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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 . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Software Engineer, ML Platform, you will work on our ML Data Team and be instrumental in architecting, implementing, and maintaining foundational ML infrastructure powering Feeds Ranking, Content Understanding, Recommendations, Ads, and much more to fulfill Reddit’s mission of bringing community and belonging to everyone in the world. You will create ML data-governance tools that help MLEs discover and reason about signals, while contributing across the broader ML data platform—including prediction logging and training data systems. Lead the design, development, testing, and operation of ML signal-governance capabilities that help MLEs discover signals and understand their ownership, lineage, quality, and usage. Build tools that help teams assess signal importance and make informed lifecycle decisions. Partner with MLEs and cross-functional teams to define governance workflows and deliver reliable, intuitive ways to explore and act on signal metadata. Contribute across the ML Data Platform, including prediction logging and training data platforms, to design, develop, test, and operate batch and streaming pipelines processing petabyte-scale data. Drive complex projects end to end from technical planning an

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana We're looking for a Senior Staff Machine Learning Engineer to lead the AI behind Altana Nexus, our agentic platform for global trade. You'll work on a continuous stream of public and proprietary trade data (shipments, customs filings, trade documents), and build the models and AI agents that turn it into real-time decisions on risk, compliance and enforcement for governments and the world's largest companies. Your Responsibilities Drive the technical direction for agentic systems. Define the architecture and roadmap for the models and agentic systems that process trade data as it arrives (shipments, customs declarations, invoices, bills of lading) and turn it into risk, classification and compliance decisions in real time. Build the pipeline from ingestion to decision. Lead the design of reliable, cost-efficient systems for ingestion, document understanding, entity resolution, inference and routing across models, at the scale of global trade. Adapt models to trade. Use analyst feedback, production outcomes and agent traces to fine-tune and post-train models (SFT, DPO, RL with domain graders) where it measurably beats prompting, and keep every model improving over time. Design the observability and feedback stack. Build the evals, tracing and feedback loops that decide what ships and catch regressions in production. Lead beyond your team. Mentor senior engineers, raise the technical bar across Engineering, and help shape how we hire and level ML talent. Shape the product and the business. Work with software engineers, data scientists, product managers and customers to generate new business ideas and turn ambiguous problems into shipped capabilities. About You BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experi

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana We're looking for a Senior Staff Machine Learning Engineer to lead the AI behind Altana Nexus, our agentic platform for global trade. You'll work on a continuous stream of public and proprietary trade data (shipments, customs filings, trade documents), and build the models and AI agents that turn it into real-time decisions on risk, compliance and enforcement for governments and the world's largest companies. Your Responsibilities Drive the technical direction for agentic systems. Define the architecture and roadmap for the models and agentic systems that process trade data as it arrives (shipments, customs declarations, invoices, bills of lading) and turn it into risk, classification and compliance decisions in real time. Build the pipeline from ingestion to decision. Lead the design of reliable, cost-efficient systems for ingestion, document understanding, entity resolution, inference and routing across models, at the scale of global trade. Adapt models to trade. Use analyst feedback, production outcomes and agent traces to fine-tune and post-train models (SFT, DPO, RL with domain graders) where it measurably beats prompting, and keep every model improving over time. Design the observability and feedback stack. Build the evals, tracing and feedback loops that decide what ships and catch regressions in production. Lead beyond your team. Mentor senior engineers, raise the technical bar across Engineering, and help shape how we hire and level ML talent. Shape the product and the business. Work with software engineers, data scientists, product managers and customers to generate new business ideas and turn ambiguous problems into shipped capabilities. About You BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experience 8+

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 . About Pinterest Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. As a Pinterest employee, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping users make their lives better in the positive corner of the internet. Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more. Staff Machine Learning Engineer, Applied Science As part of Pinterest Labs , you'll work on tackling new challe

