards) and drive reliability and performance improvements.
Set technical direction and standards for deployment and operations within the team.

We are seeking a software engineer to build high-performance software models of advanced SoC designs and to help bridge the gap between Software and Hardware, influencing performance improvements, power efficiency, security, and the programming ease of Apple products.
Responsibilities
In this role, you will:
Develop software systems and tools used to bring up the future OS on future SoCs.
Support kernel and driver development on future processor & SoC models.
Work closely with software and hardware teams across product and research groups.
Promote new opportunities and techniques with other groups.