FEQ227R273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #CMEG As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve pr
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FEQ227R273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #CMEG As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve pr
FEQ227R273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #CMEG As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve pr
FEQ227R273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #CMEG As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve pr
Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in! At Duolingo, you’ll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems. You’ll have limitless learning opportunities and daily collaborations with world-class minds — while doing work that’s both meaningful and fun. Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world. Read our blog to learn more. About the role You will... Derive insights from data to influence product roadmaps and drive business results Apply advanced analytical methods, structural approaches, causal inference, and/or machine learning and AI to model user behavior and estimate the impact of potential new feature implementations, and collaborate with product and engineering teams to develop solutions Evaluate product experiments to create and improve user experiences Communicate and present findings and recommendations to senior management Help preserve our culture of fact-based decision making as we scale You have... Pursuing a PhD degree (in at least the third year of PhD program) in a quantitative field (e.g. Economics, Finance, Statistics, Math, Linguistics, Computer Science, Computational Social Science, ML/AI), ideally planning to graduate in Fall 2027 or Spring/Summer 2028 Strong understanding of consumer digital products and an interest in applying advanced analytics and economics to business outcomes Previous experience analyzing large datasets, communicating results to technical and non-technical senior-level audiences, and making actionable recommendations that improve the product or business Skilled in SQL, R or Python, and/or statistical methods to analyze behavioral data Enthusiasm for learning and sharing analytical methods to h
Senior Python / Agentic AI Engineer Capco: Where Innovation Meets Opportunity Capco is a global leader in consulting, uniquely positioned to drive innovation and transformation in the financial services industry. More than consultants, we are strategic partners and problem solvers for some of the largest organizations in Banking, Insurance, Investment Management, Data/Digital Transformation, Regulatory Compliance, and ICT Risk. Our business and technology professionals thrive in a dynamic environment where creativity, collaboration, and cutting-edge solutions are at the heart of everything we do. Experience the Capco difference and explore how you can shape your future with us at capco.com . Capco’s AI Lab The AI Lab is a cross-disciplinary research and engineering centre that translates advanced AI research into robust, deployable solutions for clients and internal products. It runs applied research (ML and agentic/LLM systems, planning, simulation and evaluation), rapid prototyping and production engineering (APIs, CI/CD, observability, data platforms and cost/latency optimisation), and rigorous evaluation and safety work (benchmarks, red-teaming, monitoring, governance and compliance). The lab also supports client engagements and internal innovation by building demonstrators and reference architectures, transferring technology to delivery teams, publishing technical learnings, and maintaining the shared infrastructure, tooling and best practices that enable reproducible, secure and scalable AI deployment. Responsibilities Design and implement scalable, production-grade Python services that leverage LLMs and Agentic architectures. Design and implement robust agent workflows and orchestration patterns to automate complex business processes in regulated enterprise environments. Build and maintain reliable AI-enabled backend systems , including orchestration layers, tool integrations, knowledge a
About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform
About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform
Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . This position is based out of our India Development Center in Hyderabad. Who we are looking for Join Truveta’s Intelligence Platform and Applications (IPA) team to build the next wave of healthcare AI — developing adaptive agentic systems and fine-tuned foundation models that continuously learn, reason, and accelerate real-world impact. Guided by Truveta’s mission of Saving Lives with Data, you’ll help transform how health data becomes intelligence, powering breakthroughs that enable researchers, clinicians and operational managers to make data-driven, proactive, and impactful decisions. We firmly believe that patients, doctors, and medical researchers deserve to benefit from the artificial intelligence revolution that is transforming productivity, creativity, and communication. You’ll help shape the AI capabilities that make healthcare more intelligent, efficient, and equitable — driving real-world impact across research, care delivery, and patient outcomes. If you’re seeking a sense of purpose and are motivated to advance how AI supports learning, decision-making, and discovery in healthcare, you’ll find this an inspiring place to grow. We are seeking AI Engineers who thrive at the intersection of agentic and applied AI, machine learning, and large-scale engineering. You’ll blend ML craftsmanship with platform engineering excellence to create scalable, self-improving AI agents and models that learn from vast, diverse healthcare data and deliver meaningful insights through
