Location: Sainte-Anne-de-Bellevue, Canada
📍
Location:
Sainte-Anne-de-Bellevue, QC, Canada
📄
Employment Type:
Full-Time
🏢
Work Arrangement:
Remote Opportunity for US and Canadian citizens and relocation assistance and bonus for UK and European citizens.
🚀
Start Date:
TBD
💰
Compensation:
TBD — based on skills and experience
Important Screening Requirements
Must have a
B.Sc. in Electrical Engineering, Aerospace Engineering, Physics, or a related field
.
10+ years of experience preferred
, but candidates with slightly less experience may be considered based on the strength and relevance of their
GNC/AOCS background
Strong experience in
orbital mechanics, attitude dynamics, and control-law design
.
Experience implementing
real-time filtering and control algorithms in embedded code
.
Hands-on experience with
navigation sensors and actuators
.
Strong aerospace systems engineering background.
Experience supporting
systems integration, testing, and troubleshooting
.
Experience with
Confluence and JIRA
.
Ability to work independently with limited supervision.
Excellent written and verbal communication skills in an
English and French work environment
.
About the Role
We are seeking a senior
Guidance, Navigation & Control (GNC) Systems Engineer
to support the design, integration, verification, and operational support of GNC subsystems for current and next-generation
remote sensing and communications satellites
.
This role spans the complete GNC subsystem lifecycle—from algorithm development and hardware implementation through integration, verification, and on-orbit operational support.
The ideal candidate brings deep expertise in
orbital dynamics, attitude determination and control, navigation, and real-time flight software integration
, while being comfortable working closely with subsystem and mission operations teams throughout the spacecraft lifecycle.
What We're Looking For
We’re looking for a senior GNC/AOCS systems engineer who can work across the
full spacecraft lifecycle
and bridge GNC algorithms, spacecraft hardware, flight software, systems engineering, integration, verification, and mission operations.
The ideal candidate goes beyond analysis and simulation, with hands-on experience translating GNC concepts into
integrated spacecraft systems
and supporting those systems through testing and on-orbit operations.
Key Responsibilities
Architecture & Requirements
Derive GNC functional, performance, and safety requirements from mission-level requirements.
Define requirements related to pointing accuracy, slew rates, orbit-maintenance ΔV, and fault tolerance.
Develop and maintain
System Requirements, Interface Control Documents (ICDs), and system description documentation
.
Manage requirements and maintain bidirectional traceability throughout the project lifecycle.
Modeling & Trade Studies
Conduct trade studies involving navigation sensor suites and actuator families.
Perform high-fidelity spacecraft dynamics simulations using
MATLAB/Simulink and STK
.
Develop and maintain error budgets.
Analyze control-law stability, fuel consumption, and survivability margins.
Evaluate GNC architectures and design alternatives.
Algorithm Development
Design and implement attitude-determination algorithms.
Develop orbit-determination solutions.
Develop control laws for:
3-axis stabilization
Slew maneuvers
Station keeping
Validate algorithms using
Monte Carlo analysis and worst-case scenarios
.
Support
Software-in-the-Loop (SIL)
and
Hardware-in-the-Loop (HIL)
testing on avionics test benches.
Cross-Functional & Systems Engineering
Translate GNC algorithms into requirements for real-time flight software.
Collaborate with C&DH and flight software teams on telemetry/telecommand, schedulers, and FDIR logic.
Present technical status, risk analyses, and trade-study results to senior management.
Negotiate and maintain ICDs with other spacecraft subsystems.
Support
Phase 0 and pre-Phase A
activities.
Hardware Selection & Design
Specify GNC sensor and actuator hardware.
Define electrical, mechanical, and thermal interfaces.
Conduct trade studies involving redundancy architectures.
Work with structures and thermal engineering teams to ensure appropriate mounting, thermal paths, and vibration survivability.
Review harness routing and power distribution for GNC electronics.
Integration & Verification
Develop Verification Plans, Test Matrices, and Validation Procedures for unit, subsystem, and spacecraft-level GNC testing.
Lead functional testing, including:
Sensor calibration
Actuator command-response testing
Closed-loop attitude-control testing
On-orbit checkout sequences
Conduct
FMEA, FTA, and reliability assessments
.
