Applied Cryptography Pki Jobs

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 . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

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 . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

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 . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

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 . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re seeking a GPU Kernel Engineer to join our team at the cutting edge of AI acceleration, where your code directly impacts the performance of state-of-the-art machine learning models. As a GPU Kernel Engineer, you'll craft the foundation that powers modern AI workloads, optimizing every microsecond of computation to enable breakthrough applications. You'll work in a fast-paced, intellectually stimulating environment where technical excellence is paramount and your contributions directly influence production systems serving millions of users across numerous products. This role offers exceptional growth potential for engineers passionate about low-level optimization and high-impact systems work. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: Baseten Embeddings Inference: The fastest embeddings solution available The Baseten Inference Stack Driving model performance optimization RESPONSIBILITIES Core Engineering Responsibilities Design and implement high-performance GPU kernels for key ML operations, including matrix multiplications, attention mechanisms, and mixture-of-experts routing Write and optimize code using CUDA, PTX assembly, and architecture-specific techniques Apply advanced performance optimization methods such as memory coalescing, warp-level programming, tensor core acceleration, and compute/memory overlap Performance & Innovation Implem

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. We’re looking for experienced engineers who have shipped applied AI systems to production and want to define what the agent-native future looks like. We are building intelligence into the core of Linear, enabling the product to orchestrate coding, proactively move work forward, and power-up every software team. You’ll work closely with product and design to transform foundation models into structured, reliable workflows embedded deeply in the core of Linear. We care deeply about keeping Linear fast, intuitive, and opinionated—AI is no exception. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in the North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Build AI-powered product features that feel native, fast, and delightful to use Work with product and design to prototype and iterate on intelligent workflows and user interactions Design backend services to power natural language interfaces, smart suggestions, agentic workloads, and more Optimize prompts, fine-tune model behavior, and evaluate performance Help to guide our agent platform, allowing third parties to bring agents into the core Linear experience

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma is seeking a versatile and experienced Machine Learning / AI Engineer to join our growing AI team, working at the intersection of applied machine learning, infrastructure, and product innovation. Whether you’re building intelligent search systems, crafting scalable data pipelines, or enhancing AI-powered creativity tools, your work will drive user productivity, shape new product experiences, and advance the state of AI at Figma. You’ll collaborate closely with engineers, researchers, designers, and product managers across multiple teams to deliver high-quality ML-driven features and infrastructure. This is a high-impact, cross-functional role where you’ll shape both foundational systems and user-facing capabilities. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features. Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows. Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance. Work with product engineers to define and deliver impactful AI features across Figma’s platform. Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment. Explo

Role: The Quant Researcher will report to a Stamford based Portfolio Manager and will focus on: Building, running, and maintaining power dispatch model for ERCOT and other major US ISOs Driving the model’s inputs and architecture to efficiently simulate power grid conditions and marginal pricing Continuously testing and improving the model, ensuring it accurately replicates historical conditions and effectively analyzes forward scenarios Communicating the model’s results and limitations to the wider investment team Responsibilities: Formulate and build a power dispatch model using Python and a commercial solver Collaborate with the PM to optimize model inputs and architecture Ensure the model replicates grid operations from historical conditions Suggest model improvements to decrease forecast error and improve scenario handling Regularly run the model and maintain up-to-date outputs in an internal database Communicate results and limitations to the wider investment team, including publishing results to team dashboards Requirements: Master or PhD in operations research, electrical engineering, applied mathematics, or a related quantitative field 5+ years of direct experience building power dispatch models (SCUC/SCED) using optimization solvers (Gurobi, CPLEX, etc.) Knowledge of power plant dispatch, grid operations (including capacity and AS obligations), and LMP pricing in US power markets Experience using SQL and timeseries databases Proficiency in Python and Git; additional experience with an OOP language a strong plus Domain knowledge in ERCOT, PJM, or CAISO preferred About Point72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led cultu

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: We’re seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You’ll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences. RESPONSIBILITIES: Designing and architecting recommendation algorithms across various product surfaces Leverage all of SpaceXSI's infra and AI stacks to dramatically enhance the user experience Write data pipelines and training jobs that continuously learn from product data. Iterate and improve the algorithm by gathering user feedback in real time through experimentation Ensuring scalability and efficiency of machine learning systems BASIC QUALIFICATIONS: Knowledge of data infrastructure like Kafka, Clickhouse, and Spark Experienced in implementing recommender systems and/or deep learning applications at industrial scale Skilled in one or more DL software frameworks such as

