Senior Staff Engineer Data Platform Experience Jobs

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ 🌏 Location: You can choose to work in Qonto as long as you're living in (or willing to relocate to) either Germany, France, Italy, Serbia, or Spain. Mission: Join us as a Backend Engineer to build the financial infrastructure that 600,000+ European SMEs depend on every day, from highly scalable APIs to robust banking services that handle real money, in real time, with zero room for mistakes. ➡️ As a Backend Engineer at Qonto, you will Design, build, deploy, and maintain services handling real financial transactions, owning reliability in production, not just at merge time Co-own service architecture, resilience, and scalability with respect to Domain-Driven Design principles Grow in technical leadership: lead design discussions, anticipate risks, and mento

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ 🌏 Location: You can choose to work in Qonto as long as you're living in (or willing to relocate to) either Germany, France, Italy, Serbia, or Spain. Mission: Join us as a Backend Engineer to build the financial infrastructure that 600,000+ European SMEs depend on every day, from highly scalable APIs to robust banking services that handle real money, in real time, with zero room for mistakes. ➡️ As a Backend Engineer at Qonto, you will Design, build, deploy, and maintain services handling real financial transactions, owning reliability in production, not just at merge time Co-own service architecture, resilience, and scalability with respect to Domain-Driven Design principles Grow in technical leadership: lead design discussions, anticipate risks, and mento

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ 🌏 Location: You can choose to work in Qonto as long as you're living in (or willing to relocate to) either Germany, France, Italy, Serbia, or Spain. Mission: Join us as a Frontend Engineer to craft the web apps that 600,000+ European SMEs rely on every day, from the customer-facing features that make finance simpler to the design system powering every pixel of our product. ➡️ As a Frontend Engineer at Qonto, you will Craft new features for our customers within a squad Team, owning quality from design to production. Grow in technical leadership: lead design discussions, contribute to guild-wide improvement, and raise the bar for developer experience across your peers Be a key player in teamwork with Product, Design, and other Tech stacks Work AI-first: use

P-1408 The Mission We are democratizing Data and AI for every enterprise user. Our vision is a world where anyone can master their organization’s data through Apps and AI Agents. We are building the retrieval backbone for two worlds: the high-precision context layer for AI agents and the intuitive search experience for people goal is the same: instant, accurate, and actionable insight. The Role : As a Search Quality Engineer, you sit at the heart of this transformation. You aren't just building a search engine; you are building the contextual backbone of the entire company. You will own the quality of results for two distinct but deeply connected "users": The AI Agent: Optimizing the retrieval layer that allows LLMs to reason over data they weren’t trained on, ensuring they have the "ground truth" needed to synthesize accurate, high-stakes business actions. The Human User: Improving the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces. The Technical Challenge This isn't a solved problem. You will be tackling "Search" in its most evolved form: Hybrid Retrieval: Balancing traditional keyword-based search (for exactness) with semantic vector search (for intent). Dual-Optimization: Fine-tuning ranking models that satisfy both human readability and LLM-ready context. High-Stakes Accuracy: In a world of Agents, poor search quality leads to hallucinations. You will build the guardrails and relevance scoring that ensure our AI stays grounded in reality. Data Heterogeneity: Connecting the dots across structured SQL tables, unstructured docs, and real-time business metrics. Why This is the Place to Be You will have a front-row seat to the Agentic revolution. If you want to solve the hardest problems in data discovery and see your work power the decision-making of thousands of people, let’s talk. What We’re Looking For The IR Specialist: You know your way around Lucene/Elasticsearch, embe

Our Perception team is responsible for using our sensor data to understand the complex and dynamic environments where we drive. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components. As a Senior Staff ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with other teams specializing in Prediction, Planning, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects. Responsibilities Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time Build multi-modal foundation models for on-vehicle and offline applications Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field Provide technical mentorship to the broader group of ML developers at Zoox Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying Deep Learning models on sensor data-Experience

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in Pyt

About Us: YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments. Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence. We operate globally with offices in the US (NYC, Austin, Miami, Mountain View) APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery. What It’s Like to Work at YipitData: YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals. From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers. Why Top Talent Chooses YipitData: Ownership That Matters : You’ll lead high-impact projects with real business outcomes Rapid Growth : We compress years of learning into months Merit Over Titles : Trust and responsibility are earned through execution, not tenure Velocity with Purpose: We move fast, support each other, and aim high—always with purpose and intention Who Thrives Here? We hire sprinters, not coasters—people who: Choose growth over comfort Lead through challenges Are energized by high expectations It’s not for everyone, and that’s intentional. If your ambition is matched by your work ethic—and you'r

Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company's ability to safely and quickly iterate on autonomy development. We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines. This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred. In this role, you will: Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors Improve the ML training pipelines supporting the autonomous behavior org Qualifications Bachelor’s degree in Computer Science or related field and 8+ years of industry experience Experience optimizing large-scale distributed systems for cost and efficiency Experience with AWS or similar providers Proficiency with Python and familiarity with C++ Bonus Qu