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role Hiring is one of the most consequential decisions a company makes. 3,000+ enterprises rely on HackerRank to get it right. We are now reinventing how that works for the agentic era. The AI/ML systems that power this platform are not auxiliary features. They are the product. Open Problems The agentic era is reshaping every layer of the hiring stack. These are some of the core problems you'll be working across, none of them fully solved. Chakra: Building an autonomous AI interviewer that conducts, adapts to, and evaluates technical interviews end to end. Integrity: Detecting fraud and suspicious behavior across multiple signal types. The ways candidates game assessments change frequently, and the models need to keep up. Evaluation: Measuring technical skill in a world where AI writes the code. The old proxies no longer hold and the new ones have not been defined yet. Your focus will shift across these depending on where the highest-leverage work is at any given time. What you will do Research, Design, and Develop advanced Deep Learning models and novel Neural architectures. Explore architectures beyond Transformers, including State Space Models (SSMs), Liquid Neural Networks (LNNs), and Hybrid approache

About the Team Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products. We work closely with research teams to develop useful measurements and make them practical to run. Our work spans classifier development, rigorous evaluation, and efficient production inference, with ownership from initial experimentation through deployment and continued improvement. About the Role We’re looking for a machine learning engineer to develop new classification and evaluation capabilities and bring them into production. You’ll help turn open-ended questions about model behavior into well-defined ML problems, build methods that address them, and establish how reliably those methods work. This role combines traditional machine learning, model evaluation, and real-time engineering. You’ll own classifiers throughout their lifecycle, including supervised fine-tuning, distillation, evaluation, deployment, and production inference. You’ll work closely with researchers to identify valuable problems and with software engineers to make promising approaches useful at scale. In this role, you will: Build, deploy, and operate production classification and evaluation systems that provide useful feedback to post-training and research teams. Optimize production inference, including model serving, batching, caching, throughput, latency, compute utilization, and cost. Train and optimize classifiers using supervised fine-tuning and distillation, validating quality and efficiency before deployment. Own the reliability and observability of deployed classifiers, diagnose production issues, and improve their performance over time. Design rigorous evaluations that assess accuracy, calibration, generalization, and potential measurement bi

About the team The Growth team drives user and revenue growth across ChatGPT’s consumer and business segments and other OpenAI products worldwide. We work across the full funnel—from awareness and acquisition through activation, retention, and expansion—using experimentation, data science, machine learning, and product engineering to help more people discover and realize durable value from OpenAI’s products. Our team partners closely with Product, Engineering, Data Science, Design, Finance, Lifecycle, and Growth Marketing. We move quickly, test rigorously, and hold a high bar for measurement, privacy, reliability, and user trust. About this role: We are looking for a Machine Learning Engineer to build the models and decision systems that optimize paid marketing investment for ChatGPT and other OpenAI products. You will develop budget allocation and control algorithms that determine where to invest, how quickly to spend, and how to adjust as performance changes. The challenge is to make reliable decisions from noisy, delayed, and incomplete signals. You will combine machine learning, optimization, and experimentation to improve incremental growth and long-term user value within budget and efficiency constraints. You will own this work from problem formulation and prototyping through deployment, evaluation, and ongoing operation. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to eligible employees. In this role, you will: Build budget allocation algorithms. Decide how to distribute investment across channels, campaigns, and markets using estimates of marginal returns, while accounting for diminishing returns, uncertainty, and business constraints. Develop spend pacing and adaptive control systems. Adjust budgets and spending rates as performance changes, balancing responsiveness with stability when feedback is delayed or noisy. Build in spend limits, monitoring, and safe fallback

Job Requisition ID # 26WD101494 Machine Learning Operations Developer, Inference, AI/ML Platform L'affichage de poste en français suivra / The French job posting follows Position Overview Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking an MLOps Developer to join our AI/ML Platform team. This role will contribute to ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML platform used in the development of machine learning and generative AI solutions powering Autodesk’s suite of products and services. You will collaborate with research and product engineering teams from various domains including design, construction, manufacturing, and media & entertainment to support platform operations. The role is hybrid Toronto or Montreal. Responsibilities Contribute to the operational excellence of our AI/ML Platform by implementing and optimizing MLOps practices Develop and maintain automated deployment pipelines for machine learning models, supporting seamless transitions from development to production Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processing <li style="color:#1d

