Machine Vision And Aoi Sr Engineer Jobs

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our software team is growing, and we are looking for talented engineers to join us and be instrumental to one of the following areas: Data Platform, Simulation, and Technical Infrastructure. Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection. Simulation: The Simulation team builds the simulator that allows us to develop and test our autonomous driving technology in a virtual setting. We work on the core simulator and simulation frameworks, sensor simulation, scena

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. We are seeking a highly motivated software development engineer in test (SDET). This role is central to leading the creation of automation frameworks, tools, and processes for platform safety clearance and system testing. The ideal candidate is passionate about developing high-quality, robust, optimized, and reusable software infrastructure, and is eager to advance their skills in complex systems thinking and validation problem-solving. Some examples of tools this role has supported in the past: * Front and back end of Streamlit web-app to automate tracking requirements to test case traceability. * Automation framework for execution of safety critical tests. * CI/CD job to identify affected requirements and HIL tests from code changes and automate the execution of all linked tests. In this role, you will: Create tools and web-apps to help us automate and streamline manual clearance processes. Propose tools and/or feature ideas to the team to improve processes. Develop software for automated validation frameworks for system level testing in Hardware In the Loop (HIL), simulation environments, and post-processing of test data. Develop and maintain dashboards to illustrate progress against targets and highlight focus areas. Execute, triage, and debug automated verification and validation system tests. Qualifications B.S. or higher in Mechanical Engineering, Electrical Engineering, Systems Engineering, Computer Engineering, Computer Science or a related technical degree. Experience developing automated test frameworks and tools for

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The mandate of the prediction team is to use advanced machine learning techniques to improve the behavior of the Nuro Driver. As a key member of the Prediction and Smart Agents team, you will focus on building state-of-the-art models for predicting the behavior of surrounding traffic. These models are crucial for our autonomous system, as they will be deployed onboard as part of our planning stack and used offboard for realistic closed-loop simulation. You will explore novel machine learning methods to solve challenging real-world problems in autonomous driving. This work includes using generative sequence modeling approaches for robustly predicting complex, interactive traffic situations. It requires deep reasoning about the intentions of other road users and how their behaviors influence safe and correct driving decisions. You will also use different input modalities, including End-to-End (E2E) approaches, for predicting

Scale AI sits at the forefront of enabling machine learning for advanced robotics systems. As an Operations Program Manager focused on data creation for robotics models, you will design and execute the solutions, tools, and processes that power high-quality training data at scale. You’ll ensure precise, timely delivery of datasets that drive perception, manipulation, and autonomous decision-making in robotic platforms. With rapid growth, new customer onboarding, and continual product innovation, we face both strategic questions and hands-on operational challenges—your contributions will be key to solving them. You will be part of a highly motivated team of operators and collaborators who will ensure steady delivery and customer satisfaction. You are relentless in driving stellar results, running pilots, tests, and experiments, then handing over new designs to a team of skilled operators. The blend of operations, process improvement, and cross-functional leadership make this a unique and exciting role that will provide an opportunity to work with multiple teams (e.g., Engineering, Marketing, Operations, Analytics, and several others) across the company and around the globe. You will: Drive some of our most critical operational processes Improve existing processes and tools globally Collaborate with stakeholders to improve processes for new and existing customers Create an effective feedback loop between the frontline, product, strategy, and customers Build, maintain, and regularly communicate detailed reporting for other leaders across the company who will use your team's data to inform their own operations and strategy Ideally you'd have: Industry experience in supply chain, finance planning, in an operational role and/or in a top tier consulting firm An undergraduate degree from a top university in an analytics heavy major (e.g., Engineering or Economics) and/or a graduate degree from a top university in Engineering, Economics, or Business Experience leading day to

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Site Reliability Engineer (SRE) - Security and Data Systems Our company is seeking a highly skilled Senior Site Reliability Engineer to join our team. We are a SaaS company specializing in securing large-scale systems. This role is a blend of software engineering and systems administration, where you'll be responsible for building and maintaining highly reliable, scalable, and secure infrastructure. You will be a key contributor, applying your expertise to automate manual processes and proactively solve complex problems before they become incidents, handling incidents, and includes on-call shifts. Responsibilities Platform & Reliability: Design, build, and maintain the core infrastructure that underpins our security SaaS offerings, ensuring high availability, performance, and scalability. This includes building and operating the tooling for our Snowflake data systems. Automation: Develop robust automation using code to eliminate toil and ensure consistency across our environments. You'll be a key driver in automating everything from infrastructure provisioning to application deployment and incident response. Security & Compliance: Work closely with our security teams to embed a security-first mindset into all our processes and infrastructure. You will be responsible for ensuring our systems and data platforms are compliant with industry standards. Incident Response: Participate in on-call rotations and be a primary responder for critical inci

