We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

We are seeking a highly skilled Senior Staff Software Engineer with deep technical expertise in Security and a passion for building secure, reliable, and scalable systems. This role focuses on technical leadership, architecture, and hands-on development to ensure the security and resilience of our core platforms.

You will drive the security, quality, and reliability of backend systems while influencing architecture decisions, mentoring engineers, and partnering with product teams on strategic initiatives.

What You Will Do

• Architect and implement secure, scalable backend systems using Java (Spring Boot) and AWS cloud-native services.
• Lead technical design reviews, enforce security best practices, and ensure system reliability and performance.
• Develop and integrate security features such as authentication, authorization, and identity management (SSO, OIDC, RBAC/ABAC, SCIM).
• Design and implement API security patterns and API authorization at scale for microservices and service mesh environments.
• Embed Generative AI capabilities (e.g., embeddings, RAG, LLM APIs) into product workflows securely and responsibly.
• Write and review code, unblock complex technical challenges, and make critical architectural decisions.
• Champion secure SDLC practices, cryptography standards, and compliance requirements.
• Collaborate with cross-functional teams to define technical roadmaps and deliver mission-critical systems at scale.

Minimum Qualifications

• Bachelor’s degree in Computer Science or related technical field.
• 8 years of professional software development and security engineering experience.
• Proven experience designing and developing large-scale distributed systems.
• Strong knowledge of security architecture

Preferred Qualifications

• Recent hands-on experience (last 3–4 years) building secure, distributed systems at scale, with strong exposure to AI/ML development and hosting in production environments.
• Experience with cloud platforms (AWS, Azure, GCP) for identity, ML infrastructure, and secure deployment.
• Familiarity with Generative AI integration and responsible implementation of LLM-based workflows.
• Exposure to data security principles, including encryption, secure data pipelines, and compliance frameworks.
• Ability to influence technical direction and mentor engineers in security best practices.
• Proven track record of delivering mission-critical, scalable systems in production at enterprise scale.
• Expertise in Java, Spring Boot, and AWS architecture/services (EKS, S3, Lambda, RDS, IAM, KMS).
• 7+ years of solid experience with fundamental algorithms, system design, and large distributed systems.
• Deep experience in cryptography and PKI systems, including certificate management and secure key lifecycle
• 7+ years of coding experience, specifically in Java.
• Strong knowledge of security architecture, authentication/authorization, and cryptographic principles.
• Hands-on experience in building large-scale serving and data infrastructure.
• Experience with service-oriented architecture and web application/services development
• Practical experience in utilizing AWS (Amazon Web Services).
• Experience in designing and constructing machine learning-based applications and systems.
• Experience in leading cross-team system design and execution.

Pay & Benefits   

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation. 

The base pay for this position ranges from $174,00/year to $299,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

General Description of All Benefits  

• Medical/Dental/Vision/Life, AD&D insurance  
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of the Paid Time Off (PTO) a year based on the tenure
• 12 Public Holidays
• Paid Parental leave
• Pre-tax commuter benefits
• MTV - [Free] Electric Car Charging Station 

General Description of Other Compensation

 “Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.  

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.
• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or gender (including pregnancy, gender identity, gender expression, sexual orientation, transgender status), national origin, age, disability, medical condition, HIV/AIDS or Hepatitis C status, marital status, military or veteran status, use of a trained dog guide or service animal, political activities, or affiliations, citizenship, or any other characteristic or class protected by the laws or regulations in the locations where we operate. If you need assistance and/or reasonable accommodation in the recruiting process due to a disability, please contact us at usrecruiting@coupang.com.

Job Requisition ID: R0067878

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users’ queries but efficiently resolves issues and provides valuable business insights. We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform. We’re evolving from a helpful support tool to a trusted pilot that anticipates, optimizes, and executes on behalf of our users.

What you’ll do

As a Senior Machine Learning Engineer on the Stripe Assistant team, you’ll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful. You’ll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data—so users can resolve issues quickly and confidently.

You’ll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows. You’ll establish rigorous evaluation and SLOs and deliver step‑change improvements in quality, latency, cost, and availability—paving the way for configurable levels of autonomy and, ultimately, a dependable operating layer over a merchant’s Stripe account.

Responsibilities

Our team operates fluidly and here are some problems you may tackle:

• Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence.
• Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale.
• Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard.
• Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc.
• Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability.
• Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years in AI/ML and backend engineering.
• Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc.
• Proficient in Python (Ruby is a plus); strong distributed systems fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.

Preferred qualifications

• Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements.
• Track record building ML platforms, especially those that enable multiple teams to collaborate together.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Join us to build a trustworthy, proactive AI operating layer for every Stripe merchant—advancing safety, reliability, and insight at global scale. If you’re ready to help take Stripe Assistant from copilot to full autopilot and shape how businesses connect with Stripe, we’d love to hear from you.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Before Stripe, every growing internet platform had a payments team. Today, every growing internet platform has an Identity team. Identity verification has become core economic infrastructure for online businesses — enabling them to digitally verify their users' identities for fraud prevention, regulatory compliance, and trust and safety purposes.

At Stripe, we're building something more ambitious than a verification product. Our vision is to build the world's most trusted store of verified identities — a single, global, reusable, risk-scored representation of every individual who interacts with Stripe and beyond. This Identity Store becomes a platform with compounding network effects: more verifications enrich the store; a richer store produces better fraud signals; better signals mean lower friction for trusted users; lower friction drives more adoption.

Our product today serves millions of verifications per month for customers like OpenAI, Shopify, and WhatNot, and powers identity verification across multiple internal Stripe products including Fraud, Link, Connect, and Crypto. The problems ahead — adversarial AI and deepfake defense, networked identity infrastructure, progressive verification platforms, and low friction KYC APIs — sit at the frontier of what's possible in identity engineering.

What you’ll do

As a Staff Engineer on the Identity team, you will own the technical direction of one of Stripe's most strategically important product areas. This is not a role defined by task execution — it's a role defined by technical judgment, architectural influence, and the ability to turn an ambitious vision into a reliable, scalable system.

Responsibilities

• Own technical strategy — Define the architecture for Identity's core systems (Identity Store, headless verification platform, fraud detection infrastructure), make build-vs-buy-vs-partner decisions, and surface technical risks before they become customer-facing failures
• Lead 0-1 platform development — Architect net-new systems including the Identity Store, Networked Identity platform, and advanced fraud detection pipeline (behavioral biometrics, deepfake discriminators, adversarial training). Drive the evolution from a hosted-UI product to a headless-API and embedded-components platform
• Drive cross-functional alignment — Be the primary technical voice in roadmap and resourcing discussions. Partner with ML, product, legal, and engineering leads across Risk, Fraud, Link, Connect, and Crypto to ensure Identity's abstractions serve the full breadth of Stripe's product surface
• Raise the technical bar — Set engineering standards across ML, backend, mobile, and front-end; lead design reviews; and mentor senior engineers on the judgment needed to operate a high-stakes, externally-facing product
• Operate with ownership — Be accountable for reliability, scalability, and security of the systems you design — including the observability and alerting that catch model drift and fraud pattern shifts before customers do

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role.
• Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g. building internal or external developer products). 
• Proven track record of delivering pragmatic solutions that accelerate business growth 
• Ability to adjust conversations from high-level discussions to detailed coding 
• Thrives on a high level of autonomy and responsibility 
• Clear and persuasive writing and in-person communication 
• Strong problem-solving skills, critical thinking, determination, and a growth mindset 
• Ability to work effectively with a diverse group of people, genuinely caring for each other and contributing to high level of psychological safety for all team members and partner
• Has experience in a range of software languages and frameworks. Examples of what we work with include:
• Languages: primarily Ruby and Typescript, but also Python, Scala, Java, Go, and SQL (Spark and Trino dialects)
• Frameworks: React, GraphQL Kafka, Protobuf, Airflow, Bazel, Temporal, 
• Others: Mongo, Splunk, Prometheus

Preferred qualifications

• Experience with identity verification, fraud detection, or trust and safety systems — especially systems with adversarial inputs at scale
• Familiarity with ML systems in production: model serving, training pipelines, observability, drift detection, and the feedback loops that keep models accurate under adversarial conditions
• Experience building platform products with multiple consumer types — internal platform teams and external developers — where API backward compatibility and abstraction quality are first-class concerns
• Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly
• Exposure to the technical stack we work with: primarily Ruby and TypeScript on the backend and web, Python for ML and data pipelines, with infrastructure spanning Kafka, Temporal, Protobuf, React, and distributed data stores
• Experience navigating ambiguity in a fast-moving organization — you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge

Why Stripe Identity

• The market is at an inflection point. The global identity verification market is growing at ~15% CAGR, from $12.5B in 2024 to $21.8B by 2028. Competitors have more features today — but none of them have Stripe's moat: payments signals, fraud network, consumer graph, and KYC data spanning the full financial ecosystem. We're building to win the next decade, not the last one.
• The problems are genuinely hard. Adversarial ML against deepfakes and face swaps. Distributed identity graph architecture with real-time freshness requirements. Progressive verification APIs that minimize friction without sacrificing fraud detection accuracy. These are unsolved problems — not just at Stripe, but in the industry.
• You'll work on systems that matter immediately. The verifications we run protect real users from real fraud. When our recall improves by 10 points, that's millions of dollars in prevented fraud losses for customers who rely on us. When our mobile SDK completion rate rises, thousands more legitimate users successfully onboard each month.
• The team is small enough that your judgment shapes the architecture. This isn't a role where you inherit decisions made five years ago. It's a role where the decisions you make in 2026 are the ones the team will build on through 2029.

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.

This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.

