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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, inc

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are seeking experienced professionals with a strong background in Artificial Intelligence, Machine Learning, and Cloud Architecture to join our Services Delivery team to help create exciting new offerings and capabilities for our customers! In this strategic role, you will help customers expand their use of the Snowflake Data Cloud to bring AI/ML pipelines from ideation to full production. Leveraging Snowflake’s native features and extensive partner ecosystem, you will advise clients on best practices for scaling production-ready workloads. You will design tailored AI/ML solutions, coordinate closely with customer teams and Systems Integrators, and provide the technical leadership and oversight needed to ensure successful outcomes. AS A PRINCIPAL SOLUTIONS ARCHITECT AT SNOWFLAKE, YOU WILL: Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes technology stack. Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery. Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements. Work hands-on where neede

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. LEAD. STRATEGIZE. TRANSFORM. We are seeking an advanced professional handling complex enterprise AI/ML deployments, deconstructing system dependencies, and ensuring production robustness. WHY THIS ROLE? This role marks a shift from managing tactical tasks to managing strategic outcomes. You are a seasoned professional with a full understanding of your specialization, resolving a wide range of issues in creative ways. WHAT YOU'LL DO: Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem. Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions. Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI. Mentor Level 3 architects on best practices for MLOps and architectural design. TECHNICAL DEPTH & RISK MANAGEMENT: Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/GCP). Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle. Governance: Architect data security and access controls specifically for sensitive AI/ML training data. SNOWFLAKE-NATIVE TECH STACK: Snowflake Model Registry, Cortex Functions, Python,

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Manager, Applied Field Engineering - AI/ML Product Specialists to lead a high-performing team of Applied Field Engineers within the Applied Field Engineering organization. In this hands-on leadership role, you will manage a team of Applied Field Engineers who specialize in Generative AI, Machine Learning, and Advanced Analytics. You will be responsible for coaching your team through technical sales engagements, driving execution excellence, and ensuring customers successfully activate and consume Snowflake's AI/ML capabilities. You will translate team-level insights into feedback that shapes broader strategy, working closely with your manager and cross-functional partners to align execution with organizational priorities. Responsibilities & Focus Areas: Technical Execution & Consumption Activation: Drive team performance toward Consumption Activation — ensuring customers successfully move workloads into production and realize contracted credit value Coa

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for engineers with deep AI/ML and low-level systems experience who want to build the best technical support experience in the world. This isn't a traditional support role — it's an engineering role where you happen to be closest to our customers. You'll split your time roughly 50/50 between working directly with customers and shipping fixes, features, and automation that improve Modal for everyone. When you help a customer debug a training run, you'll also fix the underlying issue in the platform. When you notice ten customers hitting the same friction point, you'll build the tooling or automation that eliminates it entirely. This role is for people who solve problems, not people who answer tickets. The problems you encounter are deeply technical and arise from running some of the most demanding AI workloads in the world. You'll be a member of our eng

Datadog is looking for a resourceful and creative Associate Field Marketing Manager to lead event strategy and execution for Datadog's AI product line across the East and Canada region. This role is ideal for someone who is passionate about AI and developer communities, enjoys getting hands-on with technical audiences, and wants to build a market-leading brand presence for Datadog's AI offerings. As part of the NAMER Field Marketing team, you will own the strategy, planning, and execution of a mix of practitioner-focused events, hands-on workshops, and surround activations at major AI conferences. This role is critical to scaling awareness and adoption of Datadog's AI products, and to building durable relationships with AI customers, prospects, and the broader developer community. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Own the strategy, planning, and end-to-end execution of AI practitioner events, hands-on workshops, and meetups across the East and Canada Lead surround and off-site activations at major AI conferences (e.g., NVIDIA GTC, Ray Summit, AI Engineer Summit, and similar industry events) to build brand visibility and drive engagement with target audiences Partner with Product Marketing and AI/ML product teams to translate Datadog's AI observability and LLM monitoring capabilities into compelling, technically credible event content Design and continuously improve hands-on workshop curriculum and live demos that showcase Datadog's AI products to practitioners and technical decision-makers Build scalable, repeatable event playbooks and toolkits so programs can be run consistently across multiple markets Manage vendors, venues, budgets, staffing, and on-site logistics, ensuring every event reflects Datadog's brand and delivers a seamles

