Location: United States
Location & Work Arrangement
Costa Mesa, CA (On-Site) preferred
Remote opportunities may be considered
for exceptionally strong candidates located elsewhere in the U.S.
Employment Details
Contract:
6 months, with potential for extension or conversion to a permanent position
Target Bill Rate:
Up to $120/hour
Requirements
Must be a
U.S. Citizen
Must be
eligible to obtain and maintain a Top Secret security clearance
WHAT YOU'LL DO
Thermal design and analysis of unmanned air vehicles at conceptual, preliminary, and detailed design maturities
Define thermal system architectures and material selection strategies for vehicles operating in demanding flight environments
Thermal analysis of flight vehicles using CFD, FEA, and engineering methods
Material response modeling under combined thermal and mechanical loads
Transient thermal analysis for time-varying mission profiles
Ground test planning, execution, and analysis in specialized thermal test facilities
Flight test planning, execution, and post-flight thermal data analysis
Use first principles and MATLAB/Python models to inform design decisions
Collaborate with aerodynamics, structures, electrical, and systems engineers on integrated solutions
Present thermal status at formal reviews internally and with customers
Prepare formal documentation (specifications, test procedures, technical reports)
REQUIRED QUALIFICATIONS
MS or higher degree in Aerospace Engineering, Mechanical Engineering, or Applied Physics with focus on heat transfer and fluid dynamics
In-depth understanding of heat transfer, fluid dynamics, and high-temperature environments
5+ years of experience in aerospace thermal engineering on rocket, aircraft, or missile programs
Experience with thermal analysis in high-speed flight regimes
Thermal analysis experience using CFD (STAR-CCM+, ANSYS Fluent) and/or FEA thermal solvers
Experience with thermal-structural coupling
Ground testing experience with thermal instrumentation and data acquisition
Strong programming skills in MATLAB, Python, or similar for tool development
Experience preparing formal documentation
CAD experience with SolidWorks or Siemens NX
Passion for defending the United States and her allies
Ability to obtain and hold a U.S. Top Secret security clearance
PREFERRED QUALIFICATIONS
Experience with material response modeling in extreme thermal environments
Knowledge of material degradation and surface phenomena under demanding conditions
Experience with specialized thermal ground test facilities
Experience with chemical kinetics and finite-rate chemistry modeling
Flight test experience including instrumentation design and post-flight analysis
Experience with thermal-structural analysis codes (NASTRAN, Abaqus, ANSYS Mechanical)
Material characterization experience at elevated temperatures
Experience with manufacturing and assembly of thermal systems
Active U.S. security clearance
Location: United States
Location & Work Arrangement
Costa Mesa, CA (On-site) preferred
Remote opportunities may be considered
for exceptionally strong candidates located elsewhere in the U.S.
Employment Details
Contract:
6 months, with potential for extension or conversion to a permanent position
Target Bill Rate:
Up to $120/hour
Requirements
Must be a
U.S. Citizen
Must be
eligible to obtain and maintain a Top Secret security clearance
What You'll Do
· Own thermal design and analysis for integrated hardware products, including drones, aircraft, missiles, or related defense systems.
· Use first-principles engineering judgment to determine the right level of analysis for each design decision, including hand calculations, spreadsheets, MATLAB / Python models, FEA, and CFD.
· Define thermal architectures that can withstand rugged environments, demanding flight envelopes, and operational edge cases, including hot, cold, transient, and mission-specific thermal conditions.
· Partner with electrical, mechanical, aerospace, software, and systems engineers to document power dissipation, operating modes, thermal constraints, and design tradeoffs.
· Build and maintain thermal FEA / CFD models to predict system performance, establish design limits, and define red / yellow operating thresholds for test and field use.
· Define and execute prototype builds and thermal tests, including CAD support, sensor selection, DAQ setup, data post-processing, and results documentation.
· Present thermal status, risks, tradeoffs, timelines, and recommendations in internal design reviews and customer-facing technical reviews.