What You'll Do

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
• Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability 
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have a strong interest in LLM serving; prior inference or ML experience is not required 
• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With:

• LLM inference optimization, batching, and caching strategies
• Capacity-constrained scheduling or shared-resource test infrastructure
• Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
• Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
• Proficiency in Python or Rust

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About the role

We are seeking a Staff Software Engineer to build and operate the safety, oversight, and intervention mechanisms that protect Claude on third-party cloud service provider (CSP) platforms. As the engineer responsible for Safeguards on those surfaces, you will ensure that every request served through our CSP partners is monitored for misuse, enforced against policy, and compliant with the data residency and privacy commitments that enterprise CSP customers expect.

You will sit at the seam between the Safeguards organization and the Cloud Inference team: taking classifiers, detection signals, and enforcement policies developed by Safeguards and making them run reliably inside a CSP partner’s infrastructure at serving-path latency and scale. You will own the architecture that lets our safeguards operate within those constraints without gaps. You will build, deploy and operate the multi-layered defenses that catch unwanted model behavior in real time, the telemetry pipelines that give us situational awareness over CSP traffic, and the enforcement hooks that let us act quickly when something goes wrong. Your work will directly determine whether Anthropic can ship frontier models on CSP platforms at the same safety bar we hold ourselves to on our first-party API.

Responsibilities:

• Build, deploy and operate real-time safeguards infrastructure—classifiers, rate limits, enforcement actions, and intervention hooks—embedded directly in the third-party CSP inference serving path
• Design and maintain the data residency and privacy architecture for safeguards signals on CSP platforms, ensuring we can detect abuse and monitor model behavior while honoring regionalization boundaries and enterprise contractual commitments
• Develop telemetry, logging, and evaluation pipelines that give Safeguards, Policy, and T&S operational teams situational awareness over CSP traffic and close the visibility gap between third-party and first-party serving
• Dive into the CSP serving stack to identify the lowest-impact points to gather signals or introduce interventions without degrading latency, stability, or overall architecture
• Hold a high operational bar: own on-call, drive root-cause analyses and postmortems for safeguards incidents on CSP platforms, and build systems that reduce the human intervention required to keep Claude safe
• Work closely with Safeguards research, Policy & Enforcement, the Cloud Inference team, and CSP partner contacts to turn detection research and policy decisions into production enforcement that works inside a partner’s cloud.

You may be a good fit if you:

• Have a Bachelor’s degree in Computer Science, Software Engineering, or comparable experience
• Have 7+ years of experience in high-scale, high-reliability software development, ideally with exposure to trust & safety, anti-abuse, fraud, or integrity systems
• Are proficient in Python and comfortable working across the stack—from request-path services to data pipelines to internal tooling
• Think adversarially: you can see a system from a bad actor’s perspective, anticipate how they will respond to countermeasures, and design defenses in depth rather than single points of enforcement
• Have experience scaling infrastructure to accommodate rapid traffic growth while keeping latency and reliability within tight budgets
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Have strong communication skills and can explain complex technical and risk tradeoffs to non-technical stakeholders across Policy, Legal, and partner organizations
• Enjoy working in a fast-paced, early environment; comfortable with adapting priorities as driven by the rapidly evolving AI space

Strong candidates may also have experience with:

• Building trust and safety, anti-spam, fraud, or abuse detection and mitigation mechanisms for AI/ML systems, or the infrastructure to support these systems at scale
• Machine learning serving infrastructure (GPUs/TPUs, inference servers, load balancing) and the operational realities of running models in production
• Major cloud platform internals—IAM, Network/service perimeter controls, regional resource constraints, cloud-native logging/monitoring—or experience shipping software that runs inside a partner’s cloud rather than your own
• Data residency, privacy engineering, or compliance-constrained architectures, particularly where telemetry has to stay within regional or contractual boundaries
• Working closely with operational and human-review teams to build custom internal tooling, admin UX, and alerting
• Adversarial mindset: has shipped defenses against motivated attackers before, knows what it feels like when they adapt, and can sprint to close a gap before it becomes an incident
• Comfortable operating at the intersection of platform/infra engineering and trust & safety—neither a pure infra engineer nor a pure T&S engineer, but someone who can credibly do both
• Has shipped software that runs inside someone else’s infrastructure (partner cloud, embedded deployment, or similar) and knows how to get things done when you don’t control the whole stack
• Senior enough to own a cross-team seam independently, drive consensus across orgs, and make latency/safety tradeoff calls without escalation
• TypeScript or Rust, and agentic coding tools such as Claude Code

The Team + The Role

Pendo’s Customer Engineering team is the technical backbone of the pre- and post-sales customer motion. The team brings together work that has historically sat across Customer Success, Technical Account Management, and Solutions Engineering into one full-lifecycle technical owner. Customer Engineering helps customers connect technical execution to business outcomes and realize the value of their investment in Pendo.

As a Senior Customer Engineer, you own strategic and complex Enterprise accounts across acquisition, implementation, adoption, expansion, and escalation. You lead technical strategy for complex deployments, resolve ambiguous customer challenges, and partner closely with account teams to drive retention, expansion, and customer value. Your impact extends beyond your own accounts through playbooks, coaching, repeatable fixes, and workflow improvements that raise the capability of the broader Customer Engineering team.

This is a remote role supporting a West Coast territory. 

What this looks like day-to-day

• New customer acquisition and selling: Partner with Account Directors on pre-sales motions for new customer acquisition, product expansion, and expansion across lines of business. You identify customer pain, craft and deliver tailored demos, and lead technical evaluations through requirements gathering, success criteria, installation guidance, and hands-on workshops.
• Complex implementations and value realization: Lead onboarding for strategic customers, including planning, implementation, integrations, and training. You build customer-specific implementation playbooks, guide complex deployments with executive visibility, and ensure customers realize value during onboarding and over time.
• Adoption, expansion, and growth: Identify opportunities to expand adoption across underutilized features, untapped products, and new lines of business. When adoption stalls, you diagnose root causes, design a path forward, and connect technical work to measurable business outcomes.
• Technical escalation: Serve as an escalation point for complex technical challenges raised by other Customer Engineers. You resolve ambiguous problems with multiple variables and tradeoffs, involving Product or Engineering only when truly needed.
• Team capability building: Build playbooks, document repeatable fixes, coach peers, and improve how Customer Engineering work gets done across the team. You use AI tools to accelerate content creation, surface patterns across accounts, and share practical workflow findings with the broader team.
• Early account impact: Assess account health, risks, stakeholder relationships, and the highest-priority problems to solve within your portfolio. You establish trust with Account Directors and customer stakeholders, then independently lead complex customer interactions that move accounts forward.
• Quarterly business outcomes: Drive measurable improvement in customer health, retention, expansion, and technical resolution across strategic accounts. You contribute reusable frameworks, playbooks, or processes that other Customer Engineers use and become a trusted advisor to Account Directors on account health and technical strategy.

Who You Are

Beyond the qualifications, we hire through a specific lens. These aren't buzzwords; they're the things we'll actually look for in how you talk about your work.

You're a builder, not a maintainer.

You're most energized when there isn't a clear path yet, and you get to define it. You don't wait for direction; you identify gaps, shape solutions, and drive them forward. At Pendo, great Senior Customer Engineers don't just follow instructions; they operate as strategic advisors, influencing decisions, guiding stakeholders, and elevating how we work.

You're AI-curious - genuinely.

You're not using AI tools occasionally. You're rewiring how you work around them. You're faster, sharper, and more prolific because of it, and you bring that energy to everything — how you approach your work, how you prep, how you communicate, how you think. We want someone who sees AI as a multiplier, not a shortcut.

Must-haves

• 5 to 8 years of experience in a customer-facing technical role such as Sales Engineering, Solutions Engineering, Technical Account Management, Customer Engineering, implementation, professional services, or solutions architecture.
• Deep hands-on experience with web technologies including HTML, CSS, JavaScript, and REST APIs, with the ability to architect and troubleshoot complex front-end implementations.
• Proven experience managing strategic Enterprise accounts with executive-level stakeholders, competing priorities, and complex technical or business requirements.
• Demonstrated ability to solve ambiguous problems involving multiple variables, constraints, and tradeoffs.
• Experience connecting technical execution to business outcomes such as retention, expansion, ROI, and value realization.
• Hands-on use of AI tools for account research, content creation, or workflow automation, with demonstrated integration into day-to-day work rather than light experimentation.
• Experience mentoring or coaching more junior technical team members.

Nice-to-haves

• Experience with Pendo, digital adoption platforms, product analytics, or in-app experience tooling in an enterprise environment.
• Hands-on experience with mobile app development, including Swift, Android, or React Native.
• Familiarity with data architecture, AI or machine learning concepts, or advanced analytics instrumentation.
• Track record of building reusable frameworks, playbooks, or processes that were adopted by a broader team.

About Pendo

Pendo was founded in 2013 by former product managers, who combined their heads and hearts to build something they wanted but never had as product managers: a simple way to understand and attack what truly drives product success. Our mission is to improve society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech.

Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus.

Location: Remote

Compensation: The expected On-Target Earnings (OTE) range for this role is $193,393 - $241,742, with a 70/30 base-to-variable compensation split.

Benefits: Pendo offers highly competitive United States benefits, including employer-heavy coverage with $0 premium options, strong 401(k) match, equity, and flexible time off.

EEOC: We are an equal opportunity employer and believe having diverse teams where everyone brings their whole self to Pendo is key to our success. We welcome all people of different backgrounds, experiences, abilities and perspectives.

Accessibility: Pendo is committed to working with, and providing access and reasonable accommodation to, applicants with mental and/or physical disabilities. If you think you may require an accommodation for any part of the recruitment process, please send a request to: accommodation@pendo.io. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.

