Laser Design Engineer Jobs

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 Senior Software Engineer on the Overseer team within FinHub in the Platform group, you'll build and scale the real-time integrity layer that enforces financial correctness across every Coinbase fund flow. Overseer makes the rules that must always hold between systems explicit, detects violations in seconds rather than quarterly reconciliations, and works with every team at Coinbase that moves money. You'll own workstreams end-to-end, from designing correctness models with partner teams to operating detection systems in production, contributing directly to the platform that keeps billions of transactions accurate and trustworthy. What You'll Do: Build and scale real-time invariant enforcement systems across Coinbase's fund flows, contributing to the core detection engine, invariant framework, and onboarding tooling that partner teams rely on Own workstreams end-to-end, from designing correctness models with partner teams through production operation, ensuring new fund flows are covered by Overseer's integrity guarantees Develop AI-powered guardrails including predictive consistency models that flag deviations at initiation and proactive invariant discovery that surfaces coverage gaps before incidents occur Partner with teams across FinHub, Payments, and Trading to design and implement correctness contracts for new and existing fund flows, translating financial ru

About the Role Discover your future at Citi Working at Citi is far more than just a job. A career with us means joining a team of more than 230,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community and make a real impact. Job Overview Citi's Integrated Digital Assets Platform (CIDAP) is at the vanguard of institutional blockchain adoption — and security is its foundation. As digital assets move from innovation to regulated infrastructure, the cryptographic integrity of every transaction, wallet, and key lifecycle operation becomes mission-critical. We are building the security layer that the world's most sophisticated financial institution can trust. We are seeking a Senior Security Engineer (VP) to join our New York-based Digital Assets Platform engineering team. This is a hands-on, Java-focused backend engineering role for a security-minded engineer who understands both the craft of secure software development and the cryptographic primitives that underpin digital asset custody, signing, and key management. You will sit inside the core engineering team — writing production code every day — while being the resident authority on cryptographic design patterns, HSM integration, MPC protocols, and security architecture. Your work will directly protect billions of dollars of digital asset infrastructure used by institutional clients worldwide. Key Responsibilities Design, develop, and maintain security-critical backend services in Java — including cryptographic libraries, key management APIs, signing wor

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Responsibilities Lead hardware circuit design, schematic capture, and layout review for next-generation, high-density, and high-throughput networking platforms. Evaluate and integrate advanced switching architectures, management subsystems, and cutting-edge high-speed interconnect technologies. Drive hardware architecture design, system bring-up, high-speed signal integrity (SI) validation, and root-cause failure analysis. Partner with mechanical, thermal, and power engineering teams to address challenges related to high power density, thermal dissipation, and system-level reliability. Own BOM structure and support factory deployment to ensure seamless transition of high-layer-count PCBAs from NPI to mass production. Collaborate with cross-functional software, firmware, QA, and compliance teams throughout the entire product lifecycle. Q ualifications Bachelor’s degree or above in Electrical Engineering or a related discipline. 5+ years of hands-on experience in high-complexity system-level hardware design, ideally focused on enterprise-grade networking or high-performance infrastructure equipment. Deep technical understanding of high-speed Ethernet design, high-speed differential signals (advanced SerDes, PCIe, multi-gigabit/ultra-high-speed interfaces), and high-density PCB design rules. Practical experience with complex power d

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 Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build 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. This is an architect-and-build role. 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 — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role The Context Engine team builds the knowledge layer that AI agents use to work with enterprise data in Elasticsearch. We extract knowledge from any data sources into a structured AI Index, serve it to agents through public APIs, MCP tools and framework integrations, and close the loop with agent traces so that what the engine knows improves from real usage. Any agent can use it: Elastic’s own Agent Builder, Claude Code, LangChain and other third-party harnesses. As a Principal AI Engineer, you own the improvement loop of this product end to end: how agents, automations and skills behave in production, how we observe them, how we evaluate them, and how we ship changes to them safely. This is a hybrid role at the intersection of engineering, data science, and product. You will write production code, design evaluation and telemetry that product decisions can rest on, and set the technical bar for how the team iterates on agentic behaviour. You will work alongside data scientists, backend engineers, product, and UX, and your work will show up directly in what customers build on top of Elastic. The codebase is TypeScript and we build it in the open, so you'll be shipping code, designs and discussions in public alongside the rest of the Elastic Stack. What You Will Be Doing Own the production improvement loop for Context Engine: underst