Use Your Power for Purpose Global Commercial Analytics (GCA) harnesses the power of data to drive robust analytical insights that inform some of Pfizer's most critical business questions. With colleagues across the globe, GCA's rigorous analytical expertise is depended on as the compass and decision support for the enterprise. Our dynamic, exciting team of subject-matter experts comes from diverse backgrounds and experiences, including data science, market research, digital analytics, finance, and consulting. As a team, we partner to turn data into meaningful insights that will have a direct impact on patients' lives and the future of Pfizer as a data-driven organization. The Data Science Manager is accountable for delivering data science support across the commercial business. As a strategic partner to US Commercial teams, this person will develop and implement models and data science-derived insights that influence brands’ strategic priorities. These responsibilities will include driving the execution and interpretation AI/ML models, framing problems, and shaping solutions. This role is dynamic, fast-paced, highly collaborative, and covers a broad range of strategic topics that are critical to our business. The successful candidate will join GCA colleagues worldwide that are constantly supporting business transformation through their proactive thought leadership, innovative analytical capabilities, and their ability to communicate highly complex and dynamic information in new and creative ways. What You Will Achieve Commercial Data Science and Insights Provide data science and insights to US Commercial teams to drive brand tactic decisions Assist to frame, investigate, and translate complex data-informed models, and answer key business questions related to the identification and evaluation of brand strategies a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The FinOps function is responsible for financial accountability, visibility, and optimization across all engineering-related spend at Plaid. This includes cloud infrastructure, AI/ML and data workloads, third-party SaaS tools, and other technical investments that support Plaid’s products and internal platforms. The team operates at the intersection of Engineering, Product, and Finance, ensuring that spending decisions are transparent, intentional, and aligned with product strategy and business priorities. Rather than functioning as a cost-control or approval layer, FinOps enables teams to understand, own, and optimize their spend while maintaining engineering velocity. Responsibilities Monitors and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS, identifying trends, anomalies, and optimization opportunities. Builds and maintains forecasts for engineering spend, partnering with Finance and engineering leaders to understand drivers, assumptions, and risks. Partners with engineering, product, and TPMs to incorporate cost considerations into roadmaps, architectural decisions, and execution plans. Leads cost optimization initiatives, such as rightsizing, commitment strategies, an

We’re looking for a Senior Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Serve as the technical owner for GenAI initiatives within APM, leading design, development, and deployment of ML/AI-powered features across multiple teams. Guide long-term strategy and technical direction for GenAI workflows across APM and related products. Build and benchmark GenAI/ML models using state-of-the-art techniques. Contribute to Datadog’s broader senior engineering community through thought leadership and collaboration on company-wide initiatives. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, sc

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Our Mission You call. You wait. You call again. In every other part of your life, you book in seconds. In healthcare, you’re blocked. We’re here to give power to the patient. For nearly 20 years, we’ve built the leading healthcare marketplace - helping tens of millions of people find and book the care they need. Now, we’re going further: building our infrastructure beyond Zocdoc’s marketplace to power access to care wherever patients search, from provider websites and insurance directories to search engines, AI platforms, and more. Healthcare still lacks something every other major consumer industry takes for granted: a seamless way to go from seeking to getting . We don’t want to own the front door to care; there isn't one. We want to make sure all of those doors open when patients are knocking. Fixing healthcare starts with fixing access to it. And we're still just getting started. About the Role We're transforming how healthcare practices interact with Zocdoc, building intelligent systems that understand each practice's needs and guide them toward actions that grow their business. This means personalized homepages, smart recommendations, AI-assisted configuration, and workflows that make Zocdoc essential to daily operations. As Senior Software Engineer, you'll build these systems end-to-end. You'll own features from design through production, work across the stack, and collaborate with Product, Design, and Data Science to ship experiences that matter. What You'll Do Build platform components - including practice profile services, engagement scoring pipelines, recommendation APIs, personalization infrastructure. Ship product features end-to-end - database to API to front-end, owning the full lifecycle. Work with Data Science to integrate ML models build feature pipelines, call model endpoints, instrument feedback loops. Write production-ready code with strong testing, observability, and error handling. Participate in design discussio

We’re looking for a Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Act as a technical leader within the APM organization, driving GenAI/machine learning projects from concept to production. Build and benchmark GenAI/ML models using state-of-the-art techniques. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, scaling challenges, and evolving requirements with clear technical direction. Actively mentor engineers and influence engineering culture through leadership in design reviews, technical talks, and working groups. Who You Are: You have a BS/MS/PhD in a scientific field or equiva