We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What You’ll do:

• Embedded Customer Engineering: Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.
• Build Scalable Assets & Tooling: Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across DigitalOcean.
• Develop AI "Starter Kits": Create pre-built GenAI agents, solution templates, and notebooks (e.g., LangGraph, CrewAI) tailored to popular and advanced business needs.
• Drive the Product Roadmap: Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.
• New Tech Validation: Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on DigitalOcean.
• Partner & GTM Enablement: Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.
• Market Leadership: Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

• Customer Adoption: Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.
• Asset & Tooling Delivery: Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the crossfunctional teams and customers.
• Field Enablement & Scale: Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.
• Product Influence: Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You’ll Add to DigitalOcean:

• AI/ML Architecture & Domain Expertise: Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Distributed Systems & Infrastructure Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
• High-Performance Inference & Hardware Optimization: Hands-on experience with distributed inference serving frameworks (e.g., llm-d, NVIDIA Dynamo, or Ray Serve). You understand GPU-level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
• Software Engineering Foundation: Strong production coding skills in Python or Go with the ability to build high-quality tools, automation, and internal assets.
• Data-Driven Performance Insight: Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
• Consultative Execution: Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high-stakes technical migrations.

Preferred

• Experience with emerging AI orchestration frameworks like LangGraph, CrewAI, or LlamaIndex.
• A background in technical consulting or "Forward Deployed" roles at high-growth AI or infrastructure companies.
• Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
• Active contributor to open-source AI projects or technical communities.

Compensation Range: 

• $195,000 - $239,000

*This is a hybrid role

JR: 2026-7748

#LI-Hybrid

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We're searching for a Staff Security Engineer to join our Enterprise Security Engineering team, reporting to the Technical Lead Manager of Security Engineering.

Aurora is scaling its autonomous trucking operations, and the security foundations protecting our employees, devices, internal systems, and data need to scale with us. We're looking for a deeply technical enterprise security engineer who is as comfortable in a code editor as in a security console — you build the systems that make Aurora's security operations possible. This is a role for someone who can architect robust enterprise security solutions, write the code to implement them, and partner across Engineering and IT to make sure security is embedded from the start, not bolted on at the end.

This is not a security operations-only role. It sits squarely in enterprise security engineering, where the work is designing, building, and owning the platforms, integrations, and automation that power Aurora's internal security posture at scale.

In this role you will

• Own the architecture and implementation of Aurora's enterprise security controls — designing the systems and integrations that protect Aurora's endpoints, identities, internal infrastructure, and SaaS environment.
• Design and build Aurora's security telemetry and detection infrastructure, including log pipelines, SIEM integrations, and alerting frameworks — in partnership with the Security Operations Engineer who owns ongoing tuning and rule development.
• Define and enforce enterprise security standards, conducting architecture and design reviews to ensure alignment with Aurora's security posture and risk tolerance.
• Partner with IT, Infrastructure, and Engineering teams to embed security requirements early — shifting left on corporate IT initiatives before they become technical debt.
• Build automation and tooling that extends the capabilities of Aurora's security platforms, reduces manual operational burden, and scales the team's impact.
• Serve as the escalation point for enterprise security incidents requiring engineering-level investigation or remediation, and participate in the team's on-call rotation.
• Translate security strategy into concrete, executable engineering projects with clear milestones and measurable outcomes.

Required qualifications

• 12+ years of hands-on experience in enterprise security engineering or corporate information security — specifically securing employee-facing systems, endpoints, identities, and internal infrastructure (not product or application security).
• Proficiency in at least one programming language, used in a security context — writing production-quality automation, integrations, or internal tooling (the team primarily uses Go; Python is also common).
• Experience architecting and integrating enterprise security platforms — designing API integrations, automating workflows, and building tooling that extends platform capabilities across domains such as EDR/XDR, MDM, IAM/IGA, DLP, SaaS security, cloud security, or PKI.
• Experience designing and building security telemetry pipelines and detection infrastructure — log ingestion, normalization, SIEM integration, and alerting architecture.
• Experience leading cross-functional security engineering projects — defining scope, driving execution, and aligning stakeholders across Engineering and IT.
• Track record of conducting security architecture reviews and translating findings into actionable, risk-prioritized remediation plans.
• Experience evaluating security posture and identifying systemic gaps, with a bias toward building durable solutions rather than one-off fixes.

Desirable qualifications

• Experience with Zero Trust architecture and identity-centric security models (BeyondCorp-style or similar).
• Familiarity with NIST CSF, MITRE ATT&CK, and CIS Benchmarks as engineering inputs — used to inform what to build and how to validate it, not just as compliance checkboxes.
• Hands-on AWS security experience (SCPs, GuardDuty, Security Hub, IAM, etc.) and familiarity with integrating cloud security signals into a corporate security platform.
• Experience with applied cryptography and PKI in a production enterprise environment — certificate lifecycle management, CA design, or secrets management.
• Familiarity with securing AI/ML platforms or applications built on LLMs, RAG pipelines, or MCP-based architectures.
• Security certifications such as CISSP, GCED, GREM, or similar (valued but not required).

The base salary range for this position is $189,000 - $274,000 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#Mid-Senior 

We want people who are passionate about troubleshooting complex problems with systems, networking and storage at scale.

We are looking for a seasoned system administrator to help us keep the cloud running smoothly. Reporting to the manager of Cloud Operations, the GPU Operations Engineer monitors and provides first-response to all cloud health issues that impact, or could potentially impact, customer experience - internal or external. You will interface with teams across the organization to research and troubleshoot issues from single droplets to cloud-wide disturbances. Our workweek spans five days, and that may involve working on weekends.

What You'll Be Doing: 

• Ensuring maximum uptime for our global infrastructure
• Automating processes and building tools to improve operational efficiency
• Coordinating operational work across teams to improve the platform with minimal impact

What You'll Add to DigitalOcean:

• Solid experience with Linux operating systems or Networking and day to day upkeep
• Familiarity with virtualization technologies and troubleshooting virtual machine instances
• Familiarity with containerization technologies and troubleshooting containers
• Familiarity with IPv4 Networking and troubleshooting (CCNA equivalent)
• Basic storage concepts and technologies
• Experience with monitoring systems and incident management
• Experience scripting in one or more of the following languages: Bash, Python, or Go
• Experience with GPU hardware or AI/ML, and Kubernetes
• A passion for good documentation and open communication
• Proven ability to learn!

Compensation Range: 

• $107,000 - $134,000

*This is a hybrid role

JR: 2026-7423

#LI-Hybrid

We are seeking a highly technical Security Engineer to join our Product Security team. This role is integral to ensuring the security and integrity of our products and services. You will conduct in-depth code reviews, implement security best practices, and influence the overall security strategy. Your expertise in TypeScript, Python, AWS, CI/CD, SAST, DAST, and terraform orchestration will be crucial in identifying and mitigating potential security vulnerabilities. You will also structure complex problems, diagnose root causes independently, and clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.

You will:

• Leverage broad product security expertise to build and maintain software tooling that secures every layer of the modern AI/ML software ecosystem.
• Conduct in-depth code reviews to identify and remediate security vulnerabilities.
• Evaluate and enhance the security of our product offerings, through RFC and service review.
• Implement and maintain CI/CD pipelines with a strong focus on security.
• Perform Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to identify vulnerabilities in production code.
• Utilize terraform orchestration to ensure secure and efficient infrastructure management.
• Guide engineering teams to build robust long-term solutions that consider security and privacy. 
• Clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.
• Influence the security strategy and direction of the team, advocating for best practices and continuous improvement.

Ideally, you’d have:

• Demonstrated ability to drive multi-month security initiatives independently, from problem definition through execution, without requiring significant direction.
• Proven experience as a Security Engineer with a focus on product security.
• Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes.
• Strong understanding of modern Javascript application design.
• Production experience operating and securing AWS infrastructure at scale.
• Hands-on experience with SAST and DAST tools and methodologies.
• Familiarity with terraform orchestration for infrastructure management.
• You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input.
• Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders.
• Demonstrated ability to influence security strategies and drive improvements within a team.
• Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus.

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

• Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
• Design and implement scheduling primitives to optimize the lifecycle of training jobs.
• Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
• Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
• Work closely with Finance and Procurement teams to drive our capacity planning process.
• Participate in our team’s on call process to ensure the availability of our services.
• Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

• 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
• Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
• Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
• Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
• Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
• Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
• Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
• Experience with PyTorch
• Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

About the General Agents Team

The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers.

About the Role

As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

You will:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideally you’d have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves:

• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality.

Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation.

If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

You will:

• Build, profile and optimize our training and inference framework
• Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
• Research and integrate state-of-the-art technologies to optimize our ML system

Ideally you’d have:

• Strong excitement about system optimization
• Experience with multi-node LLM training and inference
• Experience with developing large-scale distributed ML systems
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. 
• Strong written and verbal communication skills and the ability to operate in a cross functional team environment

Nice to haves:

• Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions 
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
• Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

About the Role

We’re looking for a Senior Engineer to help build the next-generation inference platform that supports embedding models used for semantic search, retrieval, and AI-native experiences in MongoDB Atlas.

You’ll join the broader Search and AI Platform organization and collaborate with ML researchers and engineers from our Voyage.ai acquisition. Together, we’re building infrastructure for real-time, low-latency, and high-scale inference — fully integrated with Atlas and designed for developer-first experiences.

As a Senior Engineer, you'll focus on building core systems and services that power model inference at scale. You'll own key components of the infrastructure, work across teams to ensure tight integration with Atlas, and contribute to a platform designed for reliability, performance, and ease of use.

We're looking to speak with candidates in Palo Alto for our hybrid working model.