· Develop internal tools, workflows, or analysis methods that improve speed, consistency, and quality of thermal decision-making.
· Support failure reviews and root-cause investigations using test data, thermal analysis, and first-principles reasoning.
Required Qualifications
· MS or PhD in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field with a focus on heat transfer, fluid dynamics, thermal sciences, or thermal systems.
· 5+ years of experience designing, analyzing, or validating thermal systems for integrated hardware products.
· Strong first-principles understanding of heat transfer and fluid dynamics, including conduction, convection, radiation, fluid flow, and transient thermal behavior.
· Experience supporting thermal design for aerospace, aircraft, rocket, missile, UAV, defense, or other high-performance hardware systems.
· Experience using thermal analysis, modeling, simulation, and/or physical test data to drive design decisions for passive or active thermal management systems.
· Ability to communicate technical tradeoffs clearly across engineering, program, and customer stakeholders, and ability to obtain and maintain a U.S. Top Secret security clearance.
Preferred Qualifications
· Experience with thermal analysis tools such as STAR-CCM+, ANSYS, Icepak, Flotherm, or comparable FEA / CFD platforms.
· Experience using MATLAB, Python, spreadsheets, or similar tools for first-order thermal modeling, transient analysis, or engineering trade studies.
· Experience designing thermal hardware such as heat sinks, cold plates, fans, pumps, heat exchangers, thermal interface materials, liquid cooling systems, or air-cooling systems.
· Experience planning or executing thermal tests, including sensor selection, data acquisition, data post-processing, and correlation of test results to analysis.
· Experience with SolidWorks, Siemens NX, or comparable CAD tools.
· Experience supporting formal design reviews, customer reviews, flight test, qualification testing, or fielded hardware.
· Experience developing reusable analysis tools, automation workflows, reduced-order models, or other methods that improve analysis speed and consistency.
· Strong motivation to support Client’s mission of defending the United States and allied partners.
🔍We are looking for a Senior Database Engineer (PostgreSQL, MySQL). You’ll take full ownership of the production databases at a high-traffic, high-load startup with millions of rows.
Location: Costa Mesa, United States
📍
Location:
Costa Mesa, California
📄
Employment Type:
Contract-to-Perm
🏢
Work Arrangement:
Remote Opportunity for Top Candidates
🚀
Start Date:
TBD
💰
Compensation:
TBD — based on skills and experience
Important Screening Requirements
Remote opportunity is open to qualified candidates
within the United States
.
Relocation assistance is available to qualified candidates from other countries.
5+ years of experience
designing, analyzing, or validating thermal systems for integrated hardware products.
MS or PhD
in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field, with a focus on heat transfer, fluid dynamics, thermal sciences, or thermal systems.
Strong first-principles understanding of
heat transfer and fluid dynamics
.
Experience supporting thermal design for
aerospace, aircraft, rocket, missile, UAV, defense, or other high-performance hardware
.
Experience with thermal analysis, modeling, simulation, and/or physical test data.
Ability to communicate technical tradeoffs across engineering, program, and customer stakeholders.
Ability to obtain and maintain a
U.S. Top Secret security clearance
, where required.
About the Role
We are seeking a
Senior Thermal Engineer
to own thermal design and analysis for advanced defense hardware across drones, aircraft, missiles, and related flight systems.
This role is ideal for an engineer with deep expertise in
heat transfer and fluid dynamics
, strong thermal analysis capabilities, and the engineering judgment to select the appropriate level of analysis—from first-order hand calculations through detailed FEA and CFD—to support rapid and effective design decisions.
You will work across multidisciplinary engineering teams to develop thermal architectures, evaluate system performance, support prototype testing, and drive thermal design decisions for demanding operating environments.
What We’re Looking For
We’re looking for a senior thermal engineer who can take ownership of thermal engineering
from early design and analysis through testing and validation
.
