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we are looking for a Software Engineer to build and scale product experiences used by billions of people across our company, Instagram, WhatsApp, and Messenger. In this role, you will own the full software development lifecycle for consumer-facing or platform-level features, partnering closely with product management, design, and data science to define requirements, architect solutions, and ship high-quality, reliable systems at global scale.
Software Engineer, Product Engineering Responsibilities
Design, build, and maintain scalable full-stack product features across web and mobile platforms, from API design through front-end implementation
Own the technical design of product systems, evaluating architectural trade-offs to meet well-defined business requirements and drive engineering value
Instrument features with telemetry, dashboards, and alerting to establish observability before and during rollout, and use data to drive product and performance decisions
Run and review experiments using A/B testing frameworks to validate product hypotheses and make data-informed decisions that balance short-term goals with long-term quality
Manage staged feature rollouts using feature flagging systems, proactively monitoring for regressions and driving mitigation during incidents
Identify and resolve complex bugs across the stack, including non-reproducible and multithreaded issues, and implement defensive programming practices to prevent recurrence
Collaborate with product managers, designers, and data scientists to translate product requirements into technical specifications and executable engineering plans
Drive improvements to engineering efficiency by identifying bottlenecks in team workflows, building tooling and automation, and completing migrations that eliminate legacy code
Mentor other engineers on the team by sharing technical feedback, identifying growth areas, and contributing to code review standards and best practices
Proactively incorporate privacy, security, and integrity principles into early engineering stages and partner with cross-functional teams to ensure appropriate safeguards are in place.

This role will serve as the primary Global Business Group (GBG) Program Manager partnering directly with Cross Functional (XFN) Partners including Sales Strategic Planning & Operations, Marketing Science, Business Engineering, Creative Shop and HR to deliver reliable, high-quality execution.
You will directly manage programs while also shaping how our organization operates, helping manage interdependencies across concurrent initiatives, and ensure that program investments are prioritized and sequenced to deliver measurable business outcomes. You will partner with leaders and cross-functional stakeholders to translate organizational strategy into executable roadmaps, surface portfolio-level risks, and drive operational rigor across the programs you oversee.
The ideal candidate also demonstrates an AI-native mindset, approaching work with curiosity and a
bias toward experimentation. They instinctively reach for AI tools, adapt quickly to new workflows,
and view AI as a lever for greater impact by rethinking how work gets done.
This is a highly collaborative role that requires working across business, product, and engineering teams, as well as directly interfacing with and influencing leadership within and outside of our organization. You will need a demonstrated understanding of customer needs, industry trends and organizational effectiveness.
Strategic Program Manager, Global Business Group Responsibilities
Collaborate with In-market leads and cross-functional teams to design, plan, and deliver service solutions that solve clients and business problems
Lead the creation of holistic, omni-channel customer experience designs for new product and program launches
Develop and implement strategies to improve service experiences based on clients feedback and industry trends
Serve as the primary point of accountability for the organization across multiple complex workstreams - spanning diverse topics, stakeholders, and leadership teams
Develop and maintain a deep understanding of clients' needs, behaviors, and potential issues within their experience
Facilitate alignment across product, engineering, finance, and operations stakeholders to resolve competing priorities and unblock program execution
Collaborate with senior leadership to communicate strategic vision and tactical updates
Build scalable plans to deal with the most ambiguous situations, assessing resource needs and removing bottlenecks
Leverage AI, automation, and modern tools at the highest level to drive operational efficiency, standardize program management practices, and generate insight across the portfolio
Support business rhythm activities, including planning processes, business reviews, and OKR and goal-setting development
Build and own efficient processes, tools, and systems for tracking progress, follow-ups, and KPIs - bringing structure and discipline to ensure nothing falls through the cracks at scale
Build structured, systematic frameworks for decision-making based on data analysis and business insights.

Our team is looking for an FW engineer to design, develop, and implement complex SW modules for the Apple production line. The integration will require cooperation with other teams and vendors abroad. Youll be part of a team developing complex and versatile hardware/software integrated solutions for mission-critical tasks in future Apple products.
Are you a big-picture thinker who loves setting ambitious goals?
Do you have a passion for understanding how each line of code affects all the others?
Your dedication to cross-disciplinary collaboration will help develop groundbreaking technologies like iOS, macOS, watchOS, and tvOS. By crafting these distinct, holistic user experiences, youll continue to uphold and advance the excellence people expect from Apple devices.

Take part in SW design sessions (detailed designs involving system understanding), provide HLD and LLD documentation of central SW modules, participate in the coding of complex SW modules, debug complicated (system-wide) bugs, and lead HW-SW integrations.

