Laser Design Engineer Jobs

RDQ427R198 The Opportunity Multi-cloud is core to Databricks product strategy. Compute serves as the layer that abstracts the cloud from the rest of the company. Building unified infrastructure on top of heterogeneous clouds is a challenge that few companies experience. As an engineer on this team, you won’t just manage infrastructure; you will build it as a product. You will tackle the hard problems of distributed systems: sub-second container/MicroVM startup times, multi-tenant security isolation, and building a unified orchestration layer that scales across AWS, Azure, and GCP. What You’ll Do Design and build the next generation of our Serverless platform, focusing on high availability, low latency, and scale-to-zero efficiency. Build a single compute stack that supports heterogeneous workloads, including GPU instance qualification for AI training and stateful execution for Lakebase. Solve Multi-Cloud Complexity: Develop platform-level abstractions that allow Databricks to run seamlessly across all major cloud providers. Optimize everything from the API gateway down to the host-level networking and container orchestration. Work alongside industry experts who have built world-class systems like Borg, Kubernetes, and Uber’s infrastructure. What We’re Looking For 5+ years of production-level experience in one of: Python, Java, Scala, C++, or a similar language 4+ years of experience developing large-scale distributed systems from scratch Experience with Kubernetes, Docker, or MicroVM technologies (e.g., Firecracker) and a strong grasp of cloud provider internals (AWS/Azure/GCP). You aren't just a user of tools; you understand how to build them from the ground up when existing solutions fail at our scale. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.&n

Zoox is looking for an AWS Cloud Security Engineer to lead the design and implementation of secure, scalable, and software-defined infrastructure in our AWS cloud environment. This role is responsible for establishing best-in-class security practices across AWS, driving automation-first infrastructure security, and partnering with engineering and platform teams to embed security into every layer of our technology stack. You’ll act as a security champion, ensuring that infrastructure designs meet the highest standards of confidentiality, integrity, and availability — while maintaining operational efficiency and scalability through Infrastructure as Code (IaC). In this role, you will: Define and own the multi-year security architecture and roadmap for Zoox's robots and fleet, spanning embedded/firmware, in-vehicle networks, cloud, and supporting infrastructure. Partner with hardware, firmware, autonomy, and infrastructure engineering teams to embed security requirements into system design from the ground up, rather than bolting them on after the fact. Lead threat modeling and architecture reviews for new vehicle platforms and major feature launches, identifying and prioritizing systemic risk across the fleet. Set technical standards and guardrails - secure boot, key management, network segmentation, update/OTA security, and more - and drive their adoption across engineering teams. Represent Product Security in cross-functional and leadership discussions, translating technical risk into business and safety impact for the organization. Qualifications 10+ years of experience in security engineering, including significant time in an architect, staff, or technical lead capacity. Deep expertise in embedded/IoT security, including secure boot, TPM/TEE, cryptographic key management, and hardened firmware/OS design. Demonstrated experience architecting security for complex, physical/cyber-physical sys

Zoox is seeking a high-agency, hands-on Lead Analytics Engineer to bridge the gap between our complex enterprise data sources and our AI-driven decision-making systems. You will lead the design and implementation of our semantic layer and data modeling strategy, ensuring that data from SAP (S/4HANA, Ariba, BRIM, ME), Workday, Salesforce, and Anaplan is transformed into clean, performant, and "AI-ready" datasets. This is a critical leadership role for a builder who wants to own the data foundation that powers our intelligent agents and business-wide analytical workflows. In this role, you will: Design and maintain a unified semantic model that provides a "single source of truth" for cross-functional stakeholders, AI Agents, Self Serve Analytics and Executive dashboards. Collaborate with Data & AI Engineers to structure and optimize the data that allows to query enterprise knowledge with high accuracy and low latency. Establish organizational standards for data modeling, version control, testing, and documentation to ensure high data quality and system maintainability. Implement automated testing and observability frameworks that proactively identify data anomalies and "self-heal" pipelines, ensuring our data is always reliable for downstream consumption. Partner with cross-functional business leaders to translate complex operational requirements into high-impact, scalable data solutions. Qualifications: 10+ years in Data Engineering & Analytics, with extensive hands-on experience building a semantic framework using Python, SQL and modern orchestration frameworks (e.g. Airflow, Lakeflow, Argo). With at least 2+ years of hands-on experience deploying AI generated code. Extensive experience using modern data stacks (e.g. Snowflake/Databricks, Big Query) to build complex, enterprise-grade data models. Deep understanding of data structures within large-scale enterprise platf