What You’ll Do

• Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
• Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases
• Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
• Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment
• Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
• Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

Who You Are

• 5+ years of experience building backend or infrastructure systems at scale
• Strong software engineering skills in languages such as Go, Rust, Python, or C++, with an emphasis on performance and reliability
• Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
• Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
• Knowledge of vector search systems (e.g., Faiss, HNSW, ScaNN) is a plus
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
• Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

Nice to Have

• Experience integrating infrastructure with production ML workloads
• Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
• Contributions to open-source infrastructure for ML serving or search

Why Join Us

• Be part of building the AI foundation of the world’s most popular developer data platform
• Collaborate with ML researchers from Voyage.ai to bring novel ideas into scalable systems
• Tackle challenging problems in inference, observability, and distributed infrastructure
• Work in a culture that emphasizes mentorship, ownership, and technical excellence

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 4263317053

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale.

Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.

What You'll Do

• Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
• Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps
• Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
• Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Are curious about LLM serving; prior inference or ML experience is not required
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With

• Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
• Have experience working with external partners to align goals and deliver impact
• Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
• Solid understanding of multi-region deployments, geographic routing, and global traffic management
• Proficiency in Python or Rust

What We're Looking For

Lightning AI is seeking a Senior Storage Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will focus on building and operating the storage systems that power large-scale AI/ML training, inference, and HPC workloads. You will work at the intersection of software, hardware, and operations—developing automation, improving reliability, and scaling distributed storage systems across our bare-metal infrastructure.

You will help own the data plane of our storage infrastructure, supporting high-throughput, low-latency data access for some of the most demanding AI workloads. You’ll play a key role in managing and evolving our storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Storage Systems & Infrastructure

• Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
• Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
• Troubleshoot complex storage and data path issues across hardware and software layers
• Optimize storage performance to support high-throughput, low-latency AI training and inference workloads

Automation & Tooling

• Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
• Develop Python-based tools and workflows to reduce manual operational overhead
• Improve lifecycle management of storage clusters, from deployment through maintenance and scaling

Systems & Operations

• Manage and operate Linux-based systems in production, including bare-metal environments
• Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
• Support capacity planning, utilization tracking, and forecasting for storage systems
• Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability

Cross-Functional Collaboration

• Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
• Contribute to design discussions around new infrastructure deployments and scaling strategies
• Help define best practices for operating storage systems in high-performance computing environments

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Hands-on experience operating distributed storage systems (e.g., VAST, Ceph, or similar)
• Strong Linux systems experience in production environments
• Proficiency in Python or similar scripting/programming languages for automation
• Experience working with bare-metal infrastructure and hardware-oriented systems
• Ability to debug complex issues across system boundaries (storage, OS, hardware, networking)
• Experience with storage networking protocols (e.g., NFS or similar)
• Experience with capacity planning, monitoring, and performance tuning

Ideal Experience

• Experience with VAST storage systems in production environments
• Experience operating S3-compatible object storage at scale
• Data center operations experience, including working with physical hardware
• Familiarity with AI/ML or HPC workloads and their storage requirements
• Background in high-performance or low-latency distributed systems
• Familiarity with high-performance data transfer technologies (e.g., RDMA, GPU Direct Storage)
• Experience supporting GPU-based workloads or large-scale compute clusters

Compensation

What We're Looking For

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.

You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Systems, Image & Validation Infrastructure

• Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
• Run and maintain test clusters used for system validation, diagnostics, and bring-up
• Validate firmware, drivers, and OS images across compute and GPU-enabled systems
• Support hardware qualification efforts for next-generation platforms

GPU Diagnostics & Performance

• Own GPU diagnostics and validation workflows across large-scale infrastructure
• Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
• Analyze system and GPU performance using tools such as NVIDIA DCGM
• Identify failure patterns and drive improvements in system stability and validation coverage

Automation & Tooling

• Build and maintain automation for provisioning, validation, and system bring-up
• Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
• Improve the reliability, repeatability, and scalability of image pipelines and validation systems

Systems & Operations

• Manage and operate Linux-based systems in production and validation environments
• Manage virtualization technology
• Support bare-metal provisioning workflows, including PXE and image-based systems
• Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging

Cross-Functional Collaboration

• Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
• Collaborate with platform and ML teams to ensure systems meet workload requirements
• Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Strong Linux systems experience in production environments
• Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
• Familiarity with bare-metal provisioning and system bring-up workflows
• Proficiency in Python or similar scripting/programming languages for automation
• Ability to debug complex issues across hardware, OS, GPUs, and system software

Ideal Experience

• Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
• Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
• Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
• Data center operations experience, including working with physical hardware
• Experience supporting AI/ML or HPC workloads at scale
• Experience with GPU validation frameworks or large-scale hardware qualification processes

Compensation

What We're Looking For

We’re looking for a Fullstack Engineer to help develop and scale the Lightning AI platform across the frontend, CLI, APIs, and core backend systems. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in React and either Python or Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Proficiency in React and either Go (Golang) or Python, with a preference for Go
• Strong understanding of software engineering principles and lifecycle
• Hands-on experience as a Fullstack Engineer in a SaaS technology company
• Proven ability to take ownership of key features and drive end-to-end development
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
• Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
• Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
• Proven ability to take ownership of key features and drive end-to-end development
• Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
• Hands-on experience as a backend or product engineer in a SaaS technology company
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

About the Role
We are seeking an experienced research engineer to join our team. As a critical member of our interdisciplinary group, you will collaborate closely with AI scientists, engineers, and drug discovery experts to develop and deploy AI models that accelerate the identification and development of novel therapeutics. This role offers the opportunity to apply cutting-edge AI techniques in production settings to address pressing challenges in healthcare and contribute to improving human health globally.

We are particularly interested in candidates who have demonstrated experience building and delivering machine learning systems in industry environments, where rigor, scalability, and cross-functional collaboration are essential. The ideal candidate has experience translating research ideas into robust, production-ready solutions that drive measurable impact.

The role is open to the following locations: San Francisco Bay Area, Seattle

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related fields; advanced degree preferred
• Minimum of five years of industry experience in AI, machine learning, or related roles, with a track record of implementing, scaling, and deploying AI models in production environments.
• Expertise with modern deep learning toolchains and experience with large scale model training.
• Strong understanding of deep learning fundamentals.
• Excellent problem-solving skills, with a keen eye for detail and a passion for tackling complex challenges in the life sciences.
• Effective communication and collaboration abilities, with the capacity to work effectively in a fast-paced, multidisciplinary team environment.
• Publication track record at conferences such as NeurIPS, ICML, or ICLR is a plus, though demonstrated industry impact is prioritized
• If you are a motivated individual with a passion for applying AI to advance drug discovery and improve human health, we encourage you to apply!

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role:

We are looking for a Staff Software Engineer to join our Ads Data Warehouse team, which builds and evolves the core data infrastructure that powers all data-driven products and analytics across the company.

The Data Warehouse team is responsible for foundational systems such as data lineage, data catalog, access control, and compliance frameworks—enabling teams to securely and efficiently leverage data for decision-making, analytics, ML modeling, and Ads optimization.

As a Staff Engineer, you will define the technical vision and strategy for the Ads Data Warehouse, ensuring that our infrastructure scales to meet the growing complexity of our Ads ecosystem. You will lead architectural design, drive cross-team initiatives, and mentor engineers across teams. Your work will establish the foundation for reliable, compliant, and discoverable data across the entire company.

Responsibilities:

• Define and drive the technical roadmap and architecture, aligning the direction with product, analytics, ML, and infrastructure needs.
• Lead the design and evolution of core data systems, including data lineage, metadata management, and data catalog systems.
• Partner with cross-functional leaders to establish data governance, access control, and compliance frameworks that ensure data integrity and regulatory alignment.
• Build and scale high-reliability systems that power both real-time and batch data workflows across Ads and analytics use cases.
• Influence engineering culture by defining best practices for data modeling, observability, and developer experience.
• Drive cross-org initiatives to improve data quality, discoverability, and system adoption.
• Mentor senior engineers and help develop technical leadership across the data and infrastructure organization.
• Act as a trusted technical advisor to product and engineering leadership on strategy and scaling challenges.

Qualifications:

• Bachelor’s degree or higher in Computer Science, Engineering, or a related technical field.
• 8+ years of experience in software engineering, with a strong focus on data infrastructure, platform systems, or distributed architectures.
• Proven experience designing and scaling large-scale data platforms or data-intensive systems.
• Strong proficiency in Golang, Python, or Java.
• Deep understanding of distributed systems, metadata management, and data modeling principles.
• Hands-on experience with cloud data platforms (e.g., GCP, AWS, Azure) and data orchestration frameworks (e.g., Airflow, Beam, Dataflow, Kafka).
• Demonstrated ability to define and lead complex technical initiatives that span multiple teams or domains.
• Excellent communication skills, with the ability to influence and align stakeholders across engineering, product, and compliance.

Preferred Qualifications:

• Experience leading the design and development of data governance systems at scale, such as data catalog, data lineage, and/or data asset management.
• Expertise in data governance, access control, and privacy compliance frameworks (e.g., GDPR, CCPA).
• Deep understanding of metadata-driven architectures, data quality frameworks, and observability systems.
• Proven ability to set long-term technical direction, guide multiple teams through architectural transitions, and drive platform adoption.
• Recognized for technical mentorship, thought leadership, and fostering a culture of excellence in data infrastructure engineering.

About the Role

The Ads Applied Data team builds and scales the foundational data infrastructure that powers Moloco’s advertising platform. As a Senior Software Engineer, you will design, develop, and optimize distributed data systems for real-time and batch processing, ensuring reliable and low-latency delivery of data across the ads ecosystem. You’ll work closely with Product, ML, and Data Science teams to enable feature engineering, identity resolution, and advanced user signal enrichment across online and offline pipelines.

