The firm is looking for a quantitative researcher to join a new Cross Asset Risk team.
\nThe goal of the team is to build a unified set of risk data for decision-makers at the firm level to make informed decisions about the firm's complex set of positions. The team will be coordinating with multiple different asset-class risk teams to build the firm's high-level view, including building out individual asset-class risk analytics in cases where it is deemed necessary.
\nThis role involves research into using many different statistical and probabilistic techniques to evolve the firm's understanding of risk. Key to the role will be understanding the ways in which different market structures impact their individual asset classes, the behavior of large market participants, shared traits of popular trading strategies, and developing probabilistic methodologies to anticipate potential stress scenarios.
\nResponsibilities:
\nRequirements:
\nThe estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future.
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\nYour responsibilities will include identifying areas where ML can create value for our customers, identifying the right ML framing of product problems, working with teammates and Product and Design stakeholders, conducting exploratory data analysis and research, deeply understanding the problem area, researching and identifying the right algorithms and tools, being pragmatic, but innovating right to the cutting-edge when needed, performing offline evaluation to gather evidence an algorithm will work, working with engineers to bring prototypes to production, planning, measuring & socializing learnings to inform iteration, and partnering deeply with the rest of team, and others, to build excellent ML products.
\nTo be successful in this role, you will need to have broad applied machine learning knowledge, 3-5 years applied ML experience, practical stats knowledge (experiment design, dealing with confounding etc), intermediate programming skills, strong communication skills, both within engineering teams and across disciplines, comfort with ambiguity, typically have advanced education in ML or related field (e.g. MSc), and scientific thinking skills. Bonus skills and attributes include track record shipping ML products, PhD or other experience in a research environment, deep experience in an applicable ML area. e.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering, strong stats or math background, visualization, data skills, SQL, matplotlib, etc.
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\nWe're looking for a Senior Machine Learning Engineer to join our Monetization team. As a key member of the team, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.
\nKey responsibilities include:
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\nNice to have:
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\nThis position is not eligible for relocation assistance.
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\n[2026] Senior Machine Learning Engineer, Engine Optimization - PhD Early Career
\nSan Mateo, CA, United StatesEarly CareerID: 5626
\nEvery 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.
\nAt 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.
\nA 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.
\nOur engine’s resource management and streaming systems are critical to delivering a smooth, stable, and responsive experience for Roblox users across a huge range of devices and network conditions. These systems work together to intelligently allocate compute, memory, bandwidth, and rendering quality while dynamically delivering world content in real time as players move, explore, and interact. The challenges span highly dynamic environments, unpredictable user behavior, and opaque signals from device and OS constraints.
\nThis role offers a rare opportunity to pioneer the application of machine learning in real-time engine optimization. You will establish the ML framework for predictive resource allocation and content fetching, replacing heuristic-based logic with adaptive, data-driven decision-making. Your work will directly shape stability, visual quality, responsiveness, and content delivery across billions of global play sessions.
\nYou Will
\nYou Have
\nBenefits
\nAs a full-time employee at Roblox, you will be eligible for equity compensation and benefits as described on this page.
\nSalary
\nThe starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future.
\nAnnual Salary Range
\n$195,780—$242,100 USD
\nWork Schedule
\nRoles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
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\nMicrosoft AI are looking for a talented Senior Applied Scientist at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.
\nAbout the Role
\nAs a Senior Applied Scientist, you will join the asset generation team in Microsoft AI focusing on image and video retrieval, recommendation and generation. You will build core generative AI solutions that power customer-facing AI solutions and services for Microsoft Advertising at Bing platforms. In this role, you'll combine solid computer vision skills with applied ML expertise to design, prototype, evaluate and ship production systems—using techniques like knowledge distillation, prompt engineering, reinforcement learning, image/video processing and rigorous evaluation/metrics to continuously improve image and video asset qualities. You'll partner closely across product, research, and service engineering to deliver the innovative and robust solutions for enterprise customers.
\nAccountabilities
\nThe Candidate we're looking for
\nExperience:
\nTechnical skills:
\nPersonal attributes:
\nBenefits
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