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 About the job Who are we and What do we do? InMobi Group’s mission is to power intelligent, mobile-first experiences for enterprises and consumers. Its businesses acro
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WHO ARE WE? We are a bunch of super enthusiastic, passionate, and highly driven people, working to achieve a common goal! We believe that work and the workplace should be joyful and always buzzing with energy! CloudSEK , one of India’s most trusted Cyber security product companies, is on a mission to build the world’s fastest and most reliable AI technology that identifies and resolves digital threats in real-time. The central proposition is leveraging Artificial Intelligence and Machine Learning to create a quick and reliable analysis and alert system that provides rapid detection across multiple internet sources, precise threat analysis, and prompt resolution with minimal human intervention. Founded in 2015, headquartered at Singapore, we are proud to say that we’ve grown at a frenetic pace and have been able to achieve some accolades along the way, including: CloudSEK’s Product Suite: CloudSEK XVigil constantly maps a customer’s digital assets, identifies threats and enriches them with cyber intelligence, and then provides workflows to manage and remediate all identified threats including takedown support. A powerful Attack Surface Monitoring tool that gives visibility and intelligence on customers’ attack surfaces. CloudSEK's BeVigil uses a combination of Mobile, Web, Network and Encryption Scanners to map and protect known and unknown assets. CloudSEK’s Contextual AI SVigil identifies software supply chain risks by monitoring Software, Cloud Services, and third-party dependencies. CloudSEK’s AIVigil is an AI-native Attack Surface Monitoring platform that continuously discovers, monitors, and secures exposed AI infrastructure, MCP servers, leaked AI credentials, vector databases, agentic workflows, and shadow AI across the internet. Key Milestones: 2016 : Launched our first product. 2018 : Secured Pre-series A funding. 2019 : Expanded operations to India, Southeast Asia, and the Americas. 2020 : Won the NASSCOM-DSCI Excellence Award for Security Product Company
WHO ARE WE? We are a bunch of super enthusiastic, passionate, and highly driven people, working to achieve a common goal! We believe that work and the workplace should be joyful and always buzzing with energy! CloudSEK , one of India’s most trusted Cyber security product companies, is on a mission to build the world’s fastest and most reliable AI technology that identifies and resolves digital threats in real-time. The central proposition is leveraging Artificial Intelligence and Machine Learning to create a quick and reliable analysis and alert system that provides rapid detection across multiple internet sources, precise threat analysis, and prompt resolution with minimal human intervention. Founded in 2015, headquartered at Singapore, we are proud to say that we’ve grown at a frenetic pace and have been able to achieve some accolades along the way, including: CloudSEK’s Product Suite: CloudSEK XVigil constantly maps a customer’s digital assets, identifies threats and enriches them with cyber intelligence, and then provides workflows to manage and remediate all identified threats including takedown support. A powerful Attack Surface Monitoring tool that gives visibility and intelligence on customers’ attack surfaces. CloudSEK's BeVigil uses a combination of Mobile, Web, Network and Encryption Scanners to map and protect known and unknown assets. CloudSEK’s Contextual AI SVigil identifies software supply chain risks by monitoring Software, Cloud Services, and third-party dependencies. CloudSEK’s AIVigil is an AI-native Attack Surface Monitoring platform that continuously discovers, monitors, and secures exposed AI infrastructure, MCP servers, leaked AI credentials, vector databases, agentic workflows, and shadow AI across the internet. Key Milestones: 2016 : Launched our first product. 2018 : Secured Pre-series A funding. 2019 : Expanded operations to India, Southeast Asia, and the Americas. 2020 : Won the NASSCOM-DSCI Excellence Award for Security Product Company
WHO ARE WE? We are a bunch of super enthusiastic, passionate, and highly driven people, working to achieve a common goal! We believe that work and the workplace should be joyful and always buzzing with energy! CloudSEK , one of India’s most trusted Cyber security product companies, is on a mission to build the world’s fastest and most reliable AI technology that identifies and resolves digital threats in real-time. The central proposition is leveraging Artificial Intelligence and Machine Learning to create a quick and reliable analysis and alert system that provides rapid detection across multiple internet sources, precise threat analysis, and prompt resolution with minimal human intervention. Founded in 2015, headquartered at Singapore, we are proud to say that we’ve grown at a frenetic pace and have been able to achieve some accolades along the way, including: CloudSEK’s Product Suite: CloudSEK XVigil constantly maps a customer’s digital assets, identifies threats and enriches them with cyber intelligence, and then provides workflows to manage and remediate all identified threats including takedown support. A powerful Attack Surface Monitoring tool that gives visibility and intelligence on customers’ attack surfaces. CloudSEK's BeVigil uses a combination of Mobile, Web, Network and Encryption Scanners to map and protect known and unknown assets. CloudSEK’s Contextual AI SVigil identifies software supply chain risks by monitoring Software, Cloud Services, and third-party dependencies. CloudSEK’s AIVigil is an AI-native Attack Surface Monitoring platform that continuously discovers, monitors, and secures exposed AI infrastructure, MCP servers, leaked AI credentials, vector databases, agentic workflows, and shadow AI across the internet. Key Milestones: 2016 : Launched our first product. 2018 : Secured Pre-series A funding. 2019 : Expanded operations to India, Southeast Asia, and the Americas. 2020 : Won the NASSCOM-DSCI Excellence Award for Security Product Company
WHO ARE WE? We are a bunch of super enthusiastic, passionate, and highly driven people, working to achieve a common goal! We believe that work and the workplace should be joyful and always buzzing with energy! CloudSEK , one of India’s most trusted Cyber security product companies, is on a mission to build the world’s fastest and most reliable AI technology that identifies and resolves digital threats in real-time. The central proposition is leveraging Artificial Intelligence and Machine Learning to create a quick and reliable analysis and alert system that provides rapid detection across multiple internet sources, precise threat analysis, and prompt resolution with minimal human intervention. Founded in 2015, headquartered at Singapore, we are proud to say that we’ve grown at a frenetic pace and have been able to achieve some accolades along the way, including: CloudSEK’s Product Suite: CloudSEK XVigil constantly maps a customer’s digital assets, identifies threats and enriches them with cyber intelligence, and then provides workflows to manage and remediate all identified threats including takedown support. A powerful Attack Surface Monitoring tool that gives visibility and intelligence on customers’ attack surfaces. CloudSEK's BeVigil uses a combination of Mobile, Web, Network and Encryption Scanners to map and protect known and unknown assets. CloudSEK’s Contextual AI SVigil identifies software supply chain risks by monitoring Software, Cloud Services, and third-party dependencies. CloudSEK’s AIVigil is an AI-native Attack Surface Monitoring platform that continuously discovers, monitors, and secures exposed AI infrastructure, MCP servers, leaked AI credentials, vector databases, agentic workflows, and shadow AI across the internet. Key Milestones: 2016 : Launched our first product. 2018 : Secured Pre-series A funding. 2019 : Expanded operations to India, Southeast Asia, and the Americas. 2020 : Won the NASSCOM-DSCI Excellence Award for Security Product Company
ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic
About Us: Paytm is India’s leading mobile payments and financial services distribution company. A pioneer of the mobile QR payments revolution, Paytm builds technology that enables small businesses and consumers to participate in the digital economy. Our mission is to serve half a billion Indians and bring them into the mainstream economy through technology. About the Team: The Credit Risk Product Team is at the core of our lending operations, ensuring that our risk assessment models are efficient, scalable, and compliant with regulatory frameworks. The team collaborates closely with data scientists, engineers, and business stakeholders to develop and enhance credit risk models, decisioning frameworks, and risk mitigation strategies. By leveraging advanced analytics and machine learning, the team continuously refines underwriting processes to optimize loan performance and reduce defaults. About the Role: We are seeking a detail-oriented Credit Analyst to join our risk management team. The ideal candidate will be responsible for implementing credit risk policies, optimizing risk policies, and ensuring compliance with regulatory requirements. You will work closely with data scientists, product managers, and credit teams to enhance our underwriting models and decisioning frameworks. Key Responsibilities: * Analyze credit risk across various products, including merchant and personal loans, postpaid. * Liaison with the business team to understand the credit risk policies and implement the same on platform. * Implement the credit risk policies on our proprietary platform. * Monitor performance of credit risk policies. Share feedback with product and Policy team what's working well and what needs improvement. * Utilize alternative data sources, machine learning models, and traditional credit assessment techniques to enhance risk evaluation. * Conduct testing and scenario analysis to measure policy resilience. * Monitor key risk indicators (KRIs) and provide actionable
About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management role. We are looking for a leader with a solid data science and statistical foundation who can connect advances in experimentation methodology with scalable production systems. You will help set our technical and scientific direction, translating new statistical methods and machine learning research into capabilities that customers can use reliably at scale. You’ll partner closely with data scientists, engineers, product managers, and customers to advance the state of experimentation. The ideal candidate is equally comfortable discussing causal inference and statistical power with data scientists, distributed computation architectures with engineers, and experimentation strategy with customers. What You’ll Do Lead and grow the team responsible for Statsig’s data ingestion, experiment computation, and stats engine. Define the technical and scientific strategy for advancing experimentation across both Statsig Cloud and warehouse-native deployments. Partner with data scientists and engineers to turn new statistical and causal inference methods into scalable, reliable product capabilities. Evolve our data and computatio
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer - Multi-Agent Frameworks to join our AI Platform team. In this role, you will play a pivotal part in building a cutting-edge platform that empowers our users to create and deploy sophisticated intelligent agents, with a key focus on enabling collaborative and multi-agentic behaviors . This is a backend-focused role that requires deep expertise in AI, large language models (LLMs), and orchestration software. Key Responsibilities: Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination . Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration. Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems. Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications. Contribute
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and experienced Senior AI Engineer - Multi-Agent Frameworks to join our AI Platform team. In this role, you will play a pivotal part in building a cutting-edge platform that empowers our users to create and deploy sophisticated intelligent agents, with a key focus on enabling collaborative and multi-agentic behaviors . This is a backend-focused role that requires deep expertise in AI, large language models (LLMs), and orchestration software. Key Responsibilities: Design, develop, and maintain a robust platform to enable users to create and manage AI agents and their interactions. Integrate and work with multiple LLMs, ensuring seamless orchestration and scalability for both individual and coordinated agent operations. Leverage orchestration frameworks like LangGraph and others to build complex workflows and pipelines that support diverse agent functionalities, including frameworks for multi-agent coordination . Develop and implement evaluation frameworks for testing AI agents in challenging and complex scenarios, focusing on individual performance and system-level dynamics. Stay at the forefront of AI advancements, incorporating the latest research and technologies into our platform to enhance agent capabilities and collaboration. Collaborate with cross-functional teams, including product managers, designers, and frontend engineers, to deliver a seamless user experience for building and deploying intelligent systems. Address challenging AI privacy scenarios, ensuring compliance with data protection regulations and best practices within agent-based applications. C
As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r
As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r
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 Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing proble
About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h
About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. About the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Research and develop reinforcement learning algorithms Design and run experiments to study training dynamics and model behavior at scale Collaborate with engineers and researchers to integrate successful approaches into model training pipelines You might thrive in this role if you: Have a strong background in reinforcement learning, machine learning research, or related fields Have strong engineering and statistical analysis skills Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving Are motivated by seeing research ideas influence real-world AI systems About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an ex
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