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Server Platform is at the core of Figma's infrastructure foundation! This area owns the foundational layer of infrastructure that underpins all other infrastructure and application services at Figma. The Foundation team under Server Platform is Infrastructure's infrastructure. This team enables the efficient operation and rapid development of reliable infrastructure at Figma through opinionated platforms. We are building the V2 of Infrastructure and setting key initiatives that will set the tone for infrastructure for the next half decade. We're looking for thoughtful and technical leaders with experience focused on designing the next generation edge and network to handle our growing customer traffic and services. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Design, build and operate scalable distributed systems and services that power Figma's innovative tools for design and collaboration Develop and secure our internal and edge network running on AWS Help design and deploy an internal service mesh network which can support Figma's growing portfolio of services and features Develop intelligent detection and auto-scaling countermeasures for DDoS threats Debug and resolve production issues across services and multiple layers of the stack, reducing mean time to resolution for critical incidents We’d love to hear from you if you have: 4+ years of experience building infrastructure components and services at scale in a cl

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Machine Learning Engineer on the CX Intelligence team within Enterprise Applications and Architecture, you'll build the AI-powered conversational systems that connect Coinbase's Help Center, chatbots, and agent workflows. The team owns the multi-agent platform powering Coinbase Chat and agent tooling, partnering with Conversation Design, CX, and Engineering to deliver secure, scalable automated support. You'll lead the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants, directly improving how millions of customers get help. What you'll do: Architect and deploy the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products. Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery. Establish best practices for system design, coding standards, and AI/ML development workflows across the team. Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team. Co

Here’s a summary of the role: You are a seasoned AI engineer ready to design, ship, and own production‑grade agentic systems that solve real enterprise problems. At Diligent, you’ll take technical ownership of Compliance in a Box (CiaB) — a flagship AI platform reshaping how organisations manage governance, risk, and compliance at scale. You’ll architect and evolve the AI reasoning layer and agent orchestration framework at the heart of the product, shaping how multiple intelligent agents collaborate, reason, and operate safely in high‑stakes, regulated environments. This is hands‑on, deeply technical work — from system design to prompt strategy to evaluation — not research theatre. Partnering closely with product, security, and platform teams, you’ll make high‑impact decisions, move quickly, and see your work land in production fast. If you’re motivated by ownership, technical depth, and building AI systems that actually matter , this is your chance to set the standard for enterprise‑ready agentic AI. Here’s a breakdown of what you’ll do (not all of it, just the important stuff): Build and maintain the GRC Brain (AI reasoning layer) and Agentic Cortex (agent orchestration framework) — the technical core of our Compliance in a Box product Design and implement a 7-agent architecture : OnboardingAgent, ScopeAgent, StandardsMapper, RiskQuantifier, PolicyAnalyzer, InfrastructureAuditor, and ComplianceMonitor Implement Human-in-the-Loop (HITL) gates across agent workflows, and tune prompts and confidence scoring for Bedrock-hosted models Own the agent evaluation framework — measuring quality, latency, and reliability to keep CiaB performant and production-ready Collaborate with cross-functional teams to deliver CiaB feature-complete by Week 7 — your work ships fast and your impact is visible from day one These are the essentials you’ll need to get an interview: A degree in Computer Science, Software Engineering, or a related IT discipline Demonstrable understandin

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! As a Software Engineer, you'll work on some of the most technically challenging and impactful parts of our product. You will be developing high-performance client-side systems in C++/WebAssembly, extending the multiplayer protocols that make collaborative design possible, and building out the communications layer between C++ and Javascript. Your contributions will help push the boundaries of what's possible in the browser. You'll also help shape our user experience by building features that are fast, accessible, and intuitive—even in the face of complex data models and intermittent connectivity. This is a highly collaborative role: you'll partner closely with designers, product managers, and other engineers to plan, build, and iterate on features that serve millions of users around the world. Whether you're optimizing our core engine, building authoring tools, or crafting new platform abstractions, your work will be key to advancing the future of design. This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Build core features and frontend infrastructure in a real-time, multiplayer system with a complex in-memory data model (SceneGraph) Optimize performance and memory usage to deliver a fast, reliable UX in the browser using C++/WebAssembly and TypeScript Extend our core C++ engine and multiplayer protocols to support scalable design systems, branching/merging flows, and advanced collaboration modes Design and build APIs and

