דרושים » תוכנה » Physics & Optical Simulation Software Engineer - Q

We are seeking a creative and hands-on Deep Learning Research Engineer to drive model and architecture innovation across our sensing platforms. In this role, you will go beyond off-the-shelf models, exploring novel neural network designs, designing rigorous training and validation pipelines, and translating inventive concepts into clean, high-performance implementations. While our domain deals with physical data, this is an ML-first role: we are looking for a deep learning specialist with strong research intuition, expertise in PyTorch, and the drive to solve non-standard, real-world problems.

Responsibilities
Conceive, design, and implement novel neural network architectures tailored for complex physical sensing, reconstruction, and inverse problems.
Lead end-to-end hands-on research: data preparation, model formulation, training, hyperparameter exploration, and failure-mode analysis.
Build, train, and rigorously validate deep learning models using Python and PyTorch.
Formulate custom loss functions, regularization techniques, and inductive biases that capture domain-specific constraints.
Design comprehensive validation and benchmarking suites to stress-test model robustness, generalization, and scaling behavior.
Propose creative, non-conventional modeling ideas, stay abreast of state-of-the-art DL literature, and rapidly prototype proof-of-concepts.
Collaborate cross-functionally with physicists and optical software engineers to benchmark models against simulated and experimental lab datasets.

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.

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.

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.

We are seeking an experienced Signal/Image Processing and Machine Learning engineer to join our team. The role focuses on developing innovative, real-time deep learning and signal processing solutions for new sensing and imaging systems, including video restoration. You will be part of an interdisciplinary team developing technologies that will shape future Apple products.
Description
Algorithm and model development:
- Design, implement, and optimize signal processing and machine learning models for sensing and imaging tasks, including video restoration.
- Develop and validate models using real sensor data, simulated data, and public datasets.
- Prepare, filter, process, and analyze large-scale datasets to train and evaluate models.
- Analyze your algorithm's results and benchmark them against leading methods, and theoretical bounds.
- Optimize models for real-time performance, low latency, and resource efficiency on-device.

Sensing and research:
- Develop algorithms that combine classical signal processing with learned models to extract robust information from sensor data.
- Investigate efficient architecture patterns (lightweight backbones, attention mechanisms, recurrent designs) suitable for real-time, on-device inference.
- Explore how algorithmic approaches can mitigate artifacts and limitations of new sensing and imaging systems.
- Stay current with recent advances in signal processing, computer vision, and machine learning.

Collaboration and technical leadership:
- Work closely with ML researchers, SW, HW, sensor, and architecture engineers to translate research ideas into robust models and practical, shipping systems.
- Provide technical guidance and mentorship to junior engineers, and help shape the team's technical direction.

Responsibilities
- Own the end-to-end development of real-time algorithms, from concept and prototyping through validation and deployment.
- Define evaluation methodology, metrics, and failure analysis processes for sensing and imaging algorithms.
- Drive trade-off decisions among accuracy, latency, power, and memory across algorithm, HW, and system constraints.

We are seeking an experienced Signal/Image Processing and Machine Learning engineer to join our team. The role focuses on developing innovative, real-time deep learning and signal processing solutions for new sensing and imaging systems, including video restoration. You will be part of an interdisciplinary team developing technologies that will shape future Apple products.
Description
Algorithm and model development:
- Design, implement, and optimize signal processing and machine learning models for sensing and imaging tasks, including video restoration.
- Develop and validate models using real sensor data, simulated data, and public datasets.
- Prepare, filter, process, and analyze large-scale datasets to train and evaluate models.
- Analyze your algorithm's results and benchmark them against leading methods, and theoretical bounds.
- Optimize models for real-time performance, low latency, and resource efficiency on-device.

Sensing and research:
- Develop algorithms that combine classical signal processing with learned models to extract robust information from sensor data.
- Investigate efficient architecture patterns (lightweight backbones, attention mechanisms, recurrent designs) suitable for real-time, on-device inference.
- Explore how algorithmic approaches can mitigate artifacts and limitations of new sensing and imaging systems.
- Stay current with recent advances in signal processing, computer vision, and machine learning.

Collaboration and technical leadership:
- Work closely with ML researchers, SW, HW, sensor, and architecture engineers to translate research ideas into robust models and practical, shipping systems.
- Provide technical guidance and mentorship to junior engineers, and help shape the team's technical direction.

Responsibilities
- Own the end-to-end development of real-time algorithms, from concept and prototyping through validation and deployment.
- Define evaluation methodology, metrics, and failure analysis processes for sensing and imaging algorithms.
- Drive trade-off decisions among accuracy, latency, power, and memory across algorithm, HW, and system constraints.