The ideal candidate combines strong fundamentals in heat transfer and fluid dynamics with hands-on experience applying thermal analysis to complex, high-performance hardware. You should be comfortable working across disciplines, making engineering tradeoffs, troubleshooting thermal issues, and communicating technical recommendations to both engineering and customer stakeholders.
Key Responsibilities
Thermal Design & Analysis
Own thermal design and analysis for integrated hardware products, including
drones, aircraft, missiles, and related defense systems
.
Apply first-principles engineering judgment to determine the appropriate level of analysis for each design decision, including:
Hand calculations
Spreadsheets
MATLAB/Python models
FEA
CFD
Define thermal architectures capable of operating in rugged environments and demanding flight envelopes.
Evaluate
hot, cold, transient, and mission-specific thermal conditions
.
Cross-Functional Engineering
Partner with electrical, mechanical, aerospace, software, and systems engineers to document:
Power dissipation
Operating modes
Thermal constraints
Design tradeoffs
Build and maintain thermal
FEA/CFD models
to predict system performance, establish design limits, and define red/yellow operating thresholds for testing and field use.
Prototype Testing & Validation
Define and execute prototype builds and thermal tests.
Support CAD activities, sensor selection,
DAQ setup
, data post-processing, and test-result documentation.
Use test data and thermal analysis to validate designs and support engineering decisions.
Technical Leadership & Continuous Improvement
Present thermal status, risks, tradeoffs, timelines, and recommendations during internal design reviews and customer-facing technical reviews.
Develop internal tools, workflows, and analysis methods that improve the speed, consistency, and quality of thermal decision-making.
Support failure reviews and root-cause investigations using test data, thermal analysis, and first-principles engineering reasoning.
Required Qualifications
MS or PhD
in Mechanical Engineering, Aerospace Engineering, Applied Physics, or a related field focused on heat transfer, fluid dynamics, thermal sciences, or thermal systems.
5+ years
of experience designing, analyzing, or validating thermal systems for integrated hardware products.
Strong first-principles understanding of:
Conduction
Convection
Radiation
Fluid flow
Transient thermal behavior
Experience supporting thermal design for aerospace, aircraft, rocket, missile, UAV, defense, or other high-performance hardware systems.
Experience using thermal analysis, modeling, simulation, and/or physical test data to drive design decisions for passive or active thermal management systems.
Ability to clearly communicate technical tradeoffs across engineering, program, and customer stakeholders.
Ability to obtain and maintain a
U.S. Top Secret security clearance
, where required.
Preferred Qualifications
Experience with thermal analysis tools such as:
STAR-CCM+
ANSYS
Icepak
FloTHERM
Comparable FEA/CFD platforms
Experience using
MATLAB, Python, spreadsheets
, or similar tools for first-order thermal modeling, transient analysis, or engineering trade studies.
Experience designing thermal hardware such as:
Heat sinks
Cold plates
Fans
Pumps
Heat exchangers
Thermal interface materials
Liquid cooling systems
Air-cooling systems
Experience planning or executing thermal tests, including sensor selection, data acquisition, data post-processing, and correlation of test results to analysis.
Experience with
SolidWorks, Siemens NX, or comparable CAD tools
.
Experience supporting formal design reviews, customer reviews, flight testing, qualification testing, or fielded hardware.
Experience developing reusable analysis tools, automation workflows, reduced-order models, or other methods that improve analysis speed and consistency.
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🔎 We are looking for a Senior Database Engineer (PostgreSQL, MySQL). You’ll take full ownership of the production databases at a high-traffic, high-load startup with millions of rows.
Location: Office Based - Beijing, China
Canonical is a growing international software company that works with the open-source community to deliver Ubuntu, “the world’s best free software platform”. The Commercial Engineering Quality Assurance (QA) team works with all the engineering teams in Canonical, OEM and ODM customers, to bring Ubuntu directly to millions of users by delivering certified Ubuntu laptop, desktop, IoT and other computing devices.