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Card Loan Platform team builds the high-throughput decision engine at the heart of Affirm’s card products. Unlike traditional cards, every pay-later transaction is backed by its own unique loan, and our system is the "invisible piping" that makes this complex model work at scale. Every swipe triggers our platform to solve a hard problem in milliseconds: matching messy, fragmented payment network data to the correct loan to drive real-time approvals, origination, and refunds. As Affirm experiences explosive growth, our team's contributions are a key enabler. This isn't just another backend role; you'll be building the "financial brain" for our flagship card products, with your work on the critical path for every single swipe. We're tackling a unique, high-stakes distributed systems challenge that demands exceptional correctness and massive scale. You will partner closely with product, data science, and engineering teams to design and build the future of our industry-leading money movement platform. If you are passionate about making foundational design decisions and building a beloved, lasting financial brand—come join us. It’s going to be an amazing ride! What you'll do Drive technical strategy by leading the planning, prioritization, and execution of projects, ensuring alignment with product, technical, and business goals. Lead the end-to-end system design and development of large-scale, high-availability services. This includes building robust APIs and data models for our micro-service and event-driven architectures. Collaborate across functions with partners in Product, Analytics, Design, Legal, and Accounting and to define requirements and execute our card loan attribution and lifecycle strategy. Ensure system health and performance by analyzing and troubleshooting complex technical

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The Card Loan Platform team builds the high-throughput decision engine at the heart of Affirm’s card products. Unlike traditional cards, every pay-later transaction is backed by its own unique loan, and our system is the "invisible piping" that makes this complex model work at scale. Every swipe triggers our platform to solve a hard problem in milliseconds: matching messy, fragmented payment network data to the correct loan to drive real-time approvals, origination, and refunds. As Affirm experiences explosive growth, our team's contributions are a key enabler. This isn't just another backend role; you'll be building the "financial brain" for our flagship card products, with your work on the critical path for every single swipe. We're tackling a unique, high-stakes distributed systems challenge that demands exceptional correctness and massive scale. You will partner closely with product, data science, and engineering teams to design and build the future of our industry-leading money movement platform. If you are passionate about making foundational design decisions and building a beloved, lasting financial brand—come join us. It’s going to be an amazing ride! What you'll do Drive technical strategy by leading the planning, prioritization, and execution of projects, ensuring alignment with product, technical, and business goals. Lead the end-to-end system design and development of large-scale, high-availability services. This includes building robust APIs and data models for our micro-service and event-driven architectures. Collaborate across functions with partners in Product, Analytics, Design, Legal, and Accounting and to define requirements and execute our card loan attribution and lifecycle strategy. Ensure system health and performance by analyzing and troubleshooting complex technical

What you’ll do Own the tissue-class segmentation and labeling models for the ultrasound CT clinical analysis layer, and the pipelines that make them trainable and verifiable. Retune across 2D per-slice, 3D volumetric, and 2D×3D fusion as reconstructed image inputs are continuously updated, and clinical indications for use expand. Define training/evaluation pipelines, datasets, and metrics from the ground up or from open source; map model behavior to user needs and design requirements. Work with data labeling contractors, expert clinicians, and our internal cloud/data teams on labeling specs, QC, and dataset versioning. Help productionize models into a versioned, HIPAA-bound analysis service: reproducible/low-latency inference, per-prediction confidence, drift monitoring, and safe fallbacks. What we’re looking for Strong applied ML experience with a track record of developing new models — architecting, training, and evaluating from scratch as well as benchmarking against existing models. Experience with image segmentation (semantic/instance, 2D and ideally 3D/volumetric) and the modeling and training-data choices that make it robust across diverse patient anatomy. Comfortable moving fluidly between open-ended research iteration and producing quantifiable, testable models. Fluent in modern deep-learning tooling (e.g., PyTorch) and current development practices. Comfortable working under design controls, where model changes carry documentation and verification weight. Useful experience Image segmentation and label generation with modern architectures (U-Net / nnU-Net, 3D U-Net, transformer-based and promptable segmentation like SAM), including the geometry that ties voxel- and mesh-level predictions back to a coordinate frame. Learning under limited or noisy supervision: self-supervised / semi-supervised methods (masked autoencoders, contrastive pretraining like DINO/SimCLR), active learning, weak labels, and simulation-driven pretraining. Hands-on experience with data

On-site | Vancouver Office – 564 Beatty St About EviSmart EviSmart builds the automation layer that dental laboratories run on. A dental lab is a manufacturing operation. A case arrives from a dentist — a 3D scan of a patient's mouth and a prescription — and leaves as a crown, bridge, denture or night guard. In between sit a dozen manual steps: monitoring scanner portals, retyping cases into lab software, checking scan quality, interpreting handwritten prescriptions, designing the restoration. We automate that pipeline. Our software connects to 15 intraoral scanner portals and more than five lab management systems, pulls cases the moment they arrive, reads the prescription, maps it into the lab's own product catalogue, checks the scan, and routes it to design. We serve roughly 6,000 customers across 28 countries from offices in Vancouver, Manila, Seoul and Shenzhen. The automation works. It does not yet work well enough, consistently enough, to run unattended — and closing that gap is the highest-leverage technical problem in the company. What you'll do Establish measurement. Build per-model, per-customer, per-category accuracy reporting that Product and Sales can act on. Nothing else you do matters until this exists. Build the correction flywheel. Capture the quality-control corrections our customers already make, turn them into structured, versioned training data, and close the loop with human review where confidence is low. Standardize the squads. One deployment path, one evaluation harness, one model and dataset registry across restoration design, scan quality, prescription extraction and agents. Solve multi-tenant model behaviour. Thousands of customer-specific product codes, prescription conventions and unwritten preferences sitting over a shared model base — without building a bespoke model per customer. Take inference to production scale. Move workloads from on-premise to cloud with understood cost per inference and real concurrency headroom. •

