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
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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. You want to build large scale ML systems from the ground up. You care about making safe, steerable, trustworthy systems. As a Research Engineer, you'll touch all parts of our code and infrastructure, whether that's making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling. You're excited to write code when you understand the research context and more broadly why it's important. Note: This is an "evergreen" role that we keep open on an ongoing basis. We receive many applications for this position, and you may not hear back from us directly if we do not currently have an open role on any of our teams that matches your skills and experience. We encourage you to apply despite this, as we are continually evaluating for top talent to join our team. You are also welcome to reapply as you gain more experience, but we suggest only reapplying once per year. We may also put up separate, team-specific job postings . In those cases, the teams will give preference to candidates who apply to the team-specific postings, so if you are interested in a specific team please make sure to check for team-specific job postings! You may be a good fit if you: Have significant software engineering experience Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-
InMobi (Corporate) InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses — including InMobi Advertising and flagship consumer platform Glance — InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. InMobi Advertising InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach — including flagship consumer platform Glance — InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com. Glance Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV — shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com. Overview of the Role: We are looking for an Applied Scientist III to join our algorithmic and research science team. You’ll work on mathematically rigorous, research-driven problems at production scale. This role sits at the intersection of theory and application, designing algorithms that combine elegant modeling with measurable business impact. Specifically, our scientists tackle challenges across traffic shaping, fraud det
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 In this role, you will be a member of the Perception & Behavior team, leveraging the cutting edge of machine learning research to solve challenging real-world robotics problems. This role is focused on bringing advancements in the field of ML and large-scale learning to the AV domain, moving towards a more end-to-end autonomous driving system. This role requires working with and developing large models for perception and behavior, keeping up-to-date and experimenting with state-of-the-art architectures quickly and efficiently, collaborating with other teams to determine data and infrastructure support needs, and working to improve model optimization and inference speeds. You will use your applied research skills to think through the creation and deployment of these ML models on our autonomous vehicles while working alongside talented researchers in the field. If you love solving fundamental AI challenges and deploying your s
Become a part of our caring community Humana’s Quality and Cost Strategy Analytics Team is seeking a Research Scientist 2 (Remote). Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. The Quality and Cost Strategy Analytics team identifies opportunities and build solutions to improve clinical outcomes and lower costs for millions of Medicare Advantage beneficiaries leveraging data science & analytics, clinical expertise, strategic mindset, and rigorous study designs. In this multi-disciplinary team, you will have the opportunity to work closely with strategy partners and clinicians to shape Humana’s future enterprise clinical strategies and initiatives. The Research Scientist 2 will lead research, evaluation and development of opportunities that optimize healthcare delivery, lower medical cost while improve member health outcomes, through applying mathematical, statistical, epidemiologic and data science methods. The Research Scientist 2 will also partner with stakeholders across the enterprise to identify, prioritize and measure the impact of core and novel solutions to significant problems in healthcare and improve the health of especially underserved population, using high volumes of structured and unstructured data. Responsibilities As a Research Scientist 2, you will: Research, prototype and scale new ideas to improve population health and healthcare delivery Collaborate with analytic and business teams to set objectives, approaches, and work plans Collaborate with strategy to evaluate existing programs and identify and measure new solutions to impact healthcare Leverage a wide range of analytics methods ranging from descriptive to prescriptive to transform high volumes of complex data into analytics solut
Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. AI Algorithms Engineer (PHD Only) 5 Work Days Per Week Office Near to Kaki Bukit MRT, Singapore Relocate Near Tai Seng MRT in Mid-August 2026 Medical & Dental Benefits Provided Entitled to Yearly Bonus & Performance Bonus Job Requirements: PHD Holder in Computer Science, Applied Mathematics, Electrical Engineering, Pattern Recognition, Artificial Intelligence, Automatic Control, Operations Research, Biology, Physics / Quantum Computing, Neuroscience, Statistics or a related field. Familiar with common machine learning and deep learning algorithms and keeping track with the latest SOTA implementations . Strong programming skill in Python, C / C++ , proficient in mathematical / statistical concepts and exceptional coding skills Hands-on experience with AI / ML frameworks be familiar such as Caffe, PyTorch, TensorFlow, MxNet etc. Have rich project experience in machine learning and deep learning, be familiar with common algorithm models, such as CNN, RNN, LSTM, Transformer, ViT, etc., and be able to improve and innovate models according to actual problems. Experience in familiar the design, parameter tuning and optimization methods of neural network models is a plus Experience in model compression and in the transplantation and optimization of deep learning forward inference on various platforms, including NPU / GPU / DSP / ARM &nbs
