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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.

The Research and Development team is seeking a leading Applied Innovation Architect.
The team focuses on providing technological solutions to core challenges
through technological research and driving applied innovation to bridge the gap
between core needs and technological opportunities.

We are looking for an experienced engineer to work on systems that bring together many moving parts. Inertial sensors, visual sensors, wireless radios such as UWB, Bluetooth, and Wi-Fi, GNSS, and on-device processing all come together here, and much of what these systems do emerges from the interaction between those pieces rather than from any one of them alone. Understanding that interaction is most of the work, and it is what makes the problems here genuinely interesting.

The role has two sides, and we mean both of them equally. You will help decide how a system is put together: where functionality should live, how the components talk to each other, and what we trade away to get what we need. You will also be the one who builds it, writing production code, bringing up new hardware, and chasing down the failures that only appear on real devices. We have found that these two things belong together. The best designs come from people who have built the system, and the best implementations come from people who understand the whole of it.

Responsibilities
Help define the architecture of multi-component location systems spanning hardware, firmware, and software, and implement the interfaces that hold them together.
Write, review, and maintain production-quality code in C++, Objective-C, and Swift for systems that ship to our customers.
Design and implement how inertial, visual, and wireless sensing come together into a system that behaves as one.
Integrate and bring up new hardware and software components, working through the problems that only surface on real devices.
Weigh the tradeoffs between accuracy, latency, power, memory, and reliability, and bring partner teams along with your reasoning.
Debug complex issues across the full stack, where the root cause could sit anywhere from the sensor to the application.
Take new technologies from early prototype through evaluation and into production, fusing them with our existing capabilities.
Collaborate with silicon, hardware, firmware, and algorithms teams from first concept through shipping.
Build the tooling and instrumentation that let us characterize how a system really behaves, with data rather than intuition.
Participate in evaluating new signals and technologies as our platforms continue to evolve.

As part of our team, you'll collaborate with software engineers, program managers, security researchers, and data science experts to develop solutions that protect, detect, and respond to evolving cybersecurity threats.  

Responsibilities
As a Software Engineer you will:

Contribute to business-critical initiatives in our Security.

Requiring deep technical skills and the ability to quickly adapt to new areas.

Improve the end-to-end lifecycle of services.

Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.

Your role involves working on high-end technologies and collaborating across disciplines to deliver impactful features.

Collaborate with multiple teams across us to deliver key customer solutions and support technology.

Leverage AI and AI-assisted engineering tools (such as GitHub Copilot) in your day-to-day work to accelerate development, automate routine tasks, and improve code quality - while exploring opportunities to integrate AI capabilities into the services you build.

As part of our team, you'll collaborate with software engineers, program managers, security researchers, and data science experts to develop solutions that protect, detect, and respond to evolving cybersecurity threats.  

Responsibilities
As a Software Engineer you will:

Contribute to business-critical initiatives in our Security.

Requiring deep technical skills and the ability to quickly adapt to new areas.

Improve the end-to-end lifecycle of services.

Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.

Your role involves working on high-end technologies and collaborating across disciplines to deliver impactful features.

Collaborate with multiple teams across us to deliver key customer solutions and support technology.

Leverage AI and AI-assisted engineering tools (such as GitHub Copilot) in your day-to-day work to accelerate development, automate routine tasks, and improve code quality - while exploring opportunities to integrate AI capabilities into the services you build.

we are looking for a Staff Endpoint Software Engineer, Prompt.
As a Staff Backend Software Engineer, youll build the lightweight security components that power our Generative AI Security platform. This includes developing core sensors and enforcement mechanisms that operate across diverse environments-from endpoints and browsers to production workloads-enabling real-time, adaptive security. Youll collaborate with expert engineers, tackle high-impact security challenges, and expand your expertise in AI security, helping to shape the next generation of protection at scale.

We are looking for a skilled Malware Reverse Engineer to join our group. In this role, you'll analyze emerging cyber threats, dissect sophisticated malware families, and transform your technical findings into actionable insights.