The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI. We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras. This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction. By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of humans. In this role, you will: Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines. Collaborate with Synthetic Data and HIL Sim teams to integrate 3DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities. Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation. Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy. <li style="font-size: 11pt; font-family: Ar

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. ML Platform powers hundreds of use cases and billions of inferences per day across Discovery, Safety, Economy, and Creation. We build the primitives that let teams train, evaluate, deploy, and operate models quickly and safely—so a new ML idea can reach production in weeks or less. We’re looking for a Principal Platform Engineer who treats platform as a product : someone who can turn complex ML/AI infrastructure into clear, durable APIs, SDKs and easy-to-use CLIs/UIs that our internal developers love. This role blends product thinking, developer experience, backend engineering, and infrastructure at scale. Hands‑on ML experience is a plus; a track record of building internal platforms that developers love is a must. You Are Have 10+ years of professional experience and have a wealth of system design experience upon which to draw to build a scalable, reliable ML platform for all of Roblox. A Code Machine; you love not only to design and communicate ideas but also to actually ship product. You obsess about user feedback, and constantly drive towards getting platform features in customers hands. Proficient in API design and developer experience—gRPC/REST APIs, SDKs, CLIs, and simple UIs that d

NVIDIA is seeking outstanding Research Interns to join the Data-Driven AI for Robotics (DAIR) group. The focus is on learning embodied skills from large-scale human data. Our objective is to develop AI systems that capture, understand, and reproduce complex human motion and interaction skills across physical and digital embodiments, including humanoid robots and animated characters. Our research spans the full stack: reconstructing human motion and human-object interactions from video; generating diverse, controllable character behaviors; transferring motion across embodiments; and training physically grounded controllers for humanoid robots and interactive virtual characters. You will collaborate with a passionate and supportive research team that consistently produces influential work published at leading computer vision, machine learning, graphics, and robotics conferences. You will also have the opportunity to collaborate with world-class research and product teams across NVIDIA, following our strong “one-team” culture. What you'll be doing: Innovate and implement novel AI algorithms that transform large-scale human data into controllable motion and interaction skills across physical and digital embodiments. Develop robust, scalable training and inference pipelines for motion reconstruction, generation, retargeting, and character and robot control. Build methods that transfer human skills to humanoid robots, including whole-body loco-manipulation and dexterous manipulation. Maintain a close, collaborative relationship with your mentor(s). Publish your research findings at leading computer vision, machine learning, graphics, and robotics conferences. Partner with product teams to enable effective technology transfer of your work. Research Topics Include: Human motion and human-object interaction reconstruction, synthesis, and generatio

About the opportunity We are seeking an experienced Lead Technical Product Manager for our Machine Learning Platform within the Intelligent Operations Platforms segment. In this role, you will define the long term vision, platform architecture, and execution strategy for core Machine Learning infrastructure across N26. Your work will enable squads across the bank to automate risk assessments, prevent financial crime, and scale operational efficiency. Our ML Platforms team serves as the central nervous system for real-time, data-driven decisioning. We build and scale horizontal ML capabilities that allow critical functions including Financial Crime, Credit Risk, and Core Operations to execute with absolute precision at scale. As a Lead Product Manager, you will drive multi-squad strategy, transforming complex predictive models into resilient, compliant, sub-second scoring systems. In this role, you will Drive the Core ML Platform Vision: Define and execute the multi-year roadmap for the central Machine Learning platform, ensuring alignment with broader engineering architecture and executive business goals. Lead High-Volume ML Portfolios: Oversee complex predictive ML capabilities supporting high-throughput banking systems, focusing on real-time transaction monitoring, automated credit risk scoring, and operational workflow decisioning. Scale Enterprise MLOps Infrastructure: Own the platform tooling and standards across the full ML lifecycle. Drive strategic decisions around feature stores, real-time feature extraction pipelines, model registries, automated retraining triggers, and CI/CD for ML. Establish Model Evaluation and Governance: Define robust offline and online model evaluation frameworks, shadow deployment mechanics such as champion and challenger testing, and real-time monitoring for model drift, inference latency, and data quality degradation. Bridge Technical Leadership and Compliance: Partner closely with Principal Data Scientists, ML Engineers, Security