As a manager in the RTL/FE CAD team, you have the opportunity to shape the future of chip design and impact our engineers who develop the next generation of our products! You will lead a high-impact team that develops software solutions used by thousands of RTL design and integration engineers globally across all chip families (iPhone, iPad, Mac, Apple Watch, and more).
In this role, you will be a key catalyst in transforming front-end hardware design into a modern, agile discipline. You will spearhead the transition to agentic workflows-redefining how RTL and integration teams operate in the AI era. This role combines deep knowledge of RTL/FE flows with modern software engineering practices, people leadership, and a transformative vision for engineering methodology.

Responsibilities
People Leadership: Lead, mentor, and grow a team of ~20 CAD engineers, driving talent acquisition, technical mentorship, performance management, and career development.
Agentic Flow & Methodology Transformation: Drive the team and broader RTL/FE community toward agentic workflows. Act as an organizational change agent, pioneering modern, agile methodologies that transform daily design and integration practices.
LLM Harness & Agentic Tooling: Own the architecture and execution of the LLM harness for RTL/FE flows (e.g., autonomous violation triage for Lint/CDC/RDC, intelligent connectivity synthesis, and design assist agents). Establish rigorous benchmarks to continually evaluate and elevate workflow accuracy and autonomy.
RTL Integration & Connectivity Tooling: Own end-to-end RTL integration tools, including connectivity generation, SoC assembly automation, IP packaging, and structural checks.
Static Sign-off Checks: Drive methodology, deployment, waiver governance, and sign-off metrics for Lint, CDC, RDC, and related static verification domains.
Roadmap & Milestone Alignment: Define strategic roadmaps and near-term execution plans aligned with multi-project tapeout milestones and long-term organizational goals.
Stakeholder & EDA Vendor Partnership: Collaborate closely with RTL design and integration leads to turn evolving design challenges into robust software solutions. Partner with EDA vendors to resolve escalations and influence tool roadmaps.
Software Excellence: Champion software engineering best practices, modern Python development, scalable cloud architectures, and robust CI/CD infrastructure within CAD.

Define experimental and theoretical research strategies to characterize light-tissue interactions, optical penetration, and thermal/mechanical effects in biological media.
Design, build, and operate experimental lab setups to investigate photo-induced tissue damage (e.g., dermal and ocular tissue models), defining precise biological damage thresholds and exposure margins.
Serve as the team's foremost authority on laser safety, leading formal laser classification (e.g., IEC 60825, ANSI Z136, FDA CDRH) and product safety compliance.
Translate complex biological damage models and physical limits into actionable system-level specifications, hardware constraints, and operational safeguards.
Define and design system level solutions for safety compliance.
Develop and validate analytical and numerical simulation models (e.g., Monte Carlo light transport, thermal bio-heat equations) to predict tissue response and optical safety margins.
Analyze and report empirical findings clearly, enabling cross-functional engineering teams to make rigorous, risk-informed architecture decisions.
Partner with multidisciplinary teams across hardware, firmware, optics, and human factors to drive feasibility from concept to safe, viable product implementations.

Responsibilities
Lead the biological and physical risk assessment for novel optical concepts, pinpointing exposure limits, hazards, and mitigation pathways.
Conduct hands-on lab experiments combining lasers and biological tissue models to measure, observe, and quantify damage mechanisms under varied irradiation profiles.
Formulate and own the formal laser product classification strategy, defining engineering controls, interlocks, and compliance documentation.
Characterize system-level physical limits and optical delivery parameters (wavelength, pulse duration, fluence, beam profile) to maximize performance while strictly adhering to safety standards.
Author comprehensive safety reports, compliance dossiers, and technical whitepapers to support engineering choices and regulatory alignment.

As member of the DV CAD team, you have the opportunity to impact our engineers who develop next generation of our products!
You will be responsible for developing software solutions used by thousands of DV engineers globally. You will be supporting design process of all chip families we make (iPhone, iPad, Mac, our Watch and more), and your work will help streamline this complex process. This role combines DV knowledge alongside modern software engineering practices. Your work will be very diverse, and you will have broad impact contributing to the success of us.


You will develop and drive software development of multiple tools across the DV space, including cloud-native services, GUI, LLM harness, CI/CD. Your work will span from software development and architecture to collaborating with DV engineers, working with EDA vendors, and supporting critical project milestones.

Responsibilities
Developing and maintaining LLM harness for agentic DV workflows, and being responsible for benchmarking and improving accuracy of agentic workflows.
Building and managing cloud-native services running on k8s, including CI/CD, containerization, alerting, databases, GUI and monitoring.
Communication with DV stakeholders and working to understand user requirements.
Writing and maintaining Python scripts used as part of design simulation flows.
Supporting multiple projects simultaneously.

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.