Support system integration and troubleshooting activities.
Technical Leadership & Documentation
Mentor and guide junior engineers and interns.
Serve as a technical liaison with customers, partners, and external vendors.
Contribute to continuous improvement initiatives, engineering standards, and organizational knowledge bases.
Support technology road-mapping and innovation activities.
Maintain GNC standards covering sensor/actuator interfaces, filter design, and control-law documentation.
Ensure analyses, software, deliverables, and technical documentation are properly version controlled.
Support major design reviews including
SRR, PDR, CDR, MRR, and TRR
.
On-Orbit & Operations Support
Support operational procedures for
detumble, orbit maintenance, safe mode
, and related GNC activities.
Provide real-time GNC support during
launch, early-orbit checkout, and contingency events
.
Analyze on-orbit telemetry and update filter parameters as required.
Generate GNC performance reports.
Support
Satellite Operations Handbook (SOOH)
development and operator training.
Required Qualifications
Bachelor’s degree in
Electrical Engineering, Aerospace Engineering, Physics, or a related field
.
10+ years of experience, but candidates with slightly less experience may be considered based on the strength and relevance of their GNC/AOCS background
Strong knowledge of:
Orbital mechanics
Attitude dynamics
Control-law design
Classical and modern optimal control
Experience with navigation sensors and actuators.
Experience implementing real-time filtering and control algorithms in embedded code.
Strong understanding of aerospace systems engineering fundamentals.
Hands-on experience supporting systems integration, testing, and problem resolution.
Experience with
Confluence and JIRA
.
Ability to work efficiently with limited supervision.
Strong analytical and problem-solving capabilities.
Excellent written and verbal communication skills.
Preferred Qualifications
Master’s degree
in Electrical Engineering, Aerospace Engineering, Physics, or a related field.
Specialized academic or professional background in
flight dynamics, control theory, or navigation
.
Experience across the complete spacecraft GNC lifecycle, from concept and algorithm development through integration and on-orbit operations.
Experience with
MATLAB/Simulink and STK
.
Experience with
SIL/HIL testing and avionics test benches
.
Experience with spacecraft
FDIR, telemetry/telecommand, and flight software integration
.
Experience supporting spacecraft design reviews and Phase 0/pre-Phase A activities.
Experience with GNC hardware interfaces, redundancy architectures, and spacecraft environmental considerations.
Experience conducting
FMEA, FTA, and reliability analysis
.
УдалённоПротиворечивые условия: Remote Opportunity for US and Canadian citizens and relocation assistance and bonus for UK and European citizens
Location: San Francisco, CA • New York, NY
Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
The Rendering & Animation team (R&A) builds the graphics engine which renders the canvas for all Figma applications. Our mission is to make rendering performant, feature-rich, reliable, maintainable and extendible across all products & surfaces. The team plays a core, bedrock role for the company because it underpins the technology driving the user experience, touching many other teams, and as such is one of the most impactful areas of Figma.
The R&A team is devoted to hiring individuals with graphics expertise. We are interested in a variety of sub-domains, including 2D GPU-driven rendering, computational geometry & vector graphics, animation frameworks, anti-aliasing algorithms, shader effects, and more recently branching into video/image processing. A PhD Intern specializing in any of these areas would be a phenomenal fit for the team with a lot of exciting projects available.
As an intern on our team, you'll take ownership of a high-impact project at the intersection of your technical strengths and our most pressing graphics, rendering, or media challenges. You'll work closely with your intern manager, team leads, and collaborators across 1–2 partner teams to deliver tangible results within your internship. This is an opportunity to do significant, portfolio-worthy work that directly supplies Figma's visual platform.
This is a 12 or 16-week internship role that can be held from one of our US hubs (San Francisco or New York) starting in May or June of 2027.
What you'll do at Figma:
Learn from industry graphics engineers and participate as an embedded team member of the Rendering & Animation team
Collaborate with engineers, PMs, designers, and researchers to scope and execute your work
Develop, validate, and document solutions from prototypes to production-ready systems
Drive projects that apply research insights to meaningful