Lead Deployment Engineer Jobs

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, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment,

About The Role & Team Amplitude is the leading AI analytics platform, and our ability to deliver measurable customer outcomes quickly is a key part of how we keep that lead. The Customer FDE (Forward Deployed Engineering) team sits at the intersection of engineering, product, and customer success — owning the technical delivery that takes validated products from co-development and implements them across enterprise customers. As a Customer Forward Deployed Engineer, you will own end-to-end technical delivery for enterprise customer implementations, from sales engagement through post-deployment validation. You'll work directly in Amplitude's product codebase, submitting PRs, shipping customer-specific solutions, and building reusable patterns that make every successive engagement faster. This is not a traditional support or solutions role. Customer FDEs are engineers first who partner closely with Sales, Customer Success, Product, and Engineering to turn customer needs into working software. The right person thrives in ambiguity, learns new domains quickly, and cares as much about the customer's outcome as about technical elegance. As a Customer Forward Deployed Engineer, you will: Own enterprise implementations end-to-end — engage during sales to map customer needs to capabilities, scope implementation plans, and deliver through post-deployment validation with measurable customer outcomes Work directly in the product codebase — submit PRs, test, and ship customer-specific solutions without requiring constant oversight; over time, the gap between "what we built" and "what the customer needs" keeps shrinking because you're the one closing it Ship early, ship often, and gather feedback — treat every customer interaction as an opportunity to validate your approach and course-correct quickly Build reusable patterns and playbooks — when you solve something once, make sure the next person doesn't have to solve it again; identify and document implementation patterns that

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Hardware Manufacturing Test Engineer at Everpure, you will spearhead manufacturing test enablement for our next-generation enterprise hardware platforms from New Product Introduction (NPI) through high-volume production ramp. Operating with high autonomy, you will design robust test strategies and collaborate cross-functionally with Firmware, Diagnostics, and global factory teams to deliver market-ready, high-yield hardware infrastructure. Your expertise will directly optimize manufacturing throughput, improve release quality, and accelerate the global deployment of the industry-defining Everpure Platform. WHAT YOU'LL DO Own NPI & Sustaining Test Readiness: Drive end-to-end manufacturing test strategy, test sequence definition, and coverage validation for multiple hardware infrastructure variants to ensure seamless factory execution and build readiness. Lead Debug & Yield Optimization: Independently lead technical triage and resolve complex system-level test fallout during critical build phases, analyzing failure paretos to isolate root causes across hardware, firmware, and test infrastructure. Scale Test Architecture & Frameworks: Enhance and standardize the Design for Manufacturing (DFM) hardware test architecture by deploying reusable automation frameworks and consolidating test execution into shared platforms to minimize factory cycle times. Drive Vendor & Cross-Functional Alignment: Colla

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. We are seeking a highly motivated V&V software development engineer in test (SDET) to join this systems-engineering department. As a V&V SDET, you will be a technical lead, owning the end-to-end validation strategy for critical safety systems while architecting and implementing the advanced software infrastructure required to verify them. This role is coding-intensive, focused on building solutions for high-fidelity testing, scalable automation frameworks, and sophisticated data analysis tools to ensure successful compliance to requirements and mission success. Some examples of tools this role supports: Framework for event definition, orchestration, and verification High-performance C++ and Python-based emulators for vehicle sensors (e.g., Radar, Lidar, and Inertial Measurement Units) to enable realistic, real-time fault injection Robust communication bridges between simulation environments and physical vehicle hardware Automating test management and reporting within lifecycle management tools, e.g. Polarion, JAMA, DOORS. In this role, you will: Lead the design and maintenance of large-scale event-driven software/hardware -in-the-loop (SIL/HIL) testing frameworks, utilizing advanced software patterns to improve modularity and reduce code duplication. Architect and manage end-to-end continuous integration (CI) pipelines to automate the execution of regression suites. Lead root cause analysis for complex system-level failures, developing log mining scripts and visualization dashboards (e.g., Grafana, SQL-based notebooks) to triage failures and track performance metr

CSQ327R39 As a Forward Deployed Engineer (FDE) for the Emerging Enterprise & Digital Natives business in EMEA. you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role The Developer Platforms mission at The New York Times builds the foundational platforms, tooling, and paved paths that help product teams ship high‑quality experiences quickly and safely. Our Application Delivery team owns the shared software delivery platform (CI/CD, artifact management) and deployment workflows used by hundreds of engineers across News, Cooking, Games and Audio to ship software. As the Times leans into AI‑assisted and agentic development, Application Delivery is where those changes become real. You will set the technical direction for how AI‑generated and agent‑driven change flows safely, observably, and at scale through CI/CD. You'll help teams reduce release risk with modern deployment patterns, and turn effective delivery practices into reusable pipelines and templates that scale across the organization, much like our GenAI platform roles turn internal practices into reusable tools and agents. When you improve this platform, you change how The New York Times ships software. You will report to the Engineering Manager of the DevEx Application Delivery team. Responsibilities Lead the technical direction of software delivery as a shared product: shape paved paths in our shared platform that improve code health, release quality, and delivery speed for product teams. Set the technical direction for agent‑ready delivery: design the policy, guardrails, and paved paths that turn AI‑generated and agent‑driven chang