Responsibilities

• Design and build large-scale distributed systems for data ingestion (Petabyte-scale), transformation, and serving.
• Partner with ML and Serving teams to support feature engineering workflows, connecting offline data to serving systems.
• Contribute to the evolution of Feature Infra / Feature Store, ensuring scalability, discoverability, and consistency of feature data.
• Collaborate on Identity Graph construction to unify user and device identifiers for more effective signal enrichment and targeting.
• Improve system observability, resilience, and performance in high-throughput, low-latency environments.
• Mentor engineers and help define best practices for data and backend engineering.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, or equivalent technical field.
• 5+ years of software engineering experience with one or more modern languages (Java, Kotlin, Go, C++, C#, or Python).
• Proven experience designing and building large-scale distributed systems and backend services.
• Hands-on experience with data processing frameworks such as Apache Beam, Dataflow, or Spark, and orchestration tools like Airflow.
• Strong understanding of cloud infrastructure (GCP, AWS, or Azure) and data storage technologies (BigQuery, Bigtable, Redis, GCS, Kafka, Pub/Sub).
• Demonstrated experience delivering impactful projects through collaboration with cross-functional teams (Product, ML, Data Science).

Preferred Qualifications

• Experience with Feature Infra / Feature Store architecture and operations.
• Experience in Identity Graph design and construction to enhance user signal quality.
• Deep familiarity with AdTech or Machine Learning infrastructure domains.
• Experience working with Petabyte-scale data and high-availability systems.

About the Team:

The Ads Platform, Experiment team owns Moloco's company-wide experimentation infrastructure. We build the systems that help teams roll out changes safely, measure impact rigorously, and make better product and business decisions with confidence.

Our scope spans experiment lifecycle management, dynamic configuration and feature flag delivery, and the data pipelines and statistical tooling that power experiment analysis. We work at the intersection of backend infrastructure, data systems, and internal product development, partnering closely with engineers, data scientists, and statisticians.

About the Role:

As a Senior Software Engineer on the Experiment Platform team, you will lead the design and evolution of high-leverage systems that shape how Moloco runs experiments across products. You will own important technical areas end-to-end, drive sound engineering decisions in ambiguous problem spaces, and build platforms that improve the speed, safety, and trustworthiness of experimentation company-wide.

This role is well-suited for engineers who combine strong execution with technical judgment, enjoy working across backend and data system boundaries, and want to raise the quality bar for an internal platform used by many teams.

Responsibilities:

• Lead the design and implementation of major components across experiment management services, configuration delivery systems, and analysis pipelines.  
• Own technical decisions for platform areas that require balancing correctness, reliability, performance, and ease of adoption.  
• Improve the trustworthiness of experimentation by strengthening system design, observability, data quality, and operational standards.  
• Partner closely with engineers, data scientists, statisticians, and stakeholders to turn ambiguous requirements into scalable platform capabilities.  
• Mentor other engineers through design discussions, code reviews, and pragmatic technical leadership.

Minimum Qualifications:

• 5+ years of professional software engineering experience in a production environment.
• Strong hands-on experience in backend systems, data infrastructure, distributed systems, or other relevant platform areas.
• Proven ability to independently drive technical projects from problem definition through production rollout in ambiguous problem spaces.
• Strong engineering judgment in system design, operational reliability, maintainability, and cross-functional execution.
• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.

Preferred Qualifications:

• Experience designing and implementing experimentation platforms, A/B testing systems, feature flagging systems, or dynamic configuration platforms.
• Experience owning platform or infrastructure systems used by multiple engineering teams.
• Experience working with analytical data systems, metrics pipelines, or data quality and correctness challenges.
• Familiarity with advertising, mobile product ecosystems, or performance-driven product environments.

The Impact You’ll Be Contributing to Moloco:

As a Senior Machine Learning Engineer on Moloco’s Ads Quality team, you’ll design and scale machine learning systems that directly improve ad relevance, ranking, and optimization. Your work will have a measurable impact on advertiser performance, revenue efficiency, and the overall user experience across Moloco’s ad platform.

The Opportunity:

• Design, build, and deploy large-scale ML systems for ad ranking, click-through prediction, and conversion optimization
• Develop and operate production pipelines that process hundreds of millions of ad requests per day with low-latency requirements
• Collaborate directly with customers and partners in Mandarin to understand business goals and deliver data-driven ML solutions
• Apply systematic, reproducible approaches to model training, evaluation, and continuous improvement
• Partner with the Machine Learning Infrastructure and Data teams to improve tooling, deployment pipelines, and training efficiency
• Lead design and code reviews to promote technical excellence and standardize ML practices across Ads teams
• Diagnose model performance, identify optimization opportunities, and execute experiments that drive measurable results
• Mentor engineers on best practices for ML experimentation, productionization, and scaling
• Work cross-functionally with product, infrastructure, and business teams to align technical innovations with product goals

How Do I Know if the Role is Right For Me?

• You have 7+ years of experience building and deploying ML systems at scale, ideally in AdTech, recommender systems, or search/ranking domains
• You’ve shipped models that directly improved key product or business metrics such as CTR, CVR, or ROI
• You’re fluent in Mandarin Chinese and skilled at collaborating with customers or partners in technical discussions
• You have strong software engineering fundamentals: data structures, algorithms, and system design and proficiency in Python (C++ or Java a plus)
• You’re experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• You’ve worked with distributed data and compute systems like Apache Beam, Dataflow, or Flume
• You understand how to build robust ML pipelines including data versioning, feature engineering, retraining, and model monitoring in production
• You have experience optimizing inference performance on GPUs, TPUs, or similar hardware accelerators
• You thrive in fast-moving, ambiguous environments and can translate complex technical work into measurable business outcomes
• You value collaboration, accountability, and building systems that scale across teams and markets

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems. 

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

• Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
• Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

• Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work: 

• Your ethos is ownership
• You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.
• You demonstrate strong judgment under uncertainty. 
• You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.
• You lead through clarity and active listening. 
• You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions. 
• You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope. 
• You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.
• You fall in love with the problem, not the solution
• You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem. 
• When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook. 
• You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

The Impact You’ll Be Contributing to Moloco: 

The Customer Engineering (CE) team at Moloco partners with the Business Development (BD) and Product/Engineering teams to be the trusted technical advisors for Moloco’s clients. You will help the retail media platform owners to successfully build an in-house advertisement business for clients using the Moloco Commerce Media (“MCM”), a machine learning-powered AdTech solution. 

Within the MCM org, the Customer Engineering team (CE) is responsible for driving the successful adoption of Moloco Commerce Media, serving as GTM champions and technical experts. The CE team will drive the successful adoption of our products by advising clients on the best technical implementation and delivering training, architecture design consultations, and best practices. The CE team identifies gaps in the product, develops technical solutions, and communicates feature requests to product, engineering, and other cross-functional partners to shape product direction.

The Opportunity: 

• Be the trusted technical advisor for clients by offering guidance on platform integration, optimization, and troubleshooting.
• Understand clients' business objectives and challenges to provide tailored technical solutions and recommendations.
• Collaborate with BD teams to support pre-sales activities, including product demonstrations, technical consultations, and solution design.
• Lead technical implementation projects, including platform setup, configuration, and customization, to meet clients' requirements and deadlines.
• Conduct training sessions and workshops to educate clients on best practices, new features, and industry trends.
• Proactively identify opportunities for process improvement, feature enhancements, and product innovation based on client feedback and market insights.
• Stay abreast of industry developments, emerging technologies, and competitive landscape to maintain a deep understanding of the AdTech ecosystem.

How Do I Know if the Role is Right For Me? 

• 8+ years of professional experience within cloud, software, or machine learning domain areas like software engineering, systems engineering, machine learning, cloud infrastructure architecture, networking, security, data and analytics. 
• 5+ years in technical field roles – like Solutions Architect, Customer Solutions Engineer or Professional Services Consultant – in the retail or the AdTech industry.
• 3+ years of hands-on implementation, architecture design, or consulting experience in the application or the cloud infrastructure. 
• Strong technical and problem-solving skills, the ability to understand and troubleshoot systems and application flows, dive deep into complex problems & find their root cause.
• Experience in a technical role within the AdTech industry, preferably with hands-on experience in ad serving platforms, programmatic advertising, or related technologies.
• Comfortable communicating technical concepts to both technical and non-technical audiences.
• Demonstrated experience to autonomously identify goals and effectively deliver the goals along with the cross-functional internal and external stakeholders.

ABOUT THE TEAM

Anduril’s Tactical Recon & Strike (TRS) is a division with two missions: 1) build highly capable autonomous drones, and 2) build solid rocket motors at scale. We transform products like Ghost, Anvil, Bolt, and Altius from early concepts into fully operational capabilities by partnering closely with specialist engineering, operations, and production teams. Through our Anduril Rocket Motor Systems (RMS) team, we design and manufacture solid rocket motors using advanced materials, proprietary formulations, and high-volume production methods—delivering safe, reliable propulsion systems that support a wide range of mission requirements. TRS hires software engineers & hardware engineers, who are excited to build across a diverse and powerful portfolio—from autonomous aerial systems to high-performance solid rocket motors. Our teams contribute to highly capable autonomous robotics systems and propulsion products that operate reliably in the most demanding mission environment.

