Machine Learning Engineer Radar Jobs

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. 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 across advertising, marketing, data and content platforms are shaping consumer experience in a world of connected devices. InMobi Group has been recognized on both the 2018 and 2019 CNBC Disruptor 50 list and as one of Fast Company’s 2018 World’s Most Innovative Companies. What’s

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions. As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders. We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S. Target Skills and Expertise The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves: Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling. ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch). End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models. Data Pipelines: Experience orchestrating large-scale data generation an

Who are we: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition, to statistical inference analyzing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As part of this team you will be tasked to apply machine learning and specifically deep learning techniques to trading problems while staying connected to broader research community. The researcher will put theory into practice and can immediately impact the global trading landscape with the expanding presence of Graviton in various markets. Description Lead research in applying machine learning to a wide variety of datasets and trading problems Follow latest developments in academic research and incorporating research techniques from different fields of applications to our problems Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques Work on current and develop new deep learning models to exploit large pool of in-house features and computing infrastructure Develop scalable pipeline for building predictive models across global markets Discover and implement new sources of predictive alpha, verify that they improve existing models, and integrate them into the firm's strategy development pipeline Partner with quant researchers and software developers in implementation of conducted research to production using Python / C++ Advise infrastructure support team on latest developments on hardware and software to improve computing infrastructure for ML based research Qualifications Masters or PhD in Computer Science, Mathematics, Statistics, or a related field At least two years of demonstrated experience of ML/AI research in a professional setting or at a repu

About Us Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery. If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time. About the Team You’ll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you’ll collaborate with Product and Business leadership to translate ML capabilities into product value. This is a high-visibility role with a direct line to executive leadership and significant influence over product direction. About the Role We are looking for a Director of Machine Learning to define our ML strategy, lead our computer vision organization, and drive the next phase of ML maturity at Gather AI. You will assess existing ML and CV capabilities, identify gaps and opportunities, and establish a clear technical vision for how machine learning will power our warehouse intelligence platform over the next 12–18 months. The ideal candidate brings deep computer vision expertise, a track record of shipping production ML systems, and the leadership experience to build and scale a world-class ML team. What You’ll Do Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives Lead and grow the Machine Learning and FPT teams

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. With Roblox’s daily active users growing at a record pace, we are seeking experienced machine learning researchers who thrive on solving complex challenges and designing scalable, ground breaking solutions. In this role, you will innovate on LLMs, VLMs, autoregressive models, or other large models for user understanding, content understanding, recommendation, and agentic search. Your work will lay the foundation for personalizing user experiences, enhancing engagement and retention, and driving growth within the creator ecosystem. In search and discovery, you will contribute to the core systems that enable users to discover and interact with experiences across Roblox. On Search, that work spans the end-to-end user search journey, covering query suggestions, autocomplete, and retrieval and ranking. These systems drive exploration and engagement across all surfaces, helping users find relevant and exciting content. Looking ahead, our team aims to innovate further by developing auto-generated summaries, images, and videos from experience content to improve discoverability and inspire user exploration. Our mission is to connect a billion users with the best content and connections at the right

About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlo

About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlo

About the Collective The Human Frontier Collective (HFC) ’s mission is to bring the world's best minds to shape the future of AI – because the future of AI depends not only on powerful models, but on the people who teach them to think. We bring together researchers, academics, and domain leaders across 70+ fields – over 90% of members hold doctorates – to shape how frontier AI systems are built, evaluated, and governed. HFC members have since co-authored published work including SciPredict , PropensityBench , and Professional Reasoning Benchmark . Why join the HFC HFC centers on three core pillars: the network itself, participation in selected AI/ML projects, and opportunities to publish with our research team. Join a unique and exclusive expert network: You’ll become a part of an interdisciplinary community, consisting of over 90% doctorates and field leaders representing 70+ fields from the leading institutions. We’re a collective of top innovators and thought leaders committed to advancing frontier AI to power the world’s most important decisions. Participate in AI/ML projects: Beyond the collective network, you’ll be regularly invited to work on high-impact projects with Scale AI and its affiliated lab and platform: building AI safety and policy guardrails, helping models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and more. Co-author selected research publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who should apply Background : PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field. Skills : Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlo

JOB DESCRIPTION Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field. Superb analytical and quantitative skills, along with a healthy streak of creativity. Demonstrated ability to conduct independent research utilizing large data sets. Passion for seeing research through from initial conception to eventual application. Curiosity about financial markets Strong scientific programming in Python, R or Matlab. Empirical, detail-oriented mindset. Sense of ownership of his/her work, working well both independently and within a small collaborative team. We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear abou

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 learned behavior team is to use advanced machine learning techniques to accelerate software progress. In this role, you will work closely with the software vertical teams to understand their pain points and explore novel and advanced machine learning methods to solve practical real-world challenging problems. To name a few, using self-supervised learning to learn robust representations, exploring techniques for out-of-distribution detection to solve long tail problems, adjusting reinforcement learning techniques for motion planning, working on trajectory prediction and motion planning, investigating the robustness of models to mitigate uncertainties, or trying to build an end-to-end driving system. If you love solving challenging new problems with a mindset of deriving practical solutions to eventually be used on the vehicle, come join us! About the Work Work on scalable machine learning based planning and pre

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 Work Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation. Build generative models with foundation models. Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation. Optimize generative models using reinforcement learning to improve interactive reasoning. Explore reward modeling/learned verifier using generative models. Explore joint prediction and planning and self-play. Leverage generative models for active learning and world modeling. Develop controllable generative models to guide the generation process towards desired goals, conditions and rewards. Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them, evaluate

MTS - Machine Learning — Fab 10A, Singapore. Apply via Workday.

Member of Technical Staff (MTS), Machine Learning, SMAI — Fab 10A, Singapore. Apply via Workday.

Use Your Power for Purpose At Pfizer, our purpose is to deliver breakthroughs that transform patients' lives. Central to this mission is our Research and Development team, which strives to convert advanced science and cutting-edge technologies into impactful therapies and vaccines. Whether you are engaged in discovery sciences, ensuring drug safety and efficacy, or supporting clinical trials, your role is crucial. You will leverage innovative design and process development capabilities to expedite the delivery of top-tier medicines to patients globally. Role Summary Pfizer’s Machine Learning and Computational Sciences (MLCS) group is seeking a Senior Machine Learning Scientist to lead independent and collaborative research in computational antibody design and optimization. This position focuses on developing and applying modern computational and machine-learning approaches to accelerate the discovery of next-generation biologic therapeutics. Positioned at the intersection of machine learning, protein science, and therapeutic discovery, the role is ideal for candidates eager to translate foundational AI research into real-world drug design. It offers the opportunity to join an innovative, collaborative environment that supports professional growth through mentorship, knowledge sharing, and the freedom to pursue impactful science. What You Will Achieve In this role, you will: Conduct original research in computational antibody engineering, with an emphasis on sequence- and structure-based generative modeling. Develop and deploy state-of-the-art machine-learning methods for multi-objective, constraint-aware antibody optimization that balances affinity, stability, and developability. Apply proprietary computational frameworks and machine-learning models to predict antibody developability and affinity. Leverage NGS-derived antibody repertoires to info

Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group Prototype, test and productionize ML models using scalable infrastructure Own key technical deliverables within larger projects and help shape the team’s research roadmap Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies Keep raising the bar through code and design reviews across projects Translate complex results into clear stories for technical and non-technical audiences Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence QUALIFICATIONS: PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data Proven track record of innovation and technical leadership in complex method development projects Expertise in deep learning and multimodal foundation models Proficient in Python and its scientific computing ecosystem Scientific rigor throughout the R&D process, with eagerness to teach and learn new computational methods and biology Excellent co