About Sapience AI Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This is a research role focused on the models at the foundation of collective intelligence. You study, adapt, and advance the foundational models that power how Sapience AI understands language, knowledge, and reasoning. You work where research meets the platform: designing experiments, evaluating models, adapting them to the demands of professional communities, and feeding what you learn into the COGENT architecture and MINERVA. You bring scientific rigor to a fast-moving field, and you turn that rigor into advances the product can actually use. Why this role exists The quality of collective intelligence depends on the models beneath it. How well the platform understands a community’s language, grounds its answers, and reasons over knowledge starts with foundational model work done well. The field moves quickly, and not every advance is real or ready. Someone has to separate genuine progress from noise and turn the real advances into something the platform can rely on. The Foundational Model Research Data Scientist does that. You run the experiments, evaluate honestly, and translate frontier progress into dependable capability for Sapience AI. What y
About the AI Security Institute The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with direct lines to No. 10 (the Prime Minister's office), and we work with frontier developers and governments globally. We’re here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. The deadline for applying to this role is 18th October 2026, end of day, anywhere on Earth. Team Description Risks from misaligned AI systems are growing increasingly important as AI systems become more capable, autonomous, and integrated into society. Understanding these risks and stress-testing mitigations is crucial to ensuring advanced AI systems are developed and deployed safely and beneficially in the future. The Alignment Red Team is a specialised subteam within AISI's wider Red Team focused on detecting and evaluating misalignment in frontier AI systems. We perform novel research to develop techniques for finding misalignment, and pre- and post-deployment evaluations of frontier AI systems to understand loss-of-control risks associated with models, such as deceptive alignment, research sabotage, and reward-seeking. We share our findings with frontier AI companies and the UK and allied governments, to inform their respective deployments, research, and policy-making. We also work directly with safety teams at frontier labs, sharing our evaluation findings to help improve their model alignment training and monitoring methodology. We have conducted pre-deployment testing with multiple frontier AI companies for propensities related to research sabotage , cheating and unsanctioned cyber-attacks . We previously found t
Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state-of-the-art AI to accelerate discovery and drive transformative insights in biology—developing novel AI models purpose-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide. Our approach is comprehensive and integrated, bringing together world-class AI model development, exceptional engineering talent, high-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools. The Opportunity This role is part of the Data team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems. The data that trains biological frontier models comes in dozens of modalities—sequences, images, sp
Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. AI Algorithms Engineer (PHD Only) 5 Work Days Per Week Office Near to Kaki Bukit MRT, Singapore Relocate Near Tai Seng MRT in Mid-August 2026 Medical & Dental Benefits Provided Entitled to Yearly Bonus & Performance Bonus Job Requirements: PHD Holder in Computer Science, Applied Mathematics, Electrical Engineering, Pattern Recognition, Artificial Intelligence, Automatic Control, Operations Research, Biology, Physics / Quantum Computing, Neuroscience, Statistics or a related field. Familiar with common machine learning and deep learning algorithms and keeping track with the latest SOTA implementations . Strong programming skill in Python, C / C++ , proficient in mathematical / statistical concepts and exceptional coding skills Hands-on experience with AI / ML frameworks be familiar such as Caffe, PyTorch, TensorFlow, MxNet etc. Have rich project experience in machine learning and deep learning, be familiar with common algorithm models, such as CNN, RNN, LSTM, Transformer, ViT, etc., and be able to improve and innovate models according to actual problems. Experience in familiar the design, parameter tuning and optimization methods of neural network models is a plus Experience in model compression and in the transplantation and optimization of deep learning forward inference on various platforms, including NPU / GPU / DSP / ARM &nbs
Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world. About Binance Accelerator Program (BAP) Binance Accelerator Program is a concise 6-months program designed to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the world' s leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. You will be hired under a junior fixed term contract. Who may apply current students and recent graduates who can work full-time for a period of 6 months. Responsibilities Responsibilities Design and develop LLM-based agents for Web3 scenarios Build agents for token research and summarization Assist in developing and evaluating trading agents using market and on-chain data Experiment with prompt engineering, mcp, memory, and agent coordination strategies Requirements Strong background in data science, machine learning, or computer science Proficiency in Python and data processing pipelines Experience with agent orchestration, such as planning, routing, tool use, or multi-agent collaboration. E
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities Analyze semiconductor manufacturing data (yield, defects, process) to detect anomalies and drive yield improvements. Develop computer vision solutions for image and video use cases (e.g., automated inspection and defect detection). Build and productionize predictive models and robust analytical pipelines for high-volume manufacturing. Apply AI, LLMs, and agentic AI—with AI-assisted development tools—to accelerate analytics and automate engineering tasks. Partner with cross-functional teams, communicate insights clearly, and mentor junior data scientists. Qualifications & Skills Strong machine learning and advanced analytics expertise. Computer vision experience across image and video analytics. Solid database knowledge across relational databases, NoSQL, and cloud databases (Snowflake preferred). Hands-on experience with Generative AI, LLMs, and AI-assisted tools (e.g., Copilot, coding assistants). Solid software engineering discipline (Git, DevOps, Agile). Excellent English communication, able to explain technical insights to technical and non-technical audiences. Strong project management skills, with the ability to manage multiple priorities simultaneously. Proven ability to mentor and grow junior team members. Education & Experience Master's degree (or equivalent experience) in Statistics, Operations Research, Computer Science, Applied Mathematic
Senior Data Scientist [Data] • [Vancouver, BC] We're looking for a Senior Data Scientist to help define Asana's growth strategy as users increasingly discover and adopt software through LLM interfaces like ChatGPT, Claude, and Gemini. With millions of knowledge workers now starting their workday in conversational AI tools, we're at an inflection point in how productivity software reaches users. As part of the AI organization within Asana you'll leverage data to influence how we should build our agentic work management products. Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value. Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Work closely with Product Managers, User Researchers (UXR), and Engineers to understand the needs of our agentic work management customers, employing data frameworks and methodologies to understand our user segments and identify levers for driving user engagement Act as the data lead for specific AI features at Asana with product and engineering Use data analysis and data storytelling to identify key product opportunities for the roadmap Design experiments that measure product progress, and own key performance metrics. Collaborate with fellow Data Scientists in the team to research, identify and disseminate b
The AML Data Scientist will work under the supervision of a Functional Team Manager to provide ongoing support in terms of required analysis. The scope of analysis will cover all aspects of analysis performed by the team within different projects: Key Performance Indicator Driven Tuning and Tactical Tuning tasks, and data modeling/validation efforts depending on current needs and project plans. The Data Scientist will follow the globally consistent methodology but is expected to have a high level of initiative and creativity and suggest enhancements to current methodologies. The analyst evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. It requires good analytical skills to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Strong communication skills are required. Work and performance of all teams in the area are directly affected by the performance of the individual. Responsibilities : Apply quantitative and qualitative data analysis methods including Python (and R), SQL to extract, transform and analyze data. Prepare statistical and non-statistical data for visualization and exploration, validate data, identify data quality issues in AML risk related projects. Contribute towards AML Optimization techniques and related deliverables i.e. Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; write formal documentation using statistical vocabulary. Build Machine Learning (Predictive Modeling/ Classification/ Regression) models. Conduct data analysis, data mining, read and create formal statistical documentation, and work with
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Data Scientist Overview: Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. Role: We are seeking a highly skilled and motivated Lead Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. The successful candidate will play a leadership role in developing advanced analytics and machine learning solutions across cybersecurity, payments, and fraud. This person will also have formal people-management responsibilities for junior team members, helping them grow their technical capabilities, manage priorities, and deliver high-quality work. Job Responsibilities: • Lead the design, development, validation, and implementation of advanced analytical solutions, predictive models, and machine learning algorithms using large-scale payment, fraud, merchant, cybersecurity, and threat-intelligence data. • Provide technical leadership for graph analytics and modeling, including graph schema design, relationship modeling, community detection, link analysis, graph embeddings, and graph neural networks – all in service of
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