ABOUT THE JOB

As a Robotics Software Engineer on our TRS team, you'll be at the forefront of cutting-edge autonomous systems development. You'll tackle diverse challenges in autonomy, systems integration, robotics, and networking, making critical engineering decisions that directly impact mission success. Your role will be pivotal in ensuring Anduril's products work seamlessly together to achieve a variety of crucial outcomes. You'll develop innovative solutions for complex robotics problems, balance pragmatic engineering trade-offs with mission-critical requirements, and collaborate across teams to integrate software with hardware systems. Contributing to the entire product lifecycle, from concept to deployment, you'll rapidly prototype and iterate on software solutions. We're looking for someone who thrives in a fast-paced environment and isn't afraid to tackle ambiguous problems. Your "Whatever It Takes" mindset will be key in executing tasks efficiently, scalably, and pragmatically, always keeping the mission at the forefront of your work. This role offers the opportunity to make a significant impact on next-generation defense technology, working with state-of-the-art robotics and autonomous systems. You'll be part of a team that values innovation, quick iteration, and delivering high-quality solutions that meet real-world needs.

Must be eligible to obtain and maintain an active U.S. Secret security clearance. 

WHAT YOU'LL DO

• Develop and maintain core robotics libraries, including frame transformations, targeting, and guidance systems, that will be utilized across all Anduril robotics platforms
• Lead the development and implementation of major features for our products, such as designing and building Software-in-the-Loop simulators for advanced systems like Altius
• Optimize performance of existing products, primarily focused on our Altius Drone product line
• Collaborate closely with hardware and manufacturing teams throughout the product development lifecycle, providing timely feedback to influence and enhance final hardware designs
• Troubleshoot and resolve complex issues in deployed systems, ensuring optimal performance in the field
• Contribute to the design and implementation of multi-agent coordination systems for UAVs
• Participate in the full software development lifecycle, from concept and design through testing and deployment
• Stay current with emerging technologies and industry trends, recommending and implementing innovations to improve our products and processes

REQUIRED QUALIFICATIONS

• Bachelor's degree in Robotics, Computer Science, or related field
• 3+ years of professional software development experience
• Strong proficiency in C++ or Rust, with experience in Linux development environments
• Demonstrated expertise in data structures, algorithms, concurrency, and code optimization
• Proven experience troubleshooting and analyzing remotely deployed software systems
• Hands-on experience working with and testing electrical and mechanical systems
• Ability to collaborate effectively with cross-functional teams, including hardware and manufacturing
• Strong problem-solving skills and a "Whatever It Takes" mindset
• Excellent communication skills, both written and verbal
• Eligible to obtain and maintain an active U.S. Secret security clearance
• Willingness to relocate to Seattle, WA

PREFERRED QUALIFICATIONS

• Master's or Ph.D. in a relevant field (e.g., Robotics, Computer Science, Electrical Engineering)
• Expertise in one or more advanced robotics areas: motion planning, perception, localization, mapping, or controls
• Experience with performance optimization and metrics for complex robotic systems
• Proficiency in Python, Rust, and/or Go, in addition to C++
• Hands-on experience programming for embedded systems and physical devices
• Background in multi-agent coordination, particularly with UAVs
• Demonstrated ability to solve complex frame transformation problems (e.g., target localization, multi-degree-of-freedom robotic arms)
• Experience with real-time operating systems and distributed computing
• Familiarity with machine learning and AI applications in robotics
• Knowledge of sensor fusion techniques and implementation
• Understanding of aerodynamics and flight dynamics as applied to UAV systems
• Experience with simulation environments for robotics testing and development
• Track record of contributions to open-source robotics projects or relevant publications

We are seeking a Generative AI Chief Engineer Lead to drive innovations in autonomous vehicle technology using deep learning and reinforcement learning. In this dynamic role, you will design state-of-the-art algorithms and systems that enable safe, efficient, and intelligent autonomous capabilities. Today, employing mass quantities of autonomous robots requires heavy human oversight and execution. Anduril is leveraging AI approaches to improve effectiveness of autonomous missions, offload operator burden, and speed up execution via realtime monitoring, recommendations to users, and multi-modal interaction patterns. You will apply proven and un-proven approaches to create prototypes for expanding the capability of autonomous systems.

What You’ll Do

• Develop Advanced Agentic Software - Design and implement novel agent-based software systems to improve sensor perception, prediction, and decision-making for autonomous vehicles
• Apply Agentic Reasoning - Design and implement integrated agents and AI models to solve for end-user autonomous systems workflows.
• End-to-End System Integration - Collaborate with cross-functional teams to integrate research prototypes into robust, production-ready systems including simulation environments and real-world platforms.
• Research & Experimentation - Conduct research into reinforcement learning strategies and deep architectures, iterate on experimental designs, and evaluate performance using rigorous quantitative metrics.
• Data-Driven Innovation - Utilize real-world and synthetic data to enhance model robustness and generalization, leveraging scalable training pipelines on distributed systems.

Required Qualifications

• Sophisticated knowledge of LLM's with an understanding of how they work and how they're applied
• Solid experience with reinforcement learning methods and their application to autonomous systems.
• Proven experience of shipping products end to end
• Experience with simulation or real-world validation for autonomous vehicles is highly desirable.
• A degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Eligible to obtain and maintain an active U.S. Top Secret security clearance
• Travel up to 40+% of time to build, test, and deploy capabilities in the real world

Preferred Qualifications

• PhD or Master’s degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
• Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community.
• Proven experience in deep learning research and development, particularly in generative AI. This includes diffusion models and autoregressive generative models.
• Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar).
• Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines.
• Strong programming skills in Python and familiarity with C/C++ is a plus.
• General software engineering experience solving motion planning or related robotics problems.

Hudson River Trading (HRT) is seeking a Physical Design Engineer with a broad, versatile skillset to join our growing Hardware team. In this role, you will help deliver performance-critical ASICs and advance our physical design methodologies on leading-edge process nodes.

The Hardware team at HRT builds high-performance compute engines using FPGA and ASIC technology to drive low-latency trading decisions on global markets. We create custom solutions across the full spectrum of speed and sophistication, from bespoke circuits to world-class machine learning accelerators.

Responsibilities

• Drive design-for-test (DFT) methodologies and implementation 
• Contribute to physical implementation, from RTL handoff through GDSII on advanced process nodes 
• Partner on floorplanning and physical optimization for high-performance, latency-critical designs
• Close timing across multiple modes and corners while optimizing power, performance, and area (PPA)
• Diagnose and resolve physical design issues such as timing bottlenecks, congestion, and IR/EM violations
• Build, maintain, and improve repeatable, automated physical design flows
• Develop scripts and tooling to improve productivity, robustness, and insight into design behavior
• Collaborate closely with RTL, architecture, and other hardware engineers to influence design decisions early

Qualifications

• Experience working in high-performance ASIC design environments
• Strong fundamentals in digital logic, circuit design, and process technology
• Familiarity with DFT concepts and testing methodologies
• Strong scripting and automation skills (Python, Tcl, shell), including parsing and analyzing tool outputs
• Ability to design robust methodologies, diagnose complex failures, and improve physical design flows
• Applied use of statistics in analyzing timing, power, or design data (preferred)
• Hands-on experience with static timing analysis and timing closure methodologies
• Expertise using industry-standard physical design and signoff tools (e.g., Innovus, PrimeTime)

This job is accepting ongoing applications and there is no application deadline.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience.

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological innovation. We build and deploy cutting-edge systems within one of the world’s most advanced computing environments to power our global trading operations. Our non-siloed, collaborative coding environment empowers talented engineers to make significant contributions and see their impact daily. At HRT, you'll be challenged to solve the most complex problems in trading alongside many of the brightest minds in the field.

We are seeking highly motivated and skilled Research Engineers who will work very closely with our Algo Developer (Quant Research) trading teams. These roles require exceptional programming fundamentals, a strong user focus, and the ability to thrive in a fast-paced environment with constantly evolving requirements. Multitasking and context switching are inherent aspects of this role, through which you will gain insight into the ideation and execution of some of the world's most sophisticated trading strategies.  

Research Engineers at HRT work on a wide variety of projects. Examples include:

• Designing highly customized quantitative systems that enable Algo Developers to easily express and backtest new predictive signals.
• Building world-class research tooling to speed up Algo Developers’ research iteration.
• Aiding the development and deployment of very large deep learning models for HRT’s live trading.
• Improving HRT’s monetization systems which turn our predictions into profitable trades.
• Evaluating sim vs. live differences to improve the fidelity of our simulations.
• Building systems to monitor and manage live trading.
• Specializing in specific time horizons, from high frequency trading to mid-to-low frequency hedge fund-style strategies.
• Working across a very wide variety of asset classes (from equities to fixed income to options) and regions (from North America to Asia Pacific) – you’ll interact with markets across the world!

Responsibilities

• Design, develop, and maintain robust, performant, and scalable software systems.
• Optimize existing codebases for performance, reliability, and efficiency.
• Debug complex issues across distributed systems in a time-sensitive environment.
• Optimize both the mechanics and ergonomics of Algo Developer research workflows; this requires developing a deep intuition for research methodologies.
• Balance the short term goals of individual trading teams with the longer term goals of HRT’s generalized trading platforms across trading teams. Because we don’t work in a pod environment, REs on different trading teams are expected to share technology and ideas.

Qualifications

• Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
• Previous experience at a top-tier finance or technology company with an excellent track record of rapid advancement and superlative reviews.
• Experience with supporting internal users is preferred; bonus if you have real hands-on experience with quant research and/or ML/Deep Learning platforms.
• Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.)
• Candidates should be prepared for technical interviews in either Python or C++. While there is no hard language requirement for RE roles, proficiency in one of these languages will be assessed during the interview process.
• Kindness and empathy is a real requirement. No “smart jerks” at HRT. 
• Strong understanding of data structures, algorithms, and design principles.
• Excellent communication skills, both written and verbal.
• HRT ships every day. The ability to thoughtfully, methodically, and reliably deploy new software and features is a critical skill. 
• If you have management experience, that’s always a bonus – but even so, expect to code!

