Applied Ai Engineer Jobs

InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond. At InMobi Advertising , you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Position Summary: We look for talented Applied Scientists who can roll up their sleeves and have direct impact on our company metrics. The performance of our models and experiments a

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex The Data organization develops infrastructure, statistical models, and products using financial data. Our Scientists and Engineers work together to make data —and insights derived from data — a core asset across the company. Our work is ingrained in Brex’s decision-making process, in the efficiency of our operations, in our risk management policies, and in the second-to-none experience we provide our consumers. What You’ll Do Our Data Scientists are responsible for the entire model development lifecycle, from conception with stakeholders, through model development and productionization, to following through to see that the desired business impact is achieved — including circling back with stakeholders to make product or strategic decisions. Responsibilities Drive Data & AI solutions from inception to deployment to efficiently manage risk and/or improve customer experience. Be responsible for the full machine learning

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams

About the team The Applied team at OpenAI safely brings cutting-edge technology to the world. We have released groundbreaking products such as ChatGPT, Plugins, DALL·E, and APIs for GPT-4, GPT-3, embeddings, and fine-tuning. Our team also manages large-scale inference infrastructure. With much more on the horizon, our impact continues to grow. Our customers create fast-growing businesses using our APIs, enabling product features previously unimaginable. ChatGPT exemplifies the current scope of possibilities. We prioritize the responsible use of our powerful tools, valuing safe deployment over unchecked expansion. Within Applied Engineering, the Financial Engineering team ensures that our products are monetized effectively to accommodate customers' varying needs and scales. Collaborating closely with the GTM and Finance teams, we strive to tailor our billing stack to our evolving internal requirements. We seek an experienced engineer to architect and refine our billing systems, enhancing their functionality to meet the demands of our increasingly complex and expansive product offerings. In this role, you will: Architect and build the next generation of billing and monetization systems at OpenAI. Develop across the stack to create comprehensive billing integrations for our range of ChatGPT and API users. Design a versatile billing platform suitable for both subscription and usage-based offerings, ensuring scalability and enterprise readiness/flexibility. Construct and integrate tools that empower internal teams to seamlessly incorporate billing data into their workflows. Collaborate closely with a wide array of stakeholders, including the Product, Data, Finance, and Go-To-Market teams, as well as fellow engineers. You might thrive in this role if you: Possess a minimum of 5 years of professional software engineering experience, with added experience in payments, billing, or monetization seen as a bonus. Enjoy engaging with various partners, particularly those outside

About the team The Applied team at OpenAI safely brings cutting-edge technology to the world. We have released widely used products such as ChatGPT, Sora, and the OpenAI API, powering models including GPT-5 and a growing set of multimodal capabilities across text, image, audio, and video. Our team also manages large-scale inference and platform infrastructure that supports these experiences at global scale. With much more on the horizon, our impact continues to grow. Our customers build fast-growing businesses using our APIs, unlocking product capabilities that were previously unimaginable. ChatGPT and Sora exemplify the breadth of what’s now possible across text, image, audio, and video experiences. As these capabilities expand, we prioritize the responsible use of our technology, emphasizing safe and thoughtful deployment over unchecked growth. Within Applied Engineering, the Financial Engineering team builds the frontend platforms and workflows that power how OpenAI’s products are priced, purchased, and managed at scale. We work closely with Go-To-Market and Finance partners to translate complex commercial requirements into clear, reusable billing experiences. We’re looking for a frontend engineer to help define and evolve these billing platforms, shaping the primitives, interfaces, and patterns that product teams rely on as our offerings and customer needs continue to grow in complexity. In this role, you will: Create scalable, reusable UI components and patterns that support a wide range of billing use cases across products. Partner closely with backend engineers to deliver end-to-end billing capabilities spanning subscriptions, usage-based pricing, and enterprise offerings. Build tools and surfaces that allow teams like Finance, Sales, Support, and GTM to manage and reason about billing data efficiently. Create AI powered features for billing workflows and platform tooling to automate repetitive tasks, surface insights, and improve decision-making. Help define

