ML Applied Research Manager

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge , we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability. Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data. Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently. Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets. Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions. Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts. Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments. Partner closely with engineering managers, product leaders, and researchers to scope high-impac

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Global Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. We're looking for a Senior Machine Learning Engineer to join our London office as part of a Global DoorDash Engineering team (working hybrid, 3 days in the office). This role sits in our Consumer Org, where you'll work on recommendation problems with direct, measurable impact on how customers discover relevant content. You’ll collaborate with experienced scientists and engineers across DoorDash, Deliveroo and Wolt, learning from multiple recommendation systems while helping shape the next generation of the experience. What You'll Be Doing Design, develop and improve recommendation, ranking and retrieval models that surface relevant restaurants, dishes, items and content to customers. Own applied ML problems end to end: frame the problem, analyze data, develop models, define offline evaluation, run experiments and monitor production performance. Develop methods that balance relevance with product and customer needs, such as diversity, availability, business constraints and changing user intent. Collaborate closely with Software Engineers, ML Engineers, Product Managers and Analysts to turn scientific insights into reliable customer-facing products. Evaluate and apply state-of-the-art ML methods where they meaningfully improve recommendation quality, robustness or efficiency. Contribute to a high bar for applied-science practice through technical reviews, k

About Outreach Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World leading enterprise organizations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon to name a few. About the Team The Dialog Understanding and Generation team is building the industry's most advanced agentic AI capabilities for revenue orchestration, the end-to-end coordination and execution of sales and customer engagement workflows. Our mission is to transform raw customer interactions and CRM data into structured intelligence that powers the entire revenue lifecycle. We operate at the intersection of machine learning, LLM-powered systems, and cloud-scale engineering, driving both current and next-generation AI initiatives at Outreach. We are a team of applied data scientists who thrive on solving complex scientific and engineering challenges. The work is roughly an even split between applied ML research and production engineering, so you should be excited about both. You'll collaborate closely with exceptional engineers and product managers in a fast-moving, high-impact environment, applying your creativity and expertise to build innovative solutions that push the boundaries of agentic AI. Your Daily Adventures Will Include: <li aria-setsize="-1" data-leveltext="" data-font="Symbol" data-listid="5" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We're looking for a highly technical Senior Engineering Manager with a deep understanding of modern recommendation systems to manage, lead and develop a team of ML researchers and engineers within the Applied Science team. In this role, you will lead the strategy of the Recommendation System innovation team. You will help the team build a balanced portfolio of work that addresses both immediate short-term business impact and long-term strategic breakthroughs in areas like Generative Recommendation System (GenRecSys), Large Sequential Models, and Reinforcement Learning (RL). Partnering closely with executive leadership, product management, and engineering partners, you will evolve our technical roadmap and directly drive Pinterest’s core mission forward. What you will do: Technical Vision and Execution: Own the tech

About us Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor and Clay Bavor . Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. Sierra’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems. What you’ll do Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers. Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value. Turn ambiguous product and customer pro

We are seeking a mission-driven Developer Relations Manager focused on Foundational AI Research to engage leading academic labs advancing the next generation of AI models, systems, and methods. In this role, you will work directly with top researchers building frontier AI systems, including large language models, multimodal models, reasoning systems, training methods, inference systems, model serving, and scalable AI infrastructure. You will help researchers adopt NVIDIA’s AI and accelerated computing platforms to push the boundaries of model performance, efficiency, and scale. The ideal candidate brings deep technical credibility in foundational AI, strong research engagement experience, and hands-on expertise in either AI inference research or AI training research. What you'll be doing: Serve as a trusted technical advisor to leading academic AI labs working on foundation models, LLMs, multimodal AI, reasoning, training, inference, and AI systems. Identify high-impact research workloads where NVIDIA software, systems, and accelerated computing platforms can advance model performance, scale, and efficiency. Engage principal investigators, postdocs, graduate researchers, and lab leadership to understand research goals, technical blockers, infrastructure needs, and collaboration opportunities. Track frontier AI research across papers, benchmarks, open-source projects, and academic labs to identify emerging trends and future platform opportunities. Partner with Research Account Managers, Solution Architects, Product, Engineering, and Business Development teams to support researcher adoption and long-term engagement. Represent researcher needs internally by translating academic feedback into actionable insights for product roadmaps, developer programs, education, and platform strategy. Support NVIDIA participation in major AI, ML, and systems research venues through technical content,