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

For more info about interviewing at HRT, see this blog!

Responsibilities:

• Designing and implementing from scratch new information architecture strategies
• Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
• Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
• Designing and evaluating advanced agentic search capabilities.

You may be a good fit if you:

• Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
• Have good machine learning research experience 
• Have experience developing software that utilizes Large Language Models such as Claude
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to partner with world-class ML researchers to develop new LLM capabilities
• Care about the societal impacts of your work
• Have clear written and verbal communication

Strong candidates will also have experience with:

• Collaborating with product teams to quickly prototype and deliver innovative solutions
• Building complex agentic systems that utilize LLMs
• Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing

About the role

Anthropic runs some of the largest Kubernetes clusters in the industry. We have fleets of hundreds of thousands of nodes across multiple cloud providers and datacenters to train, research, and serve frontier AI models. The Kubernetes Platform team owns the Kubernetes control plane that makes those clusters work.

We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure.

We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow.

Key responsibilities

• Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption
• Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us
• Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on
• Build and maintain custom controllers, operators, and CRDs
• Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities
• Collaborate with cloud providers on required features and escalations
• Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures

Minimum qualifications

• Significant software engineering experience building and operating production distributed systems
• Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++)
• Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters
• Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes
• A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on
• Strong written and verbal communication; comfort building consensus with internal stakeholders

Preferred qualifications

• Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar
• Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents)
• Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments)
• Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL
• Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code
• Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF
• 8+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.   

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.  

Role Overview

As part of our Application Infrastructure org, this is a team building Coupang’s next-generation Real-Time Streaming & AI Platform that powers the end customer website and mobile apps. 

We are looking for a visionary Staff Software Engineer to lead the architectural design of a platform capable of processing over 100k+ events per second with sub-second, end-to-end latency. This system will serve as the central nervous system for Coupang, enabling real-time product and customer data and instant personalization. You will build a system that doesn't just meet industry standards but sets them, ensuring 5-6 nines availability while leveraging AI to optimize data flows and automate complex system behaviors.

What You Will Do

• Architect for Velocity: Lead the end-to-end design of a distributed streaming engine. You will Build the Best Team and Help Them Grow by setting the gold standard for high-throughput, low-latency architectural integrity.
• Define Extreme Performance: Design for "5-6 nines" (99.9999% availability) at a throughput of 100k+ events/sec. You will Dive Deep into JVM tuning, memory management, and network I/O to ensure sub-second latency across global clusters.
• AI-Driven Streaming: Integrate AI/ML models directly into the stream processing path. Implement predictive scaling and intelligent load balancing to ensure we Wow the Customer through seamless, real-time platform responsiveness.
• Solve Hard Problems: Address challenges related to distributed consistency, at times, exactly-once processing guarantees, and backpressure management. You must Be Data-Driven to validate architectural decisions against massive, bursty traffic patterns.

Basic Qualifications 

• Bachelor's degree in computer science, Electrical Engineering, Math, or a closely related field
• 4 years of experience in backend software development
• Proficiency in Java and the Spring Framework
• Experience working in cloud environments, particularly AWS
• Demonstrated experience in building and maintaining highly available, distributed systems

Preferred Qualifications

• Expert-level experience in Cassandra, TiDB, or DynamoDB
• Expert-level proficiency in Java and the Spring Framework.
• Demonstrated experience in building and maintaining highly available, distributed systems in cloud environments (AWS).
• Experience with high-volume messaging systems (e.g., Kafka, SQS)
• Extensive Experience: 10+ years of professional software development experience building backend infrastructure that supports global-scale, real-time traffic.
• Performance Expert: Proven track record of optimizing JVM applications for ultra-low latency (<100ms p99s) and high concurrency.
• AI Integration: Experience or a strong architectural vision for using AI/ML to automate system-level functionality, such as real-time anomaly detection in data streams.
• Distributed Systems Expert: Deep understanding of the CAP theorem, consensus algorithms, and building fault-tolerant systems from the ground up.

Pay & Benefits 

Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation. 

The base pay for this position ranges from $152,000/year to $282,000/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills and experience. 

General Description of All Benefits 

• Annual bonus is 0-20% of the base salary
• Medical/Dental/Vision/Life, AD&D insurance
• Flexible Spending Accounts (FSA) & Health Savings Account (HAS)
• Long-term/Short-term Disability
• Employee Assistance Program (EAP) program
• 401K Plan with Company Match
• 18-21 days of Paid Time Off (PTO) a year based on the tenure
• 12 Paid Holidays
• Paid Parental leave
• Pre-tax commuter benefits
• MTV- [Free] Electric Car Charging Station 

General Description of Other Compensation 

“Other Compensation” includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary or wage scale. 

Recruitment Process and Others  

Recruitment Process   

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer 

• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances. 

• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage. 

Details to Consider  

• This job posting may be closed prior to the stated end date for application if all openings are filled. 

• Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process. 

• Coupang does not discriminate against disabled applicants or those with veteran status. We are proud to offer equal opportunities for all applicants. 

 Privacy Notice   

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/  

Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or gender (including pregnancy, gender identity, gender expression, sexual orientation, transgender status), national origin, age, disability, medical condition, HIV/AIDS or Hepatitis C status, marital status, military or veteran status, use of a trained dog guide or service animal, political activities, or affiliations, citizenship, or any other characteristic or class protected by the laws or regulations in the locations where we operate. If you need assistance and/or reasonable accommodation in the recruiting process due to a disability, please contact us at usrecruiting@coupang.com.    

MORSE is seeking a skilled Full Stack Software Engineer to join one or more projects in big data, artificial intelligence, autonomous vehicle mission planning, decision systems, and their accompanying cloud applications. Our applications provide cutting-edge, algorithmic-based simulation, situational awareness, machine learning, analysis, and mission planning capabilities to a wide variety of DoD customers. As a member of a small interdisciplinary team of scientists, engineers, and software developers, you will follow Agile development processes and embrace DevSecOps to ensure fast and secure delivery of software services.

Responsibilities:

• Develop and maintain web applications hosted on cloud infrastructure

• Collaborate with infrastructure engineers to containerize applications for cloud deployment

• Implement web page UIs from design documents

• Write backend APIs that interact with cloud services

• Work closely with team members to design, develop, and deploy software applications

• Stay up-to-date with the latest web development and cloud computing trends

• Contribute to the development of new code bases that are heavily object-oriented, extensible, and maintainable

Requirements:

• U.S. Citizenship and the ability to obtain a U.S. Security Clearance (Secret or Top Secret)

• 5+ years of software engineering experience

• Experience with React and front end development

• Experience with Python

• Knowledge of Cloud technologies, including AWS, Azure, or GCP

• Proficiency with Docker and Kubernetes

• Experience with Agile development

• BS or MS in computer science or equivalent degree, or significant professional experience

Desired Skills:

• Experience with HCI and web design

• Experience with microservice architecture

• Experience with IAC tools like Terraform or CloudFormation

• Experience with scalable cloud infrastructure

MORSE is seeking a skilled Full Stack Software Engineer to join one or more projects in big data, artificial intelligence, autonomous vehicle mission planning, decision systems, and their accompanying cloud applications. Our applications provide cutting-edge, algorithmic-based simulation, situational awareness, machine learning, analysis, and mission planning capabilities to a wide variety of DoD customers. As a member of a small interdisciplinary team of scientists, engineers, and software developers, you will follow Agile development processes and embrace DevSecOps to ensure fast and secure delivery of software services.

Responsibilities:

• Develop and maintain web applications hosted on cloud infrastructure

• Collaborate with infrastructure engineers to containerize applications for cloud deployment

• Implement web page UIs from design documents

• Write backend APIs that interact with cloud services

• Work closely with team members to design, develop, and deploy software applications

• Stay up-to-date with the latest web development and cloud computing trends

• Contribute to the development of new code bases that are heavily object-oriented, extensible, and maintainable

Requirements:

• U.S. Citizenship and the ability to obtain a U.S. Security Clearance (Secret or Top Secret)

• 5+ years of software engineering experience

• Experience with React and front end development

• Experience with Python

• Knowledge of Cloud technologies, including AWS, Azure, or GCP

• Proficiency with Docker and Kubernetes

• Experience with Agile development

• BS or MS in computer science or equivalent degree, or significant professional experience

Desired Skills:

• Experience with HCI and web design

• Experience with microservice architecture

• Experience with IAC tools like Terraform or CloudFormation

• Experience with scalable cloud infrastructure

MORSE is seeking a skilled Full Stack Software Engineer to join one or more projects in big data, artificial intelligence, autonomous vehicle mission planning, decision systems, and their accompanying cloud applications. Our applications provide cutting-edge, algorithmic-based simulation, situational awareness, machine learning, analysis, and mission planning capabilities to a wide variety of DoD customers. As a member of a small interdisciplinary team of scientists, engineers, and software developers, you will follow Agile development processes and embrace DevSecOps to ensure fast and secure delivery of software services.