Zafin is an AI platform company helping regulated institutions modernize how critical work is designed, governed, and delivered. Our technology enables organizations to move faster while maintaining the governance, accountability, and control required in highly regulated environments. Our portfolio includes Zafin AIOS , an agent orchestration platform for governed AI work; the Zafin Banking Platform , which helps banks modernize product, pricing, offers, billing, loyalty, and relationship management; and Zafin IO , an integration platform that connects data, systems, and workflows across complex enterprise environments. Headquartered in Toronto, Canada, Zafin partners with leading financial institutions across North America, Europe, the Middle East, Africa, and Asia-Pacific. As AI transforms the future of financial services, we're building the platforms that help regulated organizations adopt AI responsibly and at scale. What is the Opportunity? As a Machine Learning Engineer, part of Zafin's AIOS Product team , you will build the machine learning and AI systems that power the AIOS Knowledge Fabric and help agents reason over enterprise knowledge with accuracy, traceability, and control. You will work on practical production systems, including retrieval, ranking, embeddings, model integration, evaluation, data pipelines, model serving, observability, and the workflows that make AI outputs reliable for regulated banking environments. This is a hands-on engineering role focused on turning ML and LLM capabilities into dependable product infrastructure. This role is critical for high-quality knowledge, strong evaluation, and reliable model behavior. You will help build the foundation that allows customers to use AI agents with confidence, accountability, and measurable business value. What Will You Do? Design, build, test, and maintain ML and AI capabilities for AIOS, with a focus on knowledge retrieval, model integration, and producti
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. Your Location: This position is CHINA BASED . The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. Your recruiter will inform you what cities you are able to work from depending on your personal legal working identity and Airbnb internal policies. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. Your Location: This position is CHINA BASED . The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. Your recruiter will inform you what cities you are able to work from depending on your personal legal working identity and Airbnb internal policies. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible
About the Role Anyscale is seeking a Senior / Staff Product Manager to lead Ray Data, our scalable data processing library for ML and AI workloads. This is a uniquely challenging role that requires balancing open source growth with commercial differentiation - driving rapid adoption in the open source Ray Data ecosystem while building compelling proprietary features for Anyscale RunTime, our high-performance commercial engine. You'll own the entire Ray Data product roadmap in a competitive landscape, working closely with the engineering team, the field team, enterprise customers, and the open source community. Success requires: Deeply ingraining yourself into the end-user experience to understand the nature of the product and its gaps and tradeoffs Working closely with customers and open source users to draw the subtle line between growth and commercialization Strategic thinking about which parts of the ML/Data lifecycle to focus on, identifying opportunities where our architectural strengths create the most value. Thinking deeply about and clearly articulating the product strategy to stakeholders Key Responsibilities Drive the Ray Data product roadmap - Balance open source Ray Data feature development with Anyscale Runtime commercial differentiation to ensure that both Ray Data becomes the open source standard for AI data processing and Anyscale Runtime remains sufficiently compelling. Drive open source Ray Data adoption - Focus on community growth, developer experience, and ecosystem integrations Market Positioning & Enablement - Work closely with Product Marketing on strategic market positioning, field enablement, and competitive analysis to maintain differentiation. Customer engagement - Drive key customer engagements assisting sales and field engineering teams. Required Qualifications 4+ years of product management experience with technical products Strong technical background in distributed systems, ML infrastructure, or data processing Experience working
About Formation Bio Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, John Doerr, Spark Capital, SV Angel Growth, and others. You can read more at the following links: Our Vision for AI in Pharma Our Current Drug Portfolio Our Technology & Platform At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently. About the Position As a Senior Site Reliability Engineer at Formation Bio, you will build and operate the infrastructure, delivery systems, and operational practices that allow our engineering organization to ship reliable software quickly and safely. You will work across cloud infrastructure, developer platforms, observability, and production workloads, including product applications, internal tools, data systems, and ML and AI workloads, taking problems from initial diagnosis through implementation and production adoption. Formation Bio is an AI-native engineering
About the role Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently. As a Senior Software Engineer on the Machine Learning Platform team, you will design and build scalable systems spanning traditional machine learning and emerging AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic orchestration. You’ll work at the intersection of distributed systems, cloud infrastructure, applied machine learning, and AI product engineering. This role focuses on creating secure, reliable, and reusable platform capabilities that help teams choose the right approach, from conventional predictive models to LLM-powered and multi-step agentic systems, while maintaining strong standards for evaluation, observability, governance, privacy, and cost efficiency. In this role, you can expect to Design, build, and operate scalable ML and AI infrastructure on AWS. Design and operate shared platform capabilities for LLM and agentic workloads, including model access, prompt and configuration lifecycle, retrieval, tool integration, state management, and workflow orchestration. Build evaluation frameworks for non-deterministic AI systems, including offline benchmarks, regression testing, online quality signals, human feedback, and failure analysis. Establish observability, reliability, and governance for models and agents, covering traces, model and prompt versions, tool calls, latency, token usage, quality, safety, privacy, and cost. Help teams make principled architecture decisions across traditional ML, LLM-powered applications, and agentic workflows, and contribute to the platform’s technical roadmap. Build distributed training, batch inference, and large-scale processing systems using
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