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Site Reliability Engineer (SRE) - Security and Data Systems Our company is seeking a highly skilled Senior Site Reliability Engineer to join our team. We are a SaaS company specializing in securing large-scale systems. This role is a blend of software engineering and systems administration, where you'll be responsible for building and maintaining highly reliable, scalable, and secure infrastructure. You will be a key contributor, applying your expertise to automate manual processes and proactively solve complex problems before they become incidents, handling incidents, and includes on-call shifts. * This position requires the ability to access U.S. National Security information. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15 ) upon hire. Responsibilities Platform & Reliability: Design, build, and maintain the core infrastructure that underpins our security SaaS offerings, ensuring high availability, performance, and scalability. This includes building and operating the tooling for our Snowflake data systems. Automation: Develop robust automation using code to eliminate toil and ensure consistency across our environments. You'll be a key driver in automating everything from infrastructure provisioning to application deployment and incident response. Security &amp

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. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. 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.&n

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. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. 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.&n

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Celonis Services is a strategic organization focused on optimizing our customers' business processes through technical expertise. We integrate Consulting Services, Academy, and Customer Support to deliver comprehensive solutions. As thought leaders with deep product, technical, and domain expertise, we specialize in implementing Celonis to drive the adoption of process intelligence, ultimately transforming and improving our customers' core business operations. We achieve this by leveraging our best practices, extensive delivery experience, award-winning enablement programs, and robust support infrastructure. The Role: As a Lead AI Deployment Architect, you will work directly with customers to understand their problems and design, deploy and scale innovative AI solutions and automations using our Process Intelligence platform. In a pre-sales and post sales capacity you will work closely with other AI experts across Product & Engineering and GTM to standardize these solutions and bring them to our customer base at scale. We are ideally looking for individuals with in-depth practical experience in delivering solutions to our customers. The work you’ll do: Architect & Deploy: Prototype, develop, and scale end-to-end AI

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. As a Systems Engineer at Zoox, you will be working with cross functional teams including product, feature, operations, vehicle engineering, software, autonomy, and legal to design, develop, and deploy systems that enable and support safe autonomous driving. You are responsible for ensuring these systems are developed within a safety engineering process that results in end-to-end traceability and achievement of both system safety targets and product requirements. In this role, you will: Lead powertrain safety and fail-operational design and analysis covering high-voltage battery systems, charging, propulsion, and on-vehicle load management Architect vehicle-level safety concepts, focusing on fault tolerance, and fail-operational behaviors necessary for supporting autonomy and ensuring mission assurance on the vehicle’s powertrain functions Develop vehicle level safety concepts covering fault detection, and vehicle level reaction for ensuring the powertrain systems can achieve mission objectives under presence of faults Own the delivery of key work-products including hazard analysis risk assessment (HARA), fault tree analysis (FTA), functional safety concept, vehicle level safety requirements, safety clearance artifacts, and quantitative residual risk assessments Drive consensus across product, feature, operations, vehicle engineering, software, autonomy and legal teams to implement and release safety requirements Qualifications B.S. or higher degree in Automotive, Aerospace, Robotics, Computer Science, Electrical, Mechanical, or

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: Overview of the product so far Training docs overview Story of the Training product Research we've done EXAMPLE INITIATIVES Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enabling

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 Location: Bangalore - In Office Reports To: CHRO (with strong SIG – Strategic Investment Group / CEO / CFO partnership) About InMobi Group &nbsp

About the Team: A well-established quantitative portfolio management team at Point72 is looking for an experienced quantitative professional to develop and trade systematic macro strategies, with a focus on market microstructure. The candidate will be given the resources and support to drive the build out and expansion of the quantitative macro business. Role/Responsibilities: Perform rigorous and innovative research to develop systematic signals for global macro (futures, FX, etc.) markets, with a focus on market microstructure signals Perform feature engineering with order book tick data at intraday to daily horizons Perform feature combination using various modeling techniques ranging from linear to machine learning models Participate in the research pipeline end-to-end, including signal idea generation, data processing, modeling, strategy backtesting, and production implementation Help drive the growth of the investment process and research capabilities of the team Work in a team of highly qualified and motivated individuals with access to a cutting-edge research and trading infrastructure and clean datasets Assist in building, maintenance, and continual improvement of production and trading environments Requirements: MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics 4+ years of experience in quantitative research, building statistical models for intraday to daily trading, as part of a successful proprietary trading team with a track record Knowledge of market microstructure for futures and/or FX Prior experience with tick data based feature generation, modelling, and monetization Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards

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. About the role The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data. This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position . You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: A strong background in data-centric, applied Machine Learning, with hands-on experience improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone Experience working on the data la

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are looking for Software Engineers to join our team. This is a specialized, high-impact role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work. RESPONSIBILITIES Benchmarking : Evaluate, run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving). DevEx Improvement : Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation. Tool Development : Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking and analysis. System Profiling : Use profilers like PyTorch Profiler, NVIDIA Nsight Systems and py-spy to collect performance profiles, identify bottlenecks, and debug the compute/networking stack. Monitoring & Observability : Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance. Continuous Integration : Automate performance