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron’s Heterogeneous Integration Group (HIG) is shaping the future of AI and accelerated computing by developing advanced memory solutions! The team focuses on designing and optimizing High Bandwidth Memory (HBM) products for AI/ML, high-performance computing (HPC), and data-centric systems, collaborating across global engineering and product teams to deliver industry-leading performance, power efficiency, and reliability! HBM product family is growing due to high demand from industry-leading semiconductor companies. As an HBM Memory Design Engineer you will work closely with cross-functional teams including Design Engineering (DE), Product Engineering (PE), Process Integration, Packaging, and Technology Development (TD) to analyze and resolve silicon issues across HBM products . You will collaborate with architecture to understand new or updated specification requirements and contribute to the implementation, verification, and maintenance of design updates , supporting both silicon release and ongoing product lifecycle needs. This role requires strong AI driven technical execution and the ability to independently drive complex issues to closure. Responsibilities Design Support: Work on HBM product design and support sustaining design maintenance (ECOs/spec changes). Silicon Debug: Own end-to-end debug of silicon, system, and customer issues, driving root-cause analysis and resolution. Cross-Functional Collaboration: Work closely with DE, PE, TD,

As a Senior Cost Engineer, you will support the Vehicle Program team by taking ownership of the Vehicle BOM cost and investments. You’ll partner with Engineering to ensure parts are designed with cost in mind while considering program volumes. You will be working with engineering experts in several areas such as drivetrain, trim & lighting, body & closures, EE, thermal, geometric integration, chassis, vehicle attributes and homologation. You will be an integral link to successfully developing and delivering a high-quality product to market. In this role, you will: Own and lead the execution of cost estimating and modeling processes within Vehicle Development Lead the development and maintenance of the Vehicle Development cost database to enable effective cost estimation throughout every phase of development Develop detailed cost estimates for vehicle components and systems Create detailed should-cost models for vehicle components, providing data-driven insights for key decisions Serve as the SME in value engineering and should cost modeling, identifying cost reduction strategies and value capture opportunities Collaborate with design teams to optimize component costs Qualifications BS or MS in Engineering 10+ years in Business Operations, Finance, Cost Engineering or Supply Chain Proven analytical and quantitative skills Automotive OEM experience and knowledge of vehicle systems and components Excellent communication and collaboration abilities Proficiency in Google Sheets and cost analysis tools Bonus Qualifications MBA or MS in Finance

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

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ ➡️ Mission: Join us as Analytics Engineer – Data Governance and become the architect of Qonto's data trust layer as we make our transition to a fully licensed bank. You will own end-to-end the Data Governance framework — defining rules, implementing controls, monitoring quality, and driving remediation across the company — so that every compliance report is reliable and every business decision is grounded in trusted data. You will work closely with Alice Fresko, our Head of Analytics Engineer, and with Paul, our Staff Analytics Engineer, and sit at the intersection of Data, Product, Engineering, and Compliance. This is a first-of-its-kind role at Qonto: you won't inherit a mature process, you'll build it. ➡️ As an Analytics Engineer at Qonto, you will: Build

At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs. If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. THE WORK: Ripple is building the Internet of Value: infrastructure that moves money as fast as information moves today. Every payment that flows across our network passes through real-time financial crimes controls: sanctions screening, wallet risk analysis, transaction monitoring, and travel rule compliance. The Financial Crimes Engineering team builds and operates that layer. This is the engineering that determines whether payments clear or hold, whether Ripple meets its regulatory obligations across jurisdictions, and whether the network can scale without compromising on compliance. The problem space is genuinely hard: high-throughput distributed systems, real-time decisioning, multi-source coordination across external compliance data providers, regulator-grade audit trails, and resilience. As a Senior Staff Software Engineer on this team, you will set the multi-year technical direction for the compliance control plane and drive its adoption beyond your own team. You will own the architecture of the vendor-agnostic, resilient, provable system that lets Ripple move value without moving financial crime, and you will shape how compliance engineering works across the company. This is a role for someone who defines which problems the organization solves, not only how they get solved: you will set the technical strategy other teams build against, establish the patt

At Bazaarvoice, we create smart shopping experiences. Through our expansive global network, product-passionate community & enterprise technology, we connect thousands of brands and retailers with billions of consumers. Our solutions enable brands to connect with consumers and collect valuable user-generated content, at an unprecedented scale. This content achieves global reach by leveraging our extensive and ever-expanding retail, social & search syndication network. And we make it easy for brands & retailers to gain valuable business insights from real-time consumer feedback with intuitive tools and dashboards. The result is smarter shopping: loyal customers, increased sales, and improved products. The problem we are trying to solve : Brands and retailers struggle to make real connections with consumers. It's a challenge to deliver trustworthy and inspiring content in the moments that matter most during the discovery and purchase cycle. The result? Time and money spent on content that doesn't attract new consumers, convert them, or earn their long-term loyalty. Our brand promise : closing the gap between brands and consumers. Founded in 2005, Bazaarvoice is headquartered in Austin, Texas with offices in North America, Europe, Asia and Australia. It’s official: Bazaarvoice is a Great Place to Work in the US , Australia, India, Lithuania, France, Germany and the UK! As the Lead Engineer of Portal Reports and Insights application team, your primary responsibilities will include designing and implementing distributed, fault-tolerant systems and creating high performance Reporting and Insights applications for Bazaarvoice clients that can run nearly 10k reports every week. These reports and insights are used to produce various metrics about Bazaarvoice products and programs so that their performance can be measured. Reports can also be used to simply export raw data about client's UGC like questions, answers, reviews and products, while Insights provides an

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index