Ml Platform Engineer Jobs

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 Senior Manager, Applied Field Engineering — AI/ML Product Specialists to lead a high-performing team of AI/ML specialists at the intersection of product, field, and customer success. In this hands-on leadership role, you will manage a team of Applied Field Engineers who are deep practitioners in Snowflake's AI/ML product portfolio — including Cortex AI, ML modeling, and agentic workflows. You will drive product adoption and customer outcomes, ensuring customers move beyond initial activation to unlock the full depth of Snowflake's AI/ML capabilities. Critically, you will serve as a strategic bridge between the field and Snowflake's product organization — translating customer experience into structured product insight that directly shapes roadmap priorities. You will work closely with Product Management, Engineering, and Sales leadership to ensure Snowflake builds the right things and customers realize their full potential. Responsibilities & Focus Areas Pro

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

Staff Product Engineer (GenAI, AI/ML & Advanced Data Analytics) — Fab 10A, Singapore. Apply via Workday.

Datadog’s Product Analytics suite spans Product Analytics, Session Replay, Feature Flags, and Experimentation. Together they give product teams a complete, quantitative and qualitative picture of how users experience their applications, plus the tools to release, measure, and improve those experiences with confidence. Our team of Applied Scientists makes this space smarter and more autonomous, researching, prototyping, and industrializing AI/ML capabilities that make the suite proactive and agentic by default: AI-driven event understanding and instrumentation, conversational analytics, automated insight reporting, and UI/UX issue detection from session replays. The ambition is to let product teams act with autonomy, moving from question to insight to safely released change without depending on engineering or analysts. As the Engineering Manager for this team, you’ll lead a team of Applied Scientists through an early-stage, high-impact opportunity: defining the team’s technical vision, growing its footprint, and shaping how AI capabilities get built and delivered across the suite. This is greenfield work, both in the R&D itself and in the team you’ll grow around it. 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: Lead and grow a team of Applied Scientists researching, prototyping, and industrializing AI/ML capabilities across the suite Define the technical vision and roadmap for the suite’s agentic and proactive AI/ML capabilities: event understanding, conversational analytics, insight reporting, and session-replay issue detection Stay hands-on as a technical contributor and reviewer, helping the team move from research prototypes to production-grade capabilities Shape how AI capabilities get built and delivered across the suite, partnering closely wi

Manager, IT Data, ML & AI Engineering — United States - North Carolina - Raleigh. Apply via Workday.

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 looking for people who have a strong background in data science and cloud architecture to join our AI/ML Workload Services team to create exciting new offerings and capabilities for our customers! This team within the Services Delivery group will be working with customers using Snowflake to expand their use of the Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be highly technical and hands-on, where you will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators. AS A SR. TECHNICAL ARCHITECT, AI/ML AT SNOWFLAKE, YOU WILL: Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements Work hands-on where needed using SQL, Python, and APIs to build POCs that demonstrate implementation techniques and best practices on Snowflake technology for GenAI and ML workloads Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own Maintain deep unders

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. Principal Data Cloud Architect - SI Partners We are seeking a highly experienced and results-driven AI/ML focused Principal Data Cloud Architect to join our Partner Solution Engineering (PSE) team. Our mission is to empower System Integrator (SI) partners to rapidly achieve technical wins and successful production deployments of AI/ML solutions on the Snowflake AI Data Cloud. Snowflake, the AI Data Cloud, enables teams to seamlessly run analytical workflows, develop agentic apps, and train models using both structured and unstructured data. With over 4,000 customers leveraging our gen AI and ML technology weekly, we are at the forefront of AI innovation. This role is crucial in accelerating AI/ML customer journey technical wins and production deployments being implemented by SI partners. IN THIS ROLE YOU WILL PERFORM: Strategic Account Alignment with top accounts for SI partners (Focus on Acceleration): Unlock High-Impact Customer Journeys: Identify and prioritize AI/ML customer journeys for SI partner top accounts, focusing on quick wins and high consumption, informed by your understanding of SI partner needs. Expedited POCs and RFPs: Provide support for partners during RFI/RFP processes and POCs, ensuring rapid turnaround and successful outcomes, informed by your SI propo

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

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role AI and machine learning are reshaping how developers debug, monitor, and ship software, and Sentry is uniquely positioned to lead that shift. We sit on a novel and massive dataset of real production errors, spans, and logs from tens of thousands of engineering organizations — the kind of signal that makes ML genuinely useful, whether it's a clustering model that groups related issues, a ranking system that surfaces the right alert at the right time, or an agent that proposes a fix. We're looking for an Engineering Manager to lead and grow our Machine Learning Engineering team. This team owns the full spectrum of ML at Sentry: classical techniques like clustering, ranking, anomaly detection, and embeddings that quietly power core product surfaces today, alongside the LLM-based and agentic systems shaping where the product is headed. You'll partner closely with product, design, and engineering leaders to decide where ML belongs in our products, what kind of ML actually fits the problem, and how we translate that work into experiences millions of developers rely on every day. In this role you will Set technical direction across the team's full ML surface area — from classical models for clustering, ranking, and anomaly detection to LLM-based and agentic systems — and make sharp calls about which approach fits each problem Define how the team evaluates and monitors ML systems in production, from offline metrics to online experimentation to model and agent observability Stay hands-on enough to review code and model designs, contribute to architecture discussions, and unblock engineers on complex ML problems Define

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

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence Identify areas

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory da

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence Identify areas

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory da

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, e