Data Scientist, Risk

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role The Data Science team is seeking a Senior Manager who will help support growth in our SIPS businesses by improving SoFi’s ability to execute with data. This is an exciting role for someone to leverage their Analytical, Engineering, and Management skills to lead a team of Data Scientists with high visibility and impact. You will serve as a data leader, balancing urgent requests and delivering high quality projects to key stakeholders, through a clear and repeatable data informed approach. You will create a culture of strong technical ownership, deliver impact with prioritization, support the growth of individual contributors, and hold the team accountable with high standards. You are expected to work cross-functionally, including: engineering, product managers, lifecycle marketing, data science, design, operations, finance, risk, legal, compliance, and executive teams to set business objectives, define product strategy, prioritize features, and execute on them. What you’ll do: Manage a team of Data Scientists supporting SoFi’s Checking and Savings, Invest, Credit Card, Protect, and Lantern businesses Collaborate with senior leaders and other stakeholders to identify and prioritize Data Science initiatives Set high standards for quality and on-time delivery. Recruit, grow, and reta

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. Lyft is looking for an Engineering Manager from across multiple disciplines. We are growing our team with people who want to build, improve, and incorporate technologies that make the lives of our community more enriched. As an Engineering Manager at Lyft, you'll collaborate with other teams and orgs, product managers, designers, data scientists, analysts, and operations on technology that empowers us to iterate quickly, while focusing on delighting our passengers and drivers. The Rider organization is focused on building a seamless, best-in-class rideshare experience for riders. From the foundational functionality of requesting a ride to the tailored interactions with specific verticals like your flight, we sweat the small stuff to help make Lyft the best transportation solution. As an Engineering Manager on the Rider vertical team, you will act as a critical technical leader, taking holistic ownership of supporting current projects and delivering new products from 0 to 1. This includes developing complex systems, defining strategic roadmaps, driving cross-functional alignment, and ensuring engineering excellence to improve the rideshare experience. Responsibilities: Drive team execution, proactively resolve bottlenecks and make decisive trade-offs. Partner with cross-functional teams (Product, Design, Marketing, Science, and Analytics) to define the team's strategic direction. Translate high-level business goals into actionable projects. Own a team roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Maintain operational excellence through contributing to best practices for observability, reliability, and on-call processes. Ensure technical excellence through architecture reviews, tech debt management, and engineering guidance. Maintain team health