Meta is seeking a Machine Learning Engineer to design, build, and deploy machine learning systems across a broad range of product areas including ranking, recommendations, natural language understanding, computer vision, and integrity. In this role, you will own the full ML development lifecycle - from data pipeline construction and feature engineering through model training, evaluation, and production deployment - contributing directly to systems that serve billions of users at global scale.
Machine Learning Engineer Responsibilities
Design and implement end-to-end machine learning pipelines spanning data ingestion, feature engineering, model training, offline evaluation, and production serving
Develop and optimize models for large-scale applications such as ranking, recommendations, classification, and natural language understanding
Instrument model performance with robust monitoring, alerting, and dashboards to detect regressions and maintain production reliability
Drive A/B experiment design and analysis to validate model improvements, articulate trade-offs, and make data-informed launch decisions
Architect scalable ML infrastructure and reusable components that accelerate development velocity across the team
Identify and resolve complex model quality issues through systematic debugging, root cause analysis, and defensive engineering practices
Collaborate with product managers, data scientists, and software engineers to translate product requirements into ML problem formulations and technical roadmaps
Define and evolve ML platform standards, coding best practices, and testing frameworks to improve engineering quality across the organization
Mentor other engineers on ML methodology, system design, and engineering craft, and contribute to recruiting by conducting technical interviews.

As a Data Scientist at our company, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining our company, you will become part of a analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and our company. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

We are looking for a sharp, detail-oriented student to join our Data Science team for a limited-term engagement. If you have a finance background, speak multiple languages, and enjoy digging into data, this is for you!

Lets get down to business:

About the Role

Shield FC is a leading innovator in the financial compliance space, serving some of the worlds largest banks and financial institutions. We help these organizations meet regulatory obligations by monitoring vast volumes of employee communications.

Our Data Science team builds NLP and LLM-based solutions that detect rare and subtle indicators of suspicious behavior hidden in massive streams of text. High-quality annotated data is the foundation of everything we build, and thats where you come in. As a Data Labeling Specialist, youll use your financial and linguistic expertise to label, review, and analyze real-world communication data, directly shaping the accuracy of our models.

Were looking for a Senior Backend Engineer who will join our team and make a big impact.

About the role

Youll join a small, high-ownership backend team building the systems that power Shields core platform, working mainly on data pipelines with a focus on the quality and structure of the data itself. We believe great engineers come from all backgrounds, and we actively work to build a team where everyone belongs and thrives.

What youll do

Design and implement new flows and services
Maintain, improve, and extend existing backend services and APIs
Work with multiple data stores - relational, NoSQL, search (Elasticsearch, etc.)
Maintain and build event-driven pipelines using message brokers (Kafka, RabbitMQ, or similar)
Collaborate with product and architecture on scalable, resilient system design
Integrate and leverage AI tools in your daily workflow - and ideally, build them

As a Data Scientist at our company, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining our company, you will become part of an analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and our company. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
This is a short term employment (STE) position.
Data Scientist, Product Analytics STE 18 Month Contract Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

As a Wireless SOC Design Verification Engineer, you'll be at the heart of the chip design effort - owning a meaningful verification scope and growing it project to project.
You'll work alongside DV methodologists, designers, architects, communication systems engineers, and firmware engineers to build reusable testbenches and verification environments using the latest metric-driven verification methodology.

You'll be responsible for pre-silicon RTL verification at the block, subsystem, and top-level SOC, taking your scope from test planning through coverage closure and signoff.
Your activity may focus at block level, subsystem level, or top-level SOC, including end-to-end simulations of the entire data/control path.

Responsibilities
Own critical block, subsystem, and top-level SOC verification scope on wireless SOC projects
Architect and develop testbenches and verification environments using state-of-the-art, metric-driven verification methodologies
Define the verification plan; create, simulate, and debug test scenarios
Drive regression and coverage analysis to ensure high-quality DV
Collaborate with design and systems engineering teams to review requirements, specifications, and architecture - extracting features and defining DV attributes
Verify power intent using UPF within your area; low power is part of your scope wherever it shows up
Over time, you can grow deeper into the IPs and subsystems you know best, or broader - across IPs and up from block level to full SOC integration.
The team is also pushing hard on AI-assisted verification, and you'll help figure out where it fits best: test generation, debug, coverage closure, or all of the above.

Join our Cutting-Edge Journey as a Technical Program Manager (TPM)
Are you an energetic, self-driven problem-solver with a knack for turning chaos into clarity? We are searching for a Technical Program Manager (TPM) to join our R&D Program Management team. This is your chance to make a direct impact on the future of Advanced Driving Assistance Systems (ADAS), L2+, and Autonomous Vehicles.
As a TPM, youll thrive in a dynamic environment, spearheading large-scale, cross-functional projects that are pivotal to our success. Youll be at the intersection of high-level strategic planning and hands-on implementation, working closely with C-level executives, engineering teams, and other key stakeholders. If you have a passion for tackling complexity and driving innovation, this role is for you.
What will your job look like:
Take ownership of the end-to-end execution of critical projects, aligning with our Product Group vision.
Lead in a dynamic environment, finding creative solutions to ensure smooth execution across departments.
Leverage your hands-on software development expertise and architectural understanding to align technical implementation with business goals.
Proactively identify and remove roadblocks, enabling engineering teams to focus on innovation.
Collaborate with senior executives to deliver high-impact results, influencing strategic priorities.
Foster streamlined processes and technology improvements to reduce friction and accelerate delivery.

we are seeking a Staff Data Scientist to drive product strategy and decision-making across our family of applications, including our company, Instagram, Messenger, WhatsApp, and our company's emerging platforms. 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 at Meta. 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.

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.