About the opportunity We are seeking an experienced Lead Technical Product Manager for our Machine Learning Platform within the Intelligent Operations Platforms segment. In this role, you will define the long term vision, platform architecture, and execution strategy for core Machine Learning infrastructure across N26. Your work will enable squads across the bank to automate risk assessments, prevent financial crime, and scale operational efficiency. Our ML Platforms team serves as the central nervous system for real-time, data-driven decisioning. We build and scale horizontal ML capabilities that allow critical functions including Financial Crime, Credit Risk, and Core Operations to execute with absolute precision at scale. As a Lead Product Manager, you will drive multi-squad strategy, transforming complex predictive models into resilient, compliant, sub-second scoring systems. In this role, you will Drive the Core ML Platform Vision: Define and execute the multi-year roadmap for the central Machine Learning platform, ensuring alignment with broader engineering architecture and executive business goals. Lead High-Volume ML Portfolios: Oversee complex predictive ML capabilities supporting high-throughput banking systems, focusing on real-time transaction monitoring, automated credit risk scoring, and operational workflow decisioning. Scale Enterprise MLOps Infrastructure: Own the platform tooling and standards across the full ML lifecycle. Drive strategic decisions around feature stores, real-time feature extraction pipelines, model registries, automated retraining triggers, and CI/CD for ML. Establish Model Evaluation and Governance: Define robust offline and online model evaluation frameworks, shadow deployment mechanics such as champion and challenger testing, and real-time monitoring for model drift, inference latency, and data quality degradation. Bridge Technical Leadership and Compliance: Partner closely with Principal Data Scientists, ML Engineers, Security

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Staff Machine Learning Engineer, CX Intelligence CEE Intelligence (CEEI) is the ML and intelligence layer for Coinbase's customer engagement ecosystem, building customer intelligence, evaluation systems, routing and classification models, safety guardrails, and decisioning capabilities that power Help Center, chat, voice, agent tooling, and other customer support runtimes. As a Staff Machine Learning Engineer, you'll lead the design and delivery of production ML systems across the org, shaping technical strategy, building scalable intelligence capabilities, and partnering with product and engineering stakeholders to improve resolution quality, automation coverage, safety, and customer experience. What you'll do: Own the design and delivery of production ML systems, applying LLMs, deep learning, graph neural networks, and classical ML techniques to solve complex customer experience problems. Partner with leadership and cross-functional stakeholders to define strategic roadmaps and translate vision into quarterly execution plans with measurable outcomes. Lead high-impact ML projects end-to-end, from architecture through production, managing priorities, risks, and dependencies. Build scalable, secure, and reliable ML systems, evaluation pipelines, and data workflows using high-quality, well-tested Python code. Mentor engineers and establish team-wide standards fo

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Digital Solutions Manager (Recruiting Tech & Learning Platforms) This role sits within People Experience & AI transformation and serves as the strategic technical and functional capability lead for Okta's Recruiting and Learning ecosystem. As a Digital Solutions Manager with deep expertise in enterprise systems, integrations, automation, data architecture, and AI, you will define and execute the technology vision that enables scalable hiring, workforce development, and organizational growth. In this role, you will establish the long-term technical and technical strategy for recruiting and learning systems, ensuring our platforms, integrations, data architecture, and AI capabilities work together seamlessly to support global operations. You will translate business priorities into scalable technical solutions, balancing user experience, operational efficiency, governance, and future-state innovation. You will operate at the intersection of systems architecture, automation, and user experience—building solutions that improve efficiency, enable better decision-making, and support global growth. This role also requires strong AI fluency, with a focus on leveraging AI-driven capabilities to enhance recruiting processes, learning experiences, and operational automation. What You'll Own Roadmap & Systems : Define & execute the roadmap for Recruiting and Learning systems, ensuring alignment with business goals. Serve as the primar