In this role, you will architect and implement large-scale distributed systems, low-level platform components, and high-performance services that underpin core product stack. You will drive technical strategy across system reliability, performance, and scalability, partnering closely with product, infrastructure, and data engineering teams to deliver systems that operate at global scale with high availability and efficiency.
Software Engineer, Systems Responsibilities
Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across Meta's product infrastructure
Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
Leverage AI-assisted development workflows to accelerate design iteration, code generation, and systems analysis, applying sound judgment on when to rely on AI versus deep systems expertise
Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence

In this role, you will operate as a company-level expert in product analytics, partnering with Product, Engineering, and cross-functional leadership to translate complex, large-scale behavioral data into actionable insights that shape the experiences of billions of people worldwide. You will lead the design of rigorous analytical frameworks, advance forecasting and predictive modeling capabilities, and influence the highest-priority product investments through data-driven storytelling and strategic recommendations.
Data Scientist, Product Analytics Responsibilities
Lead the design and execution of complex analytical projects across product areas, applying advanced statistical methods, causal inference, and experimentation to evaluate product impact at scale
Develop and maintain sophisticated predictive models and forecasting frameworks to inform product roadmaps, goal setting, and resource prioritization
Define and evolve success metrics and measurement strategies for product initiatives, ensuring goals accurately reflect user and business value
Identify and size high-impact product opportunities by synthesizing behavioral data, qualitative signals, and business context across multiple data sources
Partner with Product and Engineering teams to design and analyze large-scale A/B tests and feature rollouts, translating results into clear recommendations for product direction
Build scalable, self-service data pipelines and visualization interfaces that enable cross-functional teams to explore and act on product performance data independently
Communicate complex analytical findings to diverse audiences including product leadership and executives through concise, compelling data narratives and presentations
Contribute to functional data science strategy by proactively identifying methodological gaps, championing analytical best practices, and setting goals across teams
Mentor other data scientists on analytical design, hypothesis formulation, and quantitative modeling, elevating the overall quality and rigor of the team's work
Collaborate with Data Engineering and Research partners to improve data infrastructure, eliminate bias in data collection, and ensure analytical outputs accurately represent the populations of interest

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk . The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work

we are looking for a AI Engineer.
Our R&D teams build and own the features that power platform - from deep code analysis to risk detection to developer-facing workflows. AI isn't a separate initiative here; it's how we build. Every engineering team is actively embedding LLMs, AI agents, and generative AI into the products they own, moving from experimentation to production and keeping things running reliably once they're there.
What You Will Do
Build and ship end-to-end AI-driven features and agentic workflows- from experimentation through validation to production deployment (Python and C#).
Design scalable backend services that support production-grade agentic AI capabilities.
Develop and improve solutions powered by LLMs, AI agents, multi-agent systems, and generative AI frameworks.
Evaluate agentic architectures and model performance, owning monitoring, reliability, and continuous improvement in production.
Collaborate cross-functionally with software engineers, data scientists, and analysts to drive AI innovation across the platform.

we are looking for a Software Engineer.
Our Engineering team builds the platform that powers Apiiro's mission: giving development teams the risk context to ship fast and stay secure. We work across a rich technical stack - from deep code analysis engines to customer-facing features - and take full ownership of what we build, from architecture to production. We move fast, collaborate closely with product and customers, and aren't afraid to tackle hard problems.
What You Will Do:
Build robust, scalable systems using a mix of languages, frameworks, and machine learning models, taking full ownership of features from idea to live product.
Collaborate directly with customers to understand their needs and integrate valuable insights into your work.
Drive cross-disciplinary initiatives across tech domains - from DevOps and infrastructure to data engineering and full-stack development - expanding your impact company-wide.
Partner with product and research teams to deliver innovative security capabilities that make a real difference for development teams.

we are looking for a Manager, Data Science & Research.
What will you do:
Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps
Design and build models across computer vision, NLP, and multimodal pipelines
Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment
Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)
Improve model quality (precision/recall) while balancing cost, latency, and scale
Drive automation systems (auto-labeling, auto-curation, retraining loops)
Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems
Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward
Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

We're looking for a talented DevOps Engineer to join our team. As a DevOps Engineer, you will architect and operate scalable, resilient cloud environments, using advanced automation and AI-based tools to improve system health, reduce manual intervention, and optimize infrastructure costs.
Responsibilities
Own the full lifecycle of the Coin Master platform. Ensure high availability, performance, and cost-efficiency across our multi-region AWS environment.
Design and maintain robust, high-performance infrastructure using IaC. You will focus on building self-healing environments where AI agents continuously monitor and remediate issues in real-time.
Embed security into the infrastructure layer. Leverage AI-assisted tooling to proactively identify and patch vulnerabilities across our Kubernetes clusters and AWS stack.
Build tools and services that empower our engineering team to ship code faster. You are the architect of the platform, ensuring it is intuitive, scalable, and fully automated.