As a Software QA engineer, you will join the team responsible for our strategy for quality coordination and testing. You will be a quality expert with extensive experience establishing quality processes from the ground up. You will understand the tools and techniques used to introduce new products, and will work with teams across the company to drive quality improvements through the entire development cycle.
Location: This is an office-based role in Beijing.
As a Software Quality Assurance Engineer you will:
Plan, create and manage the overall Quality Planning strategy and document
Improve our automated test capability with design and code contributions
Perform automated and manual testing of Ubuntu Desktop, Server and Core on varies latest hardware.
Suggest solutions to identified product problems
Collaborate with the Project team to ensure consistent project execution
Identify quality assurance process bottleneck and suggest improvements
Oversee continuous improvement projects
Collect quality data
Establish proactive measures to improve the quality and reliability of the Ubuntu platform
Prepare time estimates and schedule for testing activities
Identify, isolate, and document bugs clearly and concisely in the bugs database
Work with development teams across multiple projects to build efficient, effective automated testing
Communicate effectively with colleagues in a variety of time zones around the world
Triage test reports and customer bugs
The successful Software Quality Assurance Engineer will have :
Experience with the Linux desktop, and related technologies. Ubuntu experience would be a plus
Solid grasp of commercial Software QA practices and ideas on how to integrate them into Linux Community standards
Experience with common scripting languages, including Shell script, Python or JavaScript
Comfortable with online communication and collaboration such as mailing lists, Mattermost, wiki
Excellent logic, problem solving, and troubleshooting skills
Strong written and spoken communication skills in English
Ability to be productive in a globally distributed team
Ability to pick up new technologies and achieve high effectiveness quickly
What Canonical Offers:
Learning and development
Annual compensation review
Recognition rewards
Annual leave
Priority Pass for travel
Annual health check
About Canonical
Canonical is a pioneering tech firm at the forefront of the global move to open source. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. We are founder-led, profitable, and growing.
Powered by worldwide distributed collaboration since our inception in 2004, we believe tech and business leadership can emerge anywhere. We have no central headquarters. Most of us work from home, but we are exceptionally disciplined about this. We have very high expectations of all colleagues, and are champions of excellence. Working here is a step into the future and will challenge you to think differently, work smarter, learn new skills, and raise your game.
Canonical believes a diverse workforce enhances our ability to deliver world class software and services which meet the world’s computing needs. We are committed to ensuring equal employment opportunities to all qualified individuals. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Location: Remote (US)
About the company
Hi, we're Ondo Finance. Our mission is to provide institutional-grade, blockchain-enabled investment products and services. We have both a technology arm that develops decentralized finance technology, and an asset management arm that creates and manages tokenized funds. We are the global leader in tokenized treasuries, tokenized stocks and ETFs, and are building the future of institutional-grade financial services onchain.
Founded by folks from Goldman Sachs Digital Assets Team, we’re backed by some of the best investors in the world including Founders Fund, Coinbase Ventures, Pantera Capital, Tiger Global, and more. We are currently the leaders in the space in terms of AUM and are well capitalized to continue growing the firm. We're fully remote, with team members across the U.S.
About the role
We’re looking for a Senior iOS Engineer to help build Ondo’s mobile experience. You’ll own features from early product discussions through release and improvement, working closely with design, product, and engineers across the stack.
Financial software asks a lot of its interface. People need to understand what they own, what an action will do, and whether it succeeded. You’ll bring strong iOS judgment to those moments: making complex flows feel clear while treating security, accessibility, performance, and reliability as core parts of the product.
What you’ll do
Build and maintain native iOS features in Swift, from architecture and implementation through App Store release.
Partner with design and product to turn complex financial workflows into clear, responsive mobile experiences.
Shape how the app handles authentication, account state, transactions, errors, and interrupted flows.
Work with backend and platform engineers to define reliable app-facing contracts.
Improve quality through thoughtful testing, observability, code review, and attention to real user behavior.
Help set technical direction for iOS and mentor other engineers through collaboration and feedback.
What you bring
A track record of shipping and improving production iOS apps with Swift.