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: The Engine Orchestration team builds and operates the distributed services that run, scale and balance the analytical query engines. We are the layer that turns a customer's model into something they and their AI agents can query interactively using our Process Query Language across enterprise-sized datasets. The team actively evolves our new premium query engine, collaborating with multiple other teams across time zones. New features, improved operationability, robust security, and allowing for scalable customer workloads are ours to design and ship. Our defining program right now is a multi-year migration of the query engine that has powered Celonis for years onto our new premium query engine. It is one of the largest and highest-leverage engineering efforts in the company. The Role: We are looking for a Senior Software Engineer to lead both the engineering that evolves the new premium query engine and the execution of milestones within the migration program that moves customer workloads onto it. This is not a lift and shift. The two query engines evolved with different focus areas and the new premium query engine serves different forward looking use cases, so the job is keeping customer workloads running seamlessly thro

About Druva Druva is the resilience foundation for the AI enterprise, helping organizations secure and recover from connected risk across data, cyber, identity, and AI. The Resilience Cloud is a fully managed, cloud-native SaaS platform that delivers air-gapped and immutable protection across cloud, SaaS, on-premises, endpoint, and edge environments. Powered by Dru MetaGraph, Druva’s graph-powered intelligence layer, the platform connects critical business context so customers can understand risk, respond faster, recover cleanly, and govern data with greater confidence. Trusted by nearly 7,500 customers, including 75 of the Fortune 500, Druva helps safeguard the critical information and systems businesses depend on in an increasingly connected world. Visit druva.com and follow us on LinkedIn , X and Facebook . The Role We are looking for a highly skilled SDET to join our Agile development team. In this role, you will not just test software; you will deconstruct complex features to understand their design, build robust automation frameworks, and ensure the resilience of our cloud-based backup solutions. You will work closely with developers to perform white-box and black-box testing, owning the quality of features from conception to deployment. Required Skills & Qualifications Operating Systems & Core Concepts: Proficiency in Windows and Linux OS . Deep understanding of Threading, Multiprocessing, and Socket Programming . Strong knowledge of Networking protocols and Cloud Architecture. Programming & Scripting: Strong proficiency in one or more high-level languages: Python, Golang. Experience with SQL databases . Testing & Tools: Expertise in RESTful API testing . Proficiency with bug and test management tools (e.g., Jira, XRay ). Familiarity with Agile testing methodologies and quality metrics. Strong analytical, troubleshooting, and debugging capabilities. Version Control: Proficiency with Git or SVN . Pluse

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. We’re looking for a Senior Android Engineer to join our SDUI team. In this role, you’ll help us build and scale our server-driven UI ( SDUI ) platform, enabling teams to build a UI once and have it deploy seamlessly to iOS, Android, and Web without redeploying a new app — performantly and consistently. This role is based in our London office with a hybrid setup, typically three days in the office. What You’ll Be Doing You’ll be joining the SDUI team. We own the Android rendering layer of our server-driven UI platform, and the backend services that drive it, ensuring every consumer surface built on it is fast, correct, and visually indistinguishable from native. Here’s what your day-to-day might look like: Drive technical execution by designing, building, and evolving the Android SDUI renderer — and the backend services (Kotlin, Golang, Protobuf) that feed it — to handle complex, real-time UI updates at scale. Lead architectural improvements and code reviews, ensuring the maintainability, visibility, and operational health of the renderer as more teams build on top of it. Partner with cross-functional disciplines (iOS and Web renderer engineers, product and design teams) to plan rollouts, align on plat

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are seeking a hands-on Engineering Manager to lead our Frontier AI Infrastructure team within Public Sector Engineering. This is a 50/50 role : you'll spend roughly half your time writing and reviewing code, and half your time leading, coaching, and growing a small team of engineers. Your team owns the model inference layer — enabling state-of-the-art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You'll lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and debug platform issues, and you'll partner upstream with Product to catch issues before they break, moving the team from "infra-only debugging" to proactive integration testing. You will: As a manager - 50/50 management and hands on coding experience. Lead, coach, and grow a team of engineers — own hiring, onboarding, performance, and career development. Set technical direction and quarterly priorities for the inference layer, and hold the team accountable to delivery on customer and contract commitments. Run the operational rhythm of the team: sprint planning, on-call rotation, incident review, and postmortems. Partner with Product, Program, and Deployed Engineering leadership to translate customer and mission requirements into roadmap. Represent the team in customer engagements and vendor escalations, including with government stakeholders. Design and implement secure, scalable backend systems for Public Sector customers, leveraging Scale's modern cloud-native AI infrastructure. Own services and systems alongside your team, define their long-term health goals, and improve the health of surrounding components. Stay in the code: review PRs, debug production issues, and take on meaningful technical wor