👋 Welcome to Glide! At Glide we’re reimagining the banking experience for the modern world . Our embedded fintech platform empowers legacy financial institutions, like community banks and credit unions, to pioneer novel digital experiences for their customers. You’ll be joining an all-star team with engineering, product, and growth experience from Stripe, Google, and Amazon. We’re looking for a talented early career Fullstack Engineer to help us build our platform. We’re bringing a new perspective to the decades-old financial world , and we’re hoping you can help us do that! Why You’ll Love This Role (Especially if you’re a new grad): A unique opportunity to work side-by-side with Glide’s founders and senior engineers, learning directly from industry veterans. Gain hands-on, end-to-end experience across the full stack: from architecture design to deployment. Be part of a small, fast-moving startup, where your code has immediate impact. Get mentorship and exposure to real-world engineering best practices, product development, and startup culture. Your Responsibilities: Move seamlessly between frontend and backend to build a well-tested, secure frontend for our core web product. Create trustworthy, safe user experiences by building interfaces that are simple, reliable, and performant using tools like Typescript, React, Node.js and NextJS . Design a scalable architecture that can serve hundreds of thousands of end users. Bring designs to life through beautifully-crafted code. Articulate a long-term technical direction and vision for maintaining and scaling our web product suite. Lead frontend and backend infrastructure & tooling for an ambitious product roadmap. Need-to-Haves: Experience with Javascript and tools like Typescript, React, Node.js and NextJS . Experience with modern, responsive HTML & CSS . Experience using data fetching libraries like React Query/Tanstack or tRPC to synchronize client and server data. Excellent understanding of software engineer

👋 Welcome to Glide! At Glide we’re reimagining the banking experience for the modern world . Our embedded fintech platform empowers legacy financial institutions, like community banks and credit unions, to pioneer novel digital experiences for their customers. You’ll be joining an all-star team with engineering, product, and growth experience from Stripe, Google, and Amazon. We’re looking for a talented early career Fullstack Engineer to help us build our platform. We’re bringing a new perspective to the decades-old financial world , and we’re hoping you can help us do that! Why You’ll Love This Role (Especially if you’re a new grad): A unique opportunity to work side-by-side with Glide’s founders and senior engineers, learning directly from industry veterans. Gain hands-on, end-to-end experience across the full stack: from architecture design to deployment. Be part of a small, fast-moving startup, where your code has immediate impact. Get mentorship and exposure to real-world engineering best practices, product development, and startup culture. Your Responsibilities: Move seamlessly between frontend and backend to build a well-tested, secure frontend for our core web product. Create trustworthy, safe user experiences by building interfaces that are simple, reliable, and performant using tools like Typescript, React, Node.js and NextJS . Design a scalable architecture that can serve hundreds of thousands of end users. Bring designs to life through beautifully-crafted code. Articulate a long-term technical direction and vision for maintaining and scaling our web product suite. Lead frontend and backend infrastructure & tooling for an ambitious product roadmap. Need-to-Haves: Experience with Javascript and tools like Typescript, React, Node.js and NextJS . Experience with modern, responsive HTML & CSS . Experience using data fetching libraries like React Query/Tanstack or tRPC to synchronize client and server data. Excellent understanding of software engineer

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The Eval Platform team owns the simulation and evaluation and validation platform that underpins autonomy development and driverless readiness validation. This platform is mission‑critical for both rapid iteration during development and rigorous validation used to assess safety, performance, and deployment readiness. We are looking for a seasoned engineering leader to lead the Eval Platform as a Director‑level role. This leader will define the technical vision, execution strategy, and organizational structure for a multi‑disciplinary org spanning simulation, evaluation infrastructure, and compute and storage platform. The evaluation platform brings together data, simulation, metrics, and analysis workflows into a coherent system that allows the teams to: Iterate quickly to improve the autonomy performance Measure autonomy performance and risk with credibility and rigor Make confident, data‑driven decisions about driverless