Strong command of SwiftUI and practical experience with UIKit where it serves the product.
Sound judgment about app architecture, asynchronous work, state management, networking, and persistence.
Experience designing for security, privacy, accessibility, and performance.
The ability to take ownership of an ambiguous problem, make clear tradeoffs, and bring others along.
Care for the details users notice and the failure cases they should never have to think about.
Experience with financial products, trading, digital assets, or wallets.
Experience building apps that handle sensitive account or transaction flows.
Familiarity with release automation, analytics, and crash monitoring.
What we offer
Competitive compensation including but not limited to salary, future token rights, and/or equity (according to your preferences) — We are well-funded and believe that great talent deserves great compensation.
Full benefits (medical, vision, and dental) and flexible vacation policy (PTO).
Remote-first team across many countries — You will be an early team member helping shape our vision, culture, and design practices.
A+ colleagues — Our team includes alumni from: Goldman Sachs, Blackrock, Two Sigma, Bridgewater, SpaceX, AWS, Meta, Google, McKinsey, Circle, Uniswap.
Best-in-class investors — We are proud to be backed by leading crypto experts and VCs, including Pantera Capital, Founders Fund and Coinbase Ventures.
Чем предстоит заниматься — участвовать в обеспечении качества продукта на всех этапах разработки и релизного процесса; — тестировать frontend и backend;
Задачи:
— разработка на Python с использованием asyncio, FastAPI
— работа с брокерами и таск-менеджерами: Kafka, RabbitMQ, Celery
— оптимизация запросов и проектирование схем в PostgreSQL
— реализация межсервисных коммуникаций через gRPC, REST, Webhooks
— написание фронтенд-компонентов на TypeScript и React
— применение DevOps-практик: Docker, CI/CD, развертывание в Kubernetes
— использование инструментов мониторинга Prometheus и Grafana
— обеспечение покрытия кода тестами
Требования:
— 3+ года коммерческого опыта на Python с глубоким пониманием asyncio, FastAPI
— опыт работы с Kafka, RabbitMQ, Celery
— уверенные знания PostgreSQL (query tuning, schema design)
— практический опыт межсервисных коммуникаций: gRPC, REST, Webhooks
— опыт написания фронтенд-компонентов на TypeScript / React
— понимание DevOps-практик: Docker, CI/CD, Kubernetes
— опыт работы с инструментами мониторинга Prometheus / Grafana
— культура покрытия кода тестами
— будет плюсом опыт работы с телеком-инфраструктурой, IP-телефонией, CTI или системами контакт-центров
Условия:
— full-time
— b2b-контракт
— почасовая оплата
— удалённая работа, строго по России
Location: Canada
What The Role Is
We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless.
Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting.
We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next.
Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help.
If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on.
What You'll Own
You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape:
Product recommendations across every surface.
Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them.
Personalizing the Feed.
Deciding which products, editorial content and social content each family sees, and in what order.
Personalizing search.
Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations.
Making Addie (our AI registry assistant) better at recs.
Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site.
In practice, you will:
Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric.
Make the modeling and architecture calls that span surfaces and are expensive to reverse.
Design the evaluation, offline and online, that tells us a model is good before and after it ships.
Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches.
Partner with product, design and data to help shape what's worth building.
Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Who You Are
You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey.
You bring:
Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias.
Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend.
An ability to take an ambiguous problem and start moving before anyone hands you the full picture.
A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings.
An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue.
AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next.
Compensation
We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is 299,300 to 372,600 CAD plus a target annual bonus of 20 percent of base. That's total target cash of roughly 359,160 to 447,120 CAD. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Location: United States
What The Role Is
We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless.
Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting.
We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next.
Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help.
If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on.
What You'll Own
You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape:
Product recommendations across every surface.
Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them.
Personalizing the Feed.
Deciding which products, editorial content and social content each family sees, and in what order.
Personalizing search.
Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations.
Making Addie (our AI registry assistant) better at recs.
Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site.
In practice, you will:
Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric.
Make the modeling and architecture calls that span surfaces and are expensive to reverse.
Design the evaluation, offline and online, that tells us a model is good before and after it ships.
Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches.
Partner with product, design and data to help shape what's worth building.
Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Who You Are
You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey.
You bring:
Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias.
Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend.
An ability to take an ambiguous problem and start moving before anyone hands you the full picture.
A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings.
An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue.
AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next.
Compensation
We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Location: Remote; Japan (Remote); Slovakia (Remote); Spain (Remote); Czechia (Remote); Switzerland (Remote); Estonia (Remote); Singapore (Remote); Mexico (Remote); USA (Remote); Israel (Remote); Kyrgyzstan (Remote); Bulgaria (Remote); Austria (Remote); India (Remote); Iceland (Remote); Hungary (Remote); Ireland (Remote); Canada (Remote); South Africa (Remote); Brazil (Remote); Finland (Remote); UK (Remote); Romania (Remote); Cyprus (Remote); Malta (Remote); Latvia (Remote); Argentina (Remote); Poland (Remote); Uruguay (Remote)
Workplace: Remote
WHO WE ARE
Hi, we're DuckDuckGo, the online protection company and remote-first team of 400+ on a mission to raise the standard of trust online. Founded in 2008 and profitable since 2014, our annual revenue is in the hundreds of millions USD and millions use our browser on Mac https://spreadprivacy.com/introducing-duckduckgo-for-mac/, Windows https://spreadprivacy.com/windows-browser-open-beta/, iOS https://spreadprivacy.com/duckduckgo-privacy-browser-ios14/, and Android https://spreadprivacy.com/introducing-app-tracking-protection/, our search engine https://duckduckgo.com/, and the DuckDuckGo subscription https://duckduckgo.com/pro. We also offer private, useful, and optional AI, including Duck.ai https://duck.ai/, which lets you chat privately with ChatGPT, Claude, and other AIs, all in one place.
Our culture https://duckduckgo.com/how-we-work of trust, inclusivity, and empowered project management underpins everything we do, where each team member takes full ownership of their projects, from scoping and execution to postmortem. If you're seeking end-to-end ownership of your work, you've come to the right place!
YOUR TEAM AND ROLE
Working on the Privacy Functional Team, you'll lead complex projects across key company-wide objectives. You'll protect the privacy of our users using Go, Node.js, Python, and (sometimes) Perl to write pragmatic, performant, testable code, and work on related projects. Potential projects include:
- Designing systems for improving our search indexes and AI features without compromising user privacy
- Building new features on top of our Tracker Radar https://spreadprivacy.com/duckduckgo-tracker-radar/ crawler to detect emerging privacy threats
- Implementing new privacy features and maintaining existing ones, such as our Web Tracking https://duckduckgo.com/duckduckgo-help-pages/privacy/web-tracking-protections and Email https://duckduckgo.com/duckduckgo-help-pages/email-protection/privacy Protections
As a Senior Privacy Engineer, you'll own major components of our privacy technology, taking responsibility for their maintenance and improvement over time. A key part of the role will also be participation in our privacy review and audit processes, ensuring that all product developments align with our privacy principles. In time, you'll formally mentor other engineers, supporting their career growth and the growth of the Privacy Team at DuckDuckGo.
ABOUT YOU
- Ability to lead and collaborate on high-impact and complex projects from proposal through post-mortem.
- Skills to wrangle vague problems, propose innovative solutions, and execute them effectively, involving others when necessary.
- Experience working on privacy solutions in an engineering capacity (e.g. tracker blocker, differential privacy, or similar technology).
- Deep technical understanding of online privacy threats and the existing solution space to protect against them.
- Proficiency in any of the following: Go, Node.js, Python, Perl.
- Excellent communication skills. You can validate your decisions and communicate them clearly to a variety of audiences, including non-technical stakeholders.