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. What you'll do at Synthesia As a Research Engineer you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting-edge challenges in the Generative AI space, with a focus on creating high-quality, expressive and real-time synthetic voices. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses. If you are an expert in ML, LLMs, speech generation, conversational models , this is your chance to make a global impact. You will join our Audio Post-Training Team , which works on generative speech and voice synthesis , ensuring our in-house voice models reach production-level quality, speed, and robustness. Typical projects include: Develop and evaluate streaming and speech-to-speech systems, enabling low-latency, interactive voice synthesis. Adapt models for new conditioning inputs (emotion, speed, prosody, speaker control, etc.). Implement post-training optimization techniques (quantization, pruning, distillation) to improve efficiency and latency in real-time speech generation. Integrate and test novel architectures, such as neural codecs, diffusion, or

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

About the Team The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb

About the Team The Future of Computing Research team is an applied research team within OpenAI’s Consumer Devices group. We study how AI systems perceive people and their surroundings, and we turn that research into capabilities for future products. Our work spans machine learning, sensing, and hardware, with a focus on building systems that work beyond controlled environments. About the Role We’re looking for a machine learning engineer to help shape how future AI systems understand the physical world and the people in it. The role focuses on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors. You’ll work with specialized perception models and larger multimodal models, and partner with hardware, firmware, software, and product teams to bring new research into real-world systems. This role is based in San Francisco. We work in the office three days per week and offer relocation assistance. In this role, you will: Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals. Explore how specialized perception models and larger multimodal models can work together. Design data, training, and evaluation approaches that improve performance in real-world conditions. Study model behavior, robustness, and failure modes across sensing, data, and deployment environments. Integrate and validate new capabilities in real-time or resource-constrained systems. Work with hardware, firmware, software, and product teams to turn research into working systems. You might thrive in this role if you: Have a strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing. Have experience developing specialized machine learning models, larger multimodal models, or both. Have brought research ideas into practical systems, prototypes, or products. Know how to design experiments, build evaluations, and investigate model behavior. Have wo

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? At Fin, you will be a Senior Software Engineer - someone who solves real customer problems through a smart and efficient application of your technical knowledge and your tools. You’ll be part of one of our multidisciplinary product teams, where you will build both back-end and front-end systems, and work closely with designers, product managers, researchers, and data analysts. We’re facing many exciting scaling challenges and we’re building a robust platform where your expertise can be applied to areas such as building a beautiful messenger composer, rule matching, deliverability, security, app availability and machine learning, to name a few. What will I be doing? As an experienced engineer you will: Develop technical plans and contribute to our technical architecture as we scale our products to serve tens of millions of people every day. Write Ruby code, which knits together a lot of AWS, infrastructure, platform and SaaS technologies that form the core of Fin's

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? At Fin, you will be a product engineer - someone who solves real customer problems through a smart and efficient application of your technical knowledge and your tools. You’ll be part of one of our multidisciplinary product teams, where you will build both back-end and front-end systems, and work closely with designers, product managers, researchers, and data analysts. We’re facing many exciting scaling challenges and we’re building a robust platform where your expertise can be applied to areas such as building a beautiful messenger composer, rule matching, deliverability, security, app availability and machine learning, to name a few. What will I be doing? As an experienced engineer you will: Develop technical plans and contribute to our technical architecture as we scale our products to serve tens of millions of people every day. Write Ruby code, which knits together a lot of AWS, infrastructure, platform and SaaS technologies that form the core of Fin's backend

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? At Fin, you will be a product engineer - someone who solves real customer problems through a smart and efficient application of your technical knowledge and your tools. You’ll be part of one of our multidisciplinary product teams, where you will build both back-end and front-end systems, and work closely with designers, product managers, researchers, and data analysts. We’re facing many exciting scaling challenges and we’re building a robust platform where your expertise can be applied to areas such as building a beautiful messenger composer, rule matching, deliverability, security, app availability and machine learning, to name a few. What will I be doing? As an experienced engineer you will: Develop technical plans and contribute to our technical architecture as we scale our products to serve tens of millions of people every day. Write Ruby code, which knits together a lot of AWS, infrastructure, platform and SaaS technologies that form the core of Fin's backend