About the Team The Merchant (Mx) AI/ML team is a cornerstone of DoorDash’s merchant organization. We empower our restaurant partners to thrive on DoorDash by building intelligent, scalable AI systems that simplify operations, elevate their digital presence, and enhance customer engagement. Our world-class machine learning engineers develop production-grade AI solutions that power the entire merchant lifecycle — from onboarding and store setup to menu management, growth, and real-time order operations. The team is deeply customer-obsessed and impact-driven, focused on turning cutting-edge research in LLMs, multimodal learning, generative AI, and agentic automation into products that make our merchants more successful every day. About the Role We’re looking for an Engineering Manager to lead the Mx AI/ML team, driving the design and deployment of next-generation AI product solutions that power our merchant experiences. This is a highly cross-functional leadership role — you’ll collaborate with product, design, operations, and data science teams to define the AI roadmap, guide technical direction, and deliver end-to-end AI/ML solutions at massive scale. You’ll lead a team of talented ML engineers who are building real AI products delivered to merchants’ fingertips, helping them become more successful on DoorDash. You’re excited about this opportunity because you will… Lead and grow a team of exceptional AI/ML engineers developing production-grade machine learning and generative AI solutions for the merchant ecosystem. Define a multi-year strategy and execute the AI roadmap across key Mx pillars — Onboarding, Menu Media Understanding & Generation, Menu Metadata Intelligence, and Agentic Task Automation. Partner with product and operations to translate merchant pain points into scalable AI-powered solutions. Own the end-to-end lifecycle of ML systems — from ideation and experimentation to productionization and continuous improvement. Drive innovation in multimodal AI

Who is Artefact? Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact. With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design. Main Responsibilities As a Senior Technical Consultant / Senior AI Engineer , you will lead the design and delivery of impactful AI and data solutions. You’ll combine hands-on engineering with client advisory, guiding multi-disciplinary teams from opportunity framing to production deployment. Own solution architecture & delivery: Define end-to-end architectures (data, ML/LLM, APIs, security), make build/buy decisions, and drive projects from PoC to production with reliability, observability, and cost in mind. Lead complex PoCs & pilots: Scope, prototype, and validate AI/ML use cases (incl. LLMs/GenAI, RAG, fine-tuning, evaluation) and convert successful pilots into scalable products. Advanced programming & modeling: Build, adapt, and evaluate ML/DL/LLM models using Python (PyTorch, TensorFlow, HuggingFace, LangChain/LlamaIndex), including prompt engineering, fine-tuning/LoRA, vector search, and safety/guardrails. Cloud & MLOps/LLMOps: Design and operate solutions on Azure, GCP, or AWS (CI/CD, containers, model serving, feature stores, vector DBs, monitoring, eval pipelines). Client advisory & stakeholder management: Translate business goals into technical roadmaps, present to senior stakeholders, manage risks and trade-offs, and ensure measurable business impact. Quality, se

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the role Software engineers (Ad Cloud Bidding) at Appier Tokyo office build a wide range of platforms and services that interconnect data and AI with our customers and users. As a Staff Software Engineer , you will play a critical role in designing and building scalable and performant backend architecture, owning and driving the technical roadmap for sizable projects or services. You will also take responsibility for service operations – ensuring reliability, availability, and efficient deployment of large-scale distributed systems. Responsibilities Engage in the design of large-scale backend systems and distributed services Contribute to technical roadmap and planning Collaborate with cross-functional teams to deliver robust and high-performance systems Troubleshoot production issues and contribute to root cause analysis Ensure high reliability through best practices in service operation, monitoring, and deployment Participate in on-call rotations and lead incident response when required About You [Minimum qualifications] 8+ years of experience in software development Proficient in modern C++ programming (C++11 and later) Familiar with Unix/Linux environments Solid understanding of system programming Experience in developing low-latency (millisecond-scale) and high-throughput (>1K QPS per machine) systems Experience in service optimization and performance tuning Strong sense of ownership and good problem-solving skills [Preferred qualifications] Experience in modern build systems Experience in operation automation tools Ex

About Appier Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. About the role Software engineers (Ad Cloud Bidding) at Appier Tokyo office build a wide range of platforms and services that interconnect data and AI with our customers and users. As a Senior Software Engineer , you will contribute to building scalable backend systems while also participating in service operation activities, including deployment, monitoring, and incident response, to ensure reliable and high-performing distributed services. Responsibilities Design, implement, and optimize backend services Participate in code reviews and contribute to system design discussions Collaborate with cross-functional teams to deliver robust and high-performance systems Troubleshoot production issues and contribute to root cause analysis Support system deployment, monitoring, and maintenance in production environments Participate in on-call rotations and lead incident response when required About You [Minimum qualifications] BS/MS degree in Computer Science or related fields 3+ years of experience in software development Experience in modern C++ programming (C++11 and later) Familiar with Unix/Linux environments Good interpersonal and problem-solving skills and strong sense of ownership [Preferred qualifications] Good understanding of system programming Experience in developing low-latency (millisecond-scale) and high-throughput (>1K QPS per machine) systems Experience in service optimization and performance tuning Experience in modern build systems Experience in operation automation tools [Language] Fluent in English or Chinese. Open to

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language