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. Overview We are hiring a Junior Full Stack Engineer. You’ll work across the stack to help design, build, and ship user-facing payment products, turning complex financial workflows into experiences that feel simple, fast, and reliable. This is a hands-on, product-focused role where you’ll contribute to meaningful projects from day one. You’ll write production code, solve real customer problems, use AI tools to accelerate how you build and learn, and gain exposure to the full product development lifecycle. You’ll work closely with experienced engineers and partner with Product, Design, Operations, Risk, and Compliance, giving you the opportunity to learn how great products are built in the complex world of payments. If you’re curious, eager to learn, love building, and want to grow alongside a fast-moving startup, we’d love to meet you. What You'll Do Build and scale user-facing fintech products that power Breeze's payments platform. Use AI tools (Claude Code and similar) as a core part of your workflow to scope, plan, and execute large projects across a large, multi-service codebase. I

OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity We are building the foundational data infrastructure that powers one of the world's leading crypto exchanges. As a Big Data Platform Engineer , you will design, build, and evolve the core platform services that enable hundreds of data engineers and analysts to move fast and ship reliable pipelines. You will be at the forefront of our AI agent initiative — embedding LLM-driven capabilities directly into the platform layer so that scheduling, cost optimization, and incident response increasingly run autonomously. What You’ll Be Doing Platform Core: Design and operate large-scale distributed data systems Own the big data compute and storage infrastructure (MaxCompute/ODPS, Hologres, Spark) Build and maintain multi-site task orchestration that dynamically selects engines and enforces policy Drive reliability and performance improvements across batch and real-time pipelines AI Integration: Build the AI-native platform layer Develop an

About the Role The Enterprise Knowledge Platform team builds the data layer that lets Perplexity's agents reach into the world's software. This team owns the systems that turn hundreds of heterogeneous integrations (native, MCP, CLI, first-party, and third-party APIs) into one unified, reliable, well-typed surface that agents can call with confidence. This platform is the core layer that forms the knowledge layer for Computer: it is how the agent discovers what tools exist, understands what each one means, decides which to call, and grounds its reasoning in real, permissioned, up-to-date enterprise data. We maintain a knowledge layer above connectors that pushes and pulls context into them, rather than letting each connector hoard org knowledge on its own, making Computer the source of truth for institutional knowledge. Models are commoditizing; grounded, actionable, permissioned access to a customer's real systems is not. When this layer is fast, accurate, and semantically rich, every agent built on top of it gets smarter; when it is weak, no amount of model quality compensates. Key Responsibilities Own the design and implementation of the connector runtime, the system that registers, hosts, and executes built-in connectors, hosted MCP servers, and CLI-backed tools behind a single agent-facing interface. Build and extend the semantic layer: tool and entity schemas, capability metadata, relationship modeling, and the mechanisms for capturing and applying organization- and account-specific corrections and knowledge. Design the tool-discovery and tool-selection surfaces that agents use to find the right connector and call it correctly, optimizing for both model accuracy and context efficiency. Make agent loops robust: structured results, partial-failure and retry semantics, idempotency, pagination, rate-limit handling, and observability into every tool call an agent makes. Define authentication, authorization, and credential-isolation patterns for connectors (OAuth fl

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma's AI Tools team builds the AI-powered workflows, platforms, and tooling that make every engineer at the company more productive. From agentic CI auto-fixing and AI-assisted code review to background cloud agents that turn a Slack message into a pull request, this team owns the systems that are transforming how Figma builds software. The team operates across a three-layer platform stack—sandbox runtime, cloud agents, and workflow orchestration—while shipping and maintaining a growing portfolio of org-wide developer workflows that compound across hundreds of engineers. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Lead and grow a team of engineers responsible for building and operating Figma's AI developer workflows and the cloud agent platform that powers them Own the technical strategy and roadmap for AI Developer Experience, spanning sandbox runtime infrastructure, cloud agent reliability, workflow orchestration, and org-wide agentic workflows Hire and scale the team - establishing team culture, execution cadence, and operational processes from the ground up Drive the reliability, observability, and scalability of our cloud agent platform, ensuring it meets production-grade standards as adoption grows across the engineering organization Partner with product engineering, security, infrastructure, and DevEx teams to identify the highest-leverage opportunities for AI-assisted developer workflows and drive adoption