About the Role We are building a new class of clinical-grade AI agents powered by a foundational model that unifies 3D volumetric medical data and textual reasoning . These agents will assist with radiology workflows, treatment planning, case summarization, longitudinal patient analysis, and human-in-the-loop clinical decision support. In this role, you will design the agent layer that transforms a powerful multimodal foundation model into a safe, reliable, adaptive medical assistant capable of analyzing 3D scans, retrieving past cases, explaining findings, and coordinating multi-step reasoning chains. This position is ideal for researchers from multimodal/VLM/CLIP ecosystems who want to move up the stack into autonomous medical reasoning , multimodal alignment, and real-world clinical impact. What You Will Work On Architect LLM-driven medical agents capable of: Reading & interpreting 3D medical volumes (MRI, CT, PET). Answering radiology questions, generating report drafts, and performing differential reasoning. Retrieving similar prior cases using contrastive embeddings. Synthesizing multi-instance evidence across scans, labs, and notes. Executing multi-step “clinical workflows”—image → analysis → summary → recommendation. Integrate clinical agents with the 3D foundation model’s representations, enabling structured medical reasoningand contextual memory across longitudinal data. Develop evaluation frameworks for trustworthiness, interpretability, calibration, and clinical safety. Collaborate with clinicians and scientists to co-design tasks, datasets, and validation protocols. Benchmark models against open and proprietary datasets: MIMIC, CheXpert, MosMed, LiTS, BraTS, and India-specific clinical corpora. Publish findings at top-tier venues (MICCAI, NeurIPS, AAAI, EMNLP). Work with regulatory and product teams to translate research into medically viable systems. Why This Role Appeals to CLIP / VLM / Chitrarth / Patram Authors A rare opportunity to work at the

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Embedded Software team is looking for a Frontier UX Engineer to build the software that turns design intent into interfaces people can pick up and use. You will work closely with Design, taking ideas, use cases, and specifications from early prototype through a world class shipped product, pushing the UI experience to its limit. Much of the work has no precedent, requiring comfort with unclear requirements and problems that cross design and several software layers. We care a lot about how the product feels to use, and we want someone who shares that mindset. Responsibilities Turn design specifications, use cases, and rough ideas into shipping interfaces, from early prototype through production on real hardware Own execution: take a prototype the whole way to something that ships, with the quality bar held at each step Find where the design language outruns the platform, and push the UI software at every layer needed to close the distance Advise designers on what the system is actually capable of, early enough for it to change the design Shape the UI runtime and system architecture with requirements drawn from real designs rather than hypotheticals Own the end-to-end development of user experiences alongside design, firmware, and hardw

Company: tastytrade Role: Senior Linux Infrastructure Engineer Location: Chicago, IL — Hybrid About the Role We are looking for a senior Linux engineer who is equal parts operator and builder. You will own the systems layer of our production environment — from the metal to the configuration management code. This is a hands-on role: you will jump into incidents, tackle challenging engineering problems, design systems that scale, and evaluate new software and architectures. This is not a role where the abstractions hide the machine. You are expected to be curious about what is underneath and to be the person other engineers come to when a system is behaving in a way nobody can explain. What You'll Do Own Linux performance. Diagnose and tune systems under real production load: CPU scheduling and NUMA placement, memory and page cache behavior, disk and filesystem I/O, and network stack tuning. Lead troubleshooting on hard problems. Work incidents methodically — form a hypothesis, find the cheapest test that falsifies it, and narrow the search rather than changing five things at once. Write postmortems, organize follow-up tasks, and future-proof the environment so the same issue does not recur. Write and maintain configuration management code. Build infrastructure declaratively with Salt, Ansible, Chef, or Puppet, treating that code with the same standards as application code: reviewed, tested, and version-controlled. Run containerized workloads. Build, deploy, and operate services on Kubernetes or Nomad, including scheduling behavior, resource limits, health checking, and the failure modes that only appear under contention. Automate in Bash and Python. Replace manual runbooks with tooling and streamline repeatable work. Operate core network services. Troubleshoot TCP/IP with confidence and bring solid networking fundamentals. Manage DNS and DHCP as production ser