COMPENSATION
$178,500 USD annually and stock options. Compensation is transparent across the organization, and all team members within the same professional level and global region receive the same compensation.
Eligibility for company-sponsored health benefits is limited to team members based in the United States. This program does not extend to team members located in other countries, such as Canada or the UK.
Our Team Member Support Guide https://duckduckgo.com/assets/hiring/team_support_guide.pdf explains how we prioritize your wellbeing including paid parental leave, office setup, and co-working allowances.
HIRING PROCESS
Hiring works best when it's a two-way street. Learn how we help you get to know DuckDuckGo, envision your future role here, and find out more about how we hire https://duckduckgo.com/how-we-hire.
DIVERSITY, EQUITY AND INCLUSION
DuckDuckGo provides equal work opportunities to all team members and applicants, and it prohibits discrimination and harassment of any type on the basis of race, color, ethnicity, caste, religion, age, sex (including pregnancy), national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by our policies or federal, state, or local laws.
We want to ensure that our hiring process is accessible. If you need reasonable accommodation for any part of the application process because of a medical condition or disability, please send an email to careers@duckduckgo.com to let us know the nature of your request.
PLEASE NOTE THAT:
- You’ll be required to attend meetings on camera via video conferencing
- Expect to travel at least two times a year: once for our all-hands meetup and again for a team retreat (each around 4-5 days). While extenuating circumstances may impact attendance, everyone is strongly encouraged to attend.
- While we offer a flexible work arrangement with no core hours, expect an average full-time commitment of 40 hours per week.
- A successful candidate must pass a background check as a condition of joining the team.
- By applying for this role, you confirm that all information submitted is accurate and complete. You further acknowledge that providing false or fraudulent information during the application process is cause for denial of an offer, revocation of any existing offer, or other adverse action, up to and including termination after the start of your commencement of work.
Disclosure Statement: Use of AI in Hiring Process
As part of our commitment to enhancing our recruitment process, we utilize artificial intelligence (AI) technology to assist in reviewing and summarizing job applications and test projects, including those tools integrated into our recruitment vendor platforms. We use AI to flag potentially fraudulent applications, analyze and summarize applicants’ experience, interviews, and project performance, and help streamline our selection process.
Key Principles:
- Data Privacy: All information provided in your application will be handled in accordance with our Recruiting Privacy Policy https://duckduckgo.com/static-assets/files/pages/careers/DuckDuckGo-Recruiting-Privacy-Policy-effective-September-30-2025.pdf. We ensure that your personal information is protected and used solely for recruitment purposes.
- Human Oversight and Accountability: The AI technology is designed to support our hiring team by providing insights and summaries of applications and evaluations of test projects against scoring rubrics. All final evaluations and hiring decisions, however, will be made by our hiring team, who will consider the AI's input alongside other factors.
- Transparency: We believe in transparency regarding our hiring practices. If you have any questions about how AI is used in our recruitment process, please feel free to reach out to us.
By submitting your application, you acknowledge and consent to the use of AI technology in our review process. If you would like to request an alternative selection process, please contact us as at careers@duckduckgo.com. Thank you for your interest in joining DuckDuckGo!
#LI-DNI
Location: Remote, Canada; Remote, United States
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.
The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.
Co-create the future with us
as we build technology that transforms how the world develops software.
*
Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.
An overview of this role
Data Products integrates GitLab and third-party SDLC data, and builds the dashboards, APIs, and data products that turn it into trusted, interoperable intelligence for customers and internal teams.
This is a 0 to 1 team and we are hiring for a foundational engineering role. That means you bring technical leadership through ambiguity, helping figure out what to build, making the foundational design decisions, and keeping delivery moving while the picture is still forming. You own the full lifecycle of what ships and stand behind it.
What you'll bring
Proven ability to influence as a Staff owning product or platform systems end to end across multiple engineering and product teams.
High agency, i.e finds the owner, clarifies the path, makes the call, and keeps pushing until the work lands.