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? At Fin, you will be a product engineer - someone who solves real customer problems through a smart and efficient application of your technical knowledge and your tools. You’ll be part of one of our multidisciplinary product teams, where you will build both back-end and front-end systems, and work closely with designers, product managers, researchers, and data analysts. We’re facing many exciting scaling challenges and we’re building a robust platform where your expertise can be applied to areas such as building a beautiful messenger composer, rule matching, deliverability, security, app availability and machine learning, to name a few. What will I be doing? As an experienced engineer you will: Develop technical plans and contribute to our technical architecture as we scale our products to serve tens of millions of people every day. Write Ruby code, which knits together a lot of AWS, infrastructure, platform and SaaS technologies that form the core of Fin's backend

About the Team The Early Access Program (EAP) team leads high-impact alpha programs at the intersection of customers, Product, Research, Engineering, GTM, Security, Legal, and launch teams. We partner with customers to test emerging capabilities with real-world use cases, surface actionable insights, and support launch decisions. Our team is made up of builders who learn quickly, collaborate deeply, create clarity in ambiguity, communicate openly, and iterate constantly. About the Role We’re hiring an Early Access Deployment Engineer to lead technical engagements with customers who are leveraging our frontier capabilities to solve real-world use cases. You will work at the earliest—and often messiest—stage of development, when capabilities are still unclear, tooling and processes are evolving, and the path from promising technology to a valuable real-world application has yet to be defined. You will be a hands-on builder, problem solver, and technical partner to customers and our research/product team. You’ll push beyond initial assumptions, identify high-value use cases, prototype solutions, design useful evaluations, and troubleshoot what is and is not working. Managing multiple customer engagements at once, you will help customers navigate ambiguity and difficult technical decisions while translating their experience into clear, actionable feedback for Research and Product. You will also own the end-to-end execution of early access programs—from onboarding customers, supporting live experimentation, synthesizing findings, and informing launch decisions. You’ll collaborate deeply with Research, Product, Engineering, Applied Evals, GTM, Legal, Security, Marketing, and other launch partners to create clarity, manage risk, and keep programs moving through changing conditions. Success in this role means turning frontier capabilities into real-world customer value and high-quality research signals. You will develop reusable technical approaches from early deployments,

Ignite your curiosity. Solve the unsolvable. At Leidos, we do more than write code—we decode the unknown. Our San Diego-based research and engineering team takes on some of the nation’s toughest defense challenges using advanced signal processing, ocean remote sensing, and high-performance computing. We’re seeking a Software Engineer / Computer Scientist who enjoys solving complex problems and pushing the limits of performance. In this role, you’ll work alongside a multidisciplinary team of scientists and engineers with expertise in hydrodynamics, physics, acoustics, and signal processing to build impactful software that turns massive, complex data sets into meaningful insight. If you are motivated by innovation, energized by collaboration, and excited to see your work support real-world missions, this could be the right opportunity for you. What You’ll Do Collaborate with scientists and engineers to design, develop, and optimize advanced algorithms for next-generation radar, optical, and infrared sensor systems. Build scalable, high-performance backend systems for scientific computing in distributed environments. Integrate, refactor, and improve scientific codebases to increase efficiency and scalability. Translate and optimize existing code for GPU/CUDA acceleration and parallel or distributed execution. Test, document, maintain, and enhance complex software in Linux/Unix environments. Contribute in a collaborative environment that values technical excellence, creativity, and continuous growth. Required Qualifications Bachelor’s degree in Computer Science, Applied Mathematics, Physics, or a related field with 4+ years of backend software development experience, or a Master’s degree with 2+ years of experience. Equivalent experience may be considered in place of a degree. U.S. citizenship and the ability to obtain a Top Secret clearance; active Top Secret clea