Responsibilities:

• Develop and maintain web applications hosted on cloud infrastructure

• Collaborate with infrastructure engineers to containerize applications for cloud deployment

• Implement web page UIs from design documents

• Write backend APIs that interact with cloud services

• Work closely with team members to design, develop, and deploy software applications

• Stay up-to-date with the latest web development and cloud computing trends

• Contribute to the development of new code bases that are heavily object-oriented, extensible, and maintainable

Requirements:

• U.S. Citizenship and the ability to obtain a U.S. Security Clearance (Secret or Top Secret)

• 5+ years of software engineering experience

• Experience with React and front end development

• Experience with Python

• Knowledge of Cloud technologies, including AWS, Azure, or GCP

• Proficiency with Docker and Kubernetes

• Experience with Agile development

• BS or MS in computer science or equivalent degree, or significant professional experience

Desired Skills:

• Experience with HCI and web design

• Experience with microservice architecture

• Experience with IAC tools like Terraform or CloudFormation

• Experience with scalable cloud infrastructure

We are seeking a Deputy Chief Engineer to lead our efforts in developing and deploying capabilities for artificial intelligence, machine learning, data management, decision systems, and mission planning software applications for the US National Security Ecosystem. This is an exceptional opportunity for an engineer with a combination of technical expertise, program leadership experience, and the ability to interface with customers to drive innovation, collaboration, and excellence in a fast-paced, growing organization.

Responsibilities:

• Set the technical vision and direction for programs, collaborating with internal technical staff and external customers

• Lead multidisciplinary teams developing algorithms, software, cloud, and data management solutions

• Manage program execution, ensuring schedule and budget adherence, and overseeing successful program delivery

• Cultivate strong relationships with external partners and stakeholders, advocating for MORSE's technology and services

• Identify and pursue new business opportunities, expanding our portfolio and driving long-term growth

• Provide technical oversight and guidance to program team members

Requirements:

• US Citizenship and ability to obtain and maintain a Security Clearance

• Bachelor’s or Master’s or PhD in Computer Science, Software Engineering, Aerospace Engineering, Electrical Engineering, Physics or a related field

• Minimum of 5 years of experience in software development, with a focus on AI/ML, cloud computing, and/or decision systems

• Proven leadership skills, with a track record of successfully managing high-performing technical teams

• Deep understanding of software development principles, methods, and tools

• Strong analytical and problem-solving abilities, with the capacity to absorb complex technical information quickly

• Excellent written and verbal communication skills, with the ability to present technical information clearly and persuasively to both technical and non-technical audiences

• Experience with Agile methodologies and DevOps practices

• Familiarity with cloud computing platforms and infrastructure is nice to have 

We are seeking a Deputy Chief Engineer to lead our efforts in developing and deploying capabilities for artificial intelligence, machine learning, data management, decision systems, and mission planning software applications for the US National Security Ecosystem. This is an exceptional opportunity for an engineer with a combination of technical expertise, program leadership experience, and the ability to interface with customers to drive innovation, collaboration, and excellence in a fast-paced, growing organization.

Responsibilities:

• Set the technical vision and direction for programs, collaborating with internal technical staff and external customers

• Lead multidisciplinary teams developing algorithms, software, cloud, and data management solutions

• Manage program execution, ensuring schedule and budget adherence, and overseeing successful program delivery

• Cultivate strong relationships with external partners and stakeholders, advocating for MORSE's technology and services

• Identify and pursue new business opportunities, expanding our portfolio and driving long-term growth

• Provide technical oversight and guidance to program team members

Requirements:

• US Citizenship and ability to obtain and maintain a Security Clearance

• Bachelor’s or Master’s or PhD in Computer Science, Software Engineering, Aerospace Engineering, Electrical Engineering, Physics or a related field

• Minimum of 5 years of experience in software development, with a focus on AI/ML, cloud computing, and/or decision systems

• Proven leadership skills, with a track record of successfully managing high-performing technical teams

• Deep understanding of software development principles, methods, and tools

• Strong analytical and problem-solving abilities, with the capacity to absorb complex technical information quickly

• Excellent written and verbal communication skills, with the ability to present technical information clearly and persuasively to both technical and non-technical audiences

• Experience with Agile methodologies and DevOps practices

• Familiarity with cloud computing platforms and infrastructure is nice to have 

We are seeking a Deputy Chief Engineer to lead our efforts in developing and deploying capabilities for artificial intelligence, machine learning, data management, decision systems, and mission planning software applications for the US National Security Ecosystem. This is an exceptional opportunity for an engineer with a combination of technical expertise, program leadership experience, and the ability to interface with customers to drive innovation, collaboration, and excellence in a fast-paced, growing organization.

Responsibilities:

• Set the technical vision and direction for programs, collaborating with internal technical staff and external customers

• Lead multidisciplinary teams developing algorithms, software, cloud, and data management solutions

• Manage program execution, ensuring schedule and budget adherence, and overseeing successful program delivery

• Cultivate strong relationships with external partners and stakeholders, advocating for MORSE's technology and services

• Identify and pursue new business opportunities, expanding our portfolio and driving long-term growth

• Provide technical oversight and guidance to program team members

Requirements:

• US Citizenship and ability to obtain and maintain a Security Clearance

• Bachelor’s or Master’s or PhD in Computer Science, Software Engineering, Aerospace Engineering, Electrical Engineering, Physics or a related field

• Minimum of 5 years of experience in software development, with a focus on AI/ML, cloud computing, and/or decision systems

• Proven leadership skills, with a track record of successfully managing high-performing technical teams

• Deep understanding of software development principles, methods, and tools

• Strong analytical and problem-solving abilities, with the capacity to absorb complex technical information quickly

• Excellent written and verbal communication skills, with the ability to present technical information clearly and persuasively to both technical and non-technical audiences

• Experience with Agile methodologies and DevOps practices

• Familiarity with cloud computing platforms and infrastructure is nice to have 

Job Summary:

We are seeking an experienced and talented Chief Engineer to lead our efforts in developing and deploying capabilities for artificial intelligence, machine learning, decision systems, and mission planning applications. This is an exceptional opportunity for a seasoned engineer to drive innovation, collaboration, and excellence in a fast-paced and growing organization.

Responsibilities:

• Set the technical vision and direction for programs, collaborating with internal technical staff and external customers

• Lead multi-disciplinary teams developing algorithmic, software, cloud, and data solutions

• Manage program execution, ensuring schedule and budget adherence, and overseeing successful program delivery

• Cultivate strong relationships with external partners and stakeholders, advocating for MORSE's technology and services

• Identify and pursue new business opportunities, expanding our portfolio and driving long-term growth

• Provide technical oversight and guidance to program team members

Requirements:

• US Citizenship and ability to obtain and maintain a Security Clearance. Active Secret, Top Secret, or TS/SCI is preferred. 

• Master's degree or PhD in Aerospace Engineering, Computer Science, Physics, Electrical Engineering, or a related field

• Minimum of 10 years of experience in R&D, with a focus on AI/ML, software, and decision systems

• Proven leadership skills, with a track record of successfully managing high-performing technical teams

• Deep understanding of software development principles, methods, and tools

• Strong analytical and problem-solving abilities, with the capacity to absorb complex technical information quickly

• Excellent written and verbal communication skills, with the ability to present technical information clearly and persuasively to both technical and non-technical audiences

• Experience with Agile methodologies and DevOps practices

• Familiarity with cloud computing platforms and infrastructure is nice to have

MORSE is seeking an experienced and talented Chief Engineer to lead our efforts in developing and deploying capabilities for artificial intelligence, machine learning, decision systems, and mission planning applications. This is an exceptional opportunity for a seasoned engineer to drive innovation, collaboration, and excellence in a fast-paced and growing organization.

Responsibilities:

• Set the technical vision and direction for programs, collaborating with internal technical staff and external customers

• Lead multi-disciplinary teams developing algorithmic, software, cloud, and data solutions

• Manage program execution, ensuring schedule and budget adherence, and overseeing successful program delivery

• Cultivate strong relationships with external partners and stakeholders, advocating for MORSE's technology and services

• Identify and pursue new business opportunities, expanding our portfolio and driving long-term growth

• Provide technical oversight and guidance to program team members

Requirements:

• US Citizenship and ability to obtain and maintain a Security Clearance. Active Secret, Top Secret, or TS/SCI is preferred. 

• Master's degree or PhD in Aerospace Engineering, Computer Science, Physics, Electrical Engineering, or a related field

• Minimum of 10 years of experience in R&D, with a focus on AI/ML, software, and decision systems

• Proven leadership skills, with a track record of successfully managing high-performing technical teams

• Deep understanding of software development principles, methods, and tools

• Strong analytical and problem-solving abilities, with the capacity to absorb complex technical information quickly

• Excellent written and verbal communication skills, with the ability to present technical information clearly and persuasively to both technical and non-technical audiences

• Experience with Agile methodologies and DevOps practices

• Familiarity with cloud computing platforms and infrastructure is nice to have

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

• US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

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.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Seattle area is $149,780 - $187,220, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging AI and Machine Learning to better serve our customers. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is seeking a Senior Machine Learning Engineer to focus on building AI Platform components enabling critical AI applications across Lyft. Expertise with GenAI and platform building is a core requirement for this role. In this role, you will contribute to our platform which supports real-time, online, and offline AI and ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in building an AI Platform at scale, with applications across each facet of the company, we are searching for you.

If you are a creative and critical thinker with experience in AI and machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge 
• Build features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents 
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks

Experience:

• BSc/MSc in Computer Engineering, Computer Science, Machine Learning related field or relevant work experience
• 5+ years of ML engineering experience working in any of these stacks: Python, GO, Java, etc.
• Experience with ML serving/training/deployment infrastructure; familiarity with cloud providers (e.g. AWS, Azure, Google Cloud); familiarity with GenAI ecosystem: LLMs, prompt engineering, MCP, RAG; hands-on experience with LLM fine-tuning techniques and frameworks (e.g. PEFT, LoRA); knowledge on deploying self-hosted LLMs (e.g. Llama, Mistral) for specialized tasks
• Experience with GenAI/LLM infrastructure, agent frameworks (e.g. LangChain, LangGraph); MLOps tooling (MLflow, Airflow)
• Preferred: Experience with AI assisted coding such as Cursor or Claude Code

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.