Force multiplier and raise the people and the codebase around them
Deep full-stack expertise, including strong proficiency in
Go, Ruby
and
Node
.
Depth in at least one of analytics and metrics platforms, graph data systems, CDC and warehouse integration.
Hands-on experience building production AI-powered tool orchestration.
Experience operating multi-tenant systems across SaaS and self-managed deployment.
Direct communicator who builds alignment across teams.
Bias to write things down and make reasoning legible.
What you'll own
Architect how GitLab and third-party data is ingested, modeled, and synced into the knowledge graph as a near-real-time graph of the development ecosystem.
Lead integration with external systems for business context (Jira, observability tools, Zendesk, ServiceNow), indexed into the graph.
Architect the Data Marketplace so customers consume GitLab data through Snowflake, Databricks, and BigQuery with no engineering dependencies.
Publish GitLab observability as OpenTelemetry and broker the data-sharing APIs.
Define operational readiness for everything the team ships across GitLab.com, Dedicated, and Self-Managed.
Translate an ambiguous 0 to 1 problem space into concrete, iterable roadmaps in partnership with Product, Design, and the graph backend team.
Resolve cross-team dependencies across graph backend, AI Platform, and Infrastructure without escalating everything upward.
Mentor senior and intermediate engineers through design reviews, pairing, and code review.
Create organizational leverage through speed. You identify systemic bottlenecks, simplify processes, and design systems that dramatically improve execution velocity.
About the team
Data Products work across three surfaces:
Dashboard and Reporting Framework
Builds AI-native dashboard components so customers and internal teams can see engineering health and GitLab's impact across DORA, VSA, AI Impact, SDLC trends, security, and quality, and launch their own custom dashboards on the same framework.
Internal Ingestion
Ingests third-party data into the GitLab and power tools like Knowledge Graph, building connectors so that signals from systems like Jira, Zendesk, ServiceNow, and observability tools become one queryable, near-real-time graph of the developer ecosystem.
External Ingestion
External makes GitLab and Knowledge Graph data consumable outside the product, through marketplace listings, data-sharing APIs and SDKs, and co-branded partner products.
We are a new team in a highly ambiguous, high-impact space, and we need engineers who can create clarity while building, make practical tradeoffs, unblock cross-team dependencies, and keep pushing until meaningful customer value lands.
The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our
benefits
and
equity
. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
United States Salary Range
$152,800
—
$259,200 USD
How GitLab Supports Full-Time Employees
Benefits to support your health, finances, and well-being
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Growth and Development Fund
Parental Leave
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from
underrepresented groups
are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
Country Hiring Guidelines:
GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.
Privacy Policy:
Please review our
Recruitment Privacy Policy.
Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also
GitLab’s EEO Policy
and
EEO is the Law
. If you have a disability or special need that requires
accommodation
, please let us know during the
recruiting process
.
☁️ Strong AWS experience: 3+ years designing cloud-native architectures on it. 🔧 6+ years architecting and running CI/CD (Jenkins, GitLab, GitHub Actions, Argo CD).
seniorCosta Mesa, United States; Relocation assistance is available to qualified candidates from other countries
ОфисOffice Based - Beijing, China
УдалённоseniorRemote (US)
Canada
United States
УдалённоseniorRemote; Japan (Remote); Slovakia (Remote); Spain (Remote); Czechia (Remote); Switzerland (Remote); Estonia (Remote); Singapore (Remote); Mexico (Remote); USA (Remote); Israel (Remote); Kyrgyzstan (Remote); Bulgaria (Remote); Austria (Remote); India (Remote); Iceland (Remote); Hungary (Remote); Ireland (Remote); Canada (Remote); South Africa (Remote); Brazil (Remote); Finland (Remote); UK (Remote); Romania (Remote); Cyprus (Remote); Malta (Remote); Latvia (Remote); Argentina (Remote); Poland (Remote); Uruguay (Remote)
УдалённоRemote, Canada; Remote, United States; The base salary range for this role’s listed level is currently for residents of the United States only
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