Ai Systems Engineer Jobs

MongoDB is helping define the next era of application development as organizations modernize legacy systems, build AI-native experiences, and power mission critical workloads across cloud, hybrid, and on-premises environments. From MongoDB Atlas, our AI ready developer data platform, to our industry leading server technology and enterprise software offerings, MongoDB provides a flexible and unified software stack that helps customers build faster, scale with confidence, and support a wide range of modern application needs. MongoDB’s standing in the market reflects that momentum: the company continues to be recognized as a leader in cloud database management while also serving organizations that require the performance, flexibility, and control of self-managed deployments. For candidates, that means the opportunity to join a company with strong market relevance, a builder-first culture, and a clear strategic focus on shaping the future of modern, intelligent applications wherever they run. We’re looking to speak to candidates based in Palo Alto, California for our hybrid working model. Life in MongoDB Technical Services As part of the Support organization, you will be directly interfacing with our largest customers and their most difficult problems. There will almost certainly be sweat. But don’t worry – you’ll have time to prepare before you take on your first escalation. The limits of your understanding will constantly be pushed, and you’ll be challenged to grow. Underlying it all is the fuel that drives our team: customer obsession. We keep mission-critical deployments online, recover from high-pressure incidents with grace and humility, become trusted advisors, and work so closely with our customers that they would swear we were part of their team. These are just a few of the things you can expect to do as a Technical Services Engineer: Become well-versed in core aspects of MongoDB Gain deeper expertise in specialized areas of the product Combine technical

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta Federal, Inc. is seeking a seasoned Classified Systems Architect to join our Technology, Data & Intelligence (TDI) Team. This team is tasked with building and maintaining a robust, compliant, and scalable "High Side" developer platform that empowers our product teams to deliver Okta’s world-class Identity capabilities to the U.S. Government’s most sensitive missions. As part of the TDI Team, this individual will serve as the technical authority for the design, development, and evolution of our development platform for US Classified environments. This position’s mandate is to define the architectural vision for our air-gapped infrastructure, select and validate hardened tooling (e.g., Big Bang, Iron Bank, etc), and bridge the gap between strict DoD compliance requirements and modern DevOps velocity. You will partner closely with stakeholders across TDI, Product Engineering, Vulnerability Management, and Security Compliance to ensure that every component of the system—from the Kubernetes substrate to the application layer—is implemented as planned, secure by design, and optimized for user experience. Strong preference will be given to those with a bias for action and the ability to solve complex "air gap" challenges outside the box. What you’ll be doing Act as the central point for defining and evolving the architecture of Okta Federal’s SIPR/JWICS environments, ensuring alignment with DoD reference designs while tailoring them to Okta’s specific pro

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. What you’ll do: Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas Use data driven methods and leverage the unique properties

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language

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 . The CX Intelligence team is part of Coinbase’s Enterprise Applications and Architecture org and builds the customer-facing and internal CX experiences that connect the Help Center, chatbots (CBCB), and agent workflows. The team owns the multi-agent platform that powers Coinbase chat, Help Center, and agent tooling, partnering closely with Conversation Design, CX, and engineering teams to deliver secure, compliant, and scalable AI-powered support. Our work helps customers get answers faster while enabling agents to resolve cases more effectively. We are hiring an IC4 Machine Learning Engineer to help evolve our conversational ecosystem by building a seamless hybrid vendor-internal chatbot experience. You will contribute to the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants. This role is ideal for someone who enjoys solving complex ML systems problems, building reliable handoff logic across LLM frameworks, and shipping AI-enabled products that are measurable and scalable. What you'll do: Build and improve the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Develop production-grade Python services that bridge advanced AI and ML capab

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 . EAA Integrations builds scalable automation that connects systems, streamlines business processes, and unifies data across the enterprise. We create integration assets and APIs that improve developer productivity and help teams integrate complex systems efficiently. As our Enterprise Integration team grows, we’re hiring a Workato Developer / Workato Architect with experience building and governing automation at scale. In this role, you will design Workato recipes, frameworks, and connectors while applying integration patterns and platform standards. You will partner with business units and engineering teams to translate requirements into reliable, scalable solutions and ensure integrations run smoothly in production. Reporting to the Manager of Engineering (Integrations), you will help drive automation strategy and strengthen Workato platform excellence across Coinbase. What you’ll do: Design, build, and maintain integrations across enterprise applications using Workato, custom connectors, and automation frameworks. Architect scalable automation solutions and solve complex integration challenges using patterns, governance, and best practices. Integrate Workato workflows with AI and LLM services to support decision-making, content generation, and data enrichment. Build frameworks for incorporating LLMs into business processes with secure and scalable usage. Partner wi

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is looking for an Engineering Manager from across multiple disciplines. We are growing our team with people who want to build, improve, and incorporate technologies that make the lives of our community more enriched. As an Engineering Manager at Lyft, you'll collaborate with other teams and orgs, product managers, designers, data scientists, analysts, and operations on technology that empowers us to iterate quickly, while focusing on delighting our passengers and drivers. The Rider organization is focused on building a seamless, best-in-class rideshare experience for riders. From the foundational functionality of requesting a ride to the tailored interactions with specific verticals like your flight, we sweat the small stuff to help make Lyft the best transportation solution. As an Engineering Manager on the Rider vertical team, you will act as a critical technical leader, taking holistic ownership of supporting current projects and delivering new products from 0 to 1. This includes developing complex systems, defining strategic roadmaps, driving cross-functional alignment, and ensuring engineering excellence to improve the rideshare experience. Responsibilities: Drive team execution, proactively resolve bottlenecks and make decisive trade-offs. Partner with cross-functional teams (Product, Design, Marketing, Science, and Analytics) to define the team's strategic direction. Translate high-level business goals into actionable projects. Own a team roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Maintain operational excellence through contributing to best practices for observability, reliability, and on-call processes. Ensure technical excellence through architecture reviews, tech debt management, and engineering guidance. Maintain team health

Role Description As a Principal Engineer at Dropbox, you will own company critical, loosely defined technical problems with multi year impact, operating at the intersection of technology, product, business strategy, and applied AI. You will define long term technical direction for customer facing experiences used by millions, identifying where AI meaningfully improves customer value and translating evolving business context and industry advances into durable, multi area strategies and roadmaps that shape how Dropbox builds, scales, and innovates, while remaining hands on in software development where it provides the greatest leverage. Your influence will span organizations, setting foundational architecture, driving execution standards, and aligning senior technical and product leaders across boundaries. You will lead the responsible introduction and adoption of AI across product capabilities and engineering workflows, bring clarity to the most complex decisions, institutionalize engineering excellence, and contribute directly through critical design, prototyping, and code reviews. In return, you will operate as a trusted technical partner to senior leadership, shape systems and platforms including AI powered foundations that define Dropbox’s future, and act as a company level technical strategist, advancing Dropbox’s mission to create a more enlightened way of working. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here . Responsibilities Own and drive technical outcomes across multiple teams and organizations, delivering company critical customer and business impact at scale. Define long term technical strategy and partner with senior Product and Engineering leaders as the technical owner for the most important company objectives. Tackle the most ambiguous and far reaching technical and product problems, shaping w

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are looking for a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and de

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing engineer, who will be responsible for driving technical initiatives related to manufacturing to ensure product success from concept to launch and through mass production with a specific focus on PCB and PCBa manufacturing and process. You’ll have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams,TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: In this role, you’ll be responsible for driving manufacturing and quality initiatives to ensure product success from concept to launch Lead the product design and the manufacturing process for next-gen AI hardware system development, you will have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams, TPMs and external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. Lead the team to establish NPI product manufacturing process, systems and quality controls, defining clear milestones and deliverables, drive internal process improvements across multiple terms and functions Provide hands-on product manufacturing analysis during desi

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are looking for an embedded engineer to help build firmware and associated modeling software for OpenAI’s in house AI accelerator. This role involves designing and developing drivers and functional models for a large array of HW components, writing high throughput and low latency firmware code, investigating bring-up and production issues. Responsibilities Design and implement drivers for hardware peripherals, including those related to AI chips. Design and implement functional software models to simulate SoC uncore logic and enable FW testing against the model Design and implement low-latency and high throughput embedded SW to manage HW resources. Work with adjacent software and hardware teams to implement requirements, debug issues and shape future generations of the hardware. Collaborate with vendors to integrate their technologies within our systems. Bring up and debug firmware/driver on new platforms. Come up with processes and debug issues raised in the field. Set up monitoring, integration testing and diagnostics tools. Qualifications 5+ years of experience working in embedded SW space. Ability to thrive in ambiguity and learn new technologies. Strong programming skills in C/C++ and/or Rust. Experience developing high throughput, low latency and multi-threaded code. Experience working with real time operating systems (RTOS). Experience developing hardware drivers and working with hardware Experience with HW/SW co-design Knowledge of common embedded pr

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for signal integrity (SI) system design engineers who have a deep expertise in the SI area, and hold strong system level design knowledge This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead system signal integrity (SI) design for AI supercomputer product in the data center application. Collaborate with chip, package, boards, rack and system engineers, design partners to drive system SI design and develop innovative interconnect and high-speed technologies Identify and evaluate new technologies and methodologies to improve signal and power integrity in product design, and contribute to the development of new products and technology by providing expertise in signal integrity Perform simulation and modeling to identify and troubleshoot signal integrity issues Lead system interconnect design, bring up and qualification As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings. You might thrive in this role if you: Have at least 10 years of industry experience, including experience design hardware system and SerDes testing for data center applications Have a strong bias toward action, and won’t take no for an answer. Have experience and good knowledge of system design experience in the SI areas, from chip, SerDes, board, rack level Have ex

About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role OpenAI is developing custom silicon to power the next generation of frontier AI models. We’re looking for experienced Design Verification (DV) Engineers to ensure functional correctness and robust design for our cutting-edge ML accelerators. You will play a key role in verifying complex hardware systems—ranging from individual IP blocks to subsystems and full SoC—working closely with architecture, RTL, software, and systems teams to deliver reliable silicon at scale. In this role you will: Own the verification of one or more of: custom IP blocks, subsystems (compute, interconnect, memory, etc.), or full-chip SoC-level functionality. Define verification plans based on architecture and microarchitecture specs. Develop constrained-random, directed, and system-level testbenches using SystemVerilog/UVM or equivalent methodologies. Build and maintain stimulus generators, checkers, monitors, and scoreboards to ensure high coverage and correctness. Drive bug triage, root cause analysis, and work closely with design teams on resolution. Contribute to regression infrastructure, coverage analysis, and closure for both block- and top-level environments. You might thrive in this role if you have: BS/MS in EE/CE/CS or equivalent with 3+ years of experience in hardware verification. Proven success verifying complex IP or SoC designs in industry-standard flows Proficient in SystemVerilog, UVM, and common simulation and debug tools (e.g., VCS, Questa, Verdi). Strong knowledge

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with