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Strategic accounts at Baseten are the largest and fastest-growing AI companies in the world. These are the teams defining the future of what AI products and services look like. These accounts can scale rapidly from one token to billions of tokens in a matter of weeks. This role owns these relationships, working directly with founders and engineering leaders on mission-critical and large-scale-AI problems in production—and shaping what we build next. This is a highly technical sale. You’ll trade opinions on the latest open-source model releases, run fast and nuanced evaluations alongside customer engineering teams, and often pulling in SMEs from applied research to infrastructure engineers to win. You’ll bring tight sales fundamentals and process discipline, while maintaining flexibility and creativity in how you run each cycle. This role is pioneering what sales looks like at the bleeding-edge of technology sales. This is a front row seat to the most consequential decisions made at the forefront of Artificial Intelligence. There is no faster place to learn and make an immediate impact. RESPONSIBILITIES Own a focused portfolio of high-growth, strategic AI-native accounts end to end — from technical evaluation and initial workload landing through expansion as inference usage scales. Lead technical evaluations and complex, multi-stakeholder sales cycles from first conversation through close. Bring strong sales fund

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: You have built and run production services in a high growth, rapidly scaling environment. You can debug live issues and restore systems quickly. You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Py

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Infrastructure team: Multi-cloud capacity management Inference on B200 GPUs Multi-node inference Fractional H100 GPUs for efficient model serving RESPONSIBILITIES Develop infrastructure components for our ML inference platform using Python and Go Implement and maintain Kubernetes deployments for model serving Contribute to our inference orchestration layer for model deployments Build and enhance monitoring systems for model performance metrics Implement efficient resource management solutions for ML workloads Support infrastructure automation to improve ML deployment workflows Work closely with team members to implement technical solutions Help balance performance optimization with system reliability Participate in technical discussions around infrastructure improvements Learn and apply infrastructure best practices REQUIREMENTS Bachelor's degree or higher in Computer Science or related field Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus Working knowledge of Kubernetes and containerizati

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As an Outbound Sales Development Representative at Baseten, you'll drive strategic outbound into a defined set of target accounts - partnering closely with your Account Executive to research key decision-makers and break through via cold calls, email, and LinkedIn. Together, you'll turn cold accounts into qualified pipeline. RESPONSIBILITIES Build revenue pipeline by setting introductory meetings with potential businesses and key decision makers. Help influence Baseten's product roadmap for customers and prospects. Identify high-potential businesses and verticals and develop and execute outbound strategies to bring them to Baseten. Stay up-to-date on market trends, competition, and industry developments. Manage and document the progression of the sales pipeline. Drive pre- & post-engagement at industry events (will attend multiple events in person). REQUIREMENTS 1+ year of experience in a sales/lead generation role in a high-tech/SaaS company. Ability to develop strong, long-lasting relationships both internally and externally. Collaborative and coachable, always looking to improve your skills and impact. Ability to handle rejection and stay persistent in pursuing leads. Excellent verbal and written communication skills. A basic understanding of a standard SaaS seller's technical stack (CRM, Outreach/Salesloft, Prospect Research, etc.). Excellent time management, process, and prioritization skills. Preferred

Why Work with Us Solve impactful problems. At Seven Research, our close-knit team unites brilliant minds passionate about pushing technological and scientific boundaries in the global markets. We provide state-of-the-art resources and cultivate intellectual freedom, enabling our people to develop groundbreaking solutions to the most complex challenges of our field. Our collaborative approach celebrates excellence from everyone, regardless of tenure. Your Role Our Deep Learning Researchers expand the boundaries of quantitative finance through the development of advanced deep learning models. You will conduct rigorous, systematic research to pioneer advanced methodologies, uncover sophisticated insights, and implement innovative approaches within our teams. What We’re Looking For We seek talented and knowledgeable problem-solvers with strong backgrounds in deep learning to come build with us. No financial knowledge is expected. Deep Learning Researcher candidates should have demonstrated strong applied research and critical analysis skills. We value team members who communicate clearly and can exercise ownership over projects. If working on challenging quantitative problems in a close-knit, research-driven environment excites you, we’d love to get to know you. The ideal candidate will possess most of the following: PhD degree in computer science or a related field Mastery of deep learning techniques and proven track record of building sophisticated predictive models using deep learning Publications in relevant journals and/or conference presentations Strong programming skills, including mastery of Python Strong problem-solving skills and research acumen Strong communication skills to articulate complex technical concepts Experience working with large data sets and computationally intensive projects Experience with high-performance computing Job Compensation Range The base salary range for this role is $200,000 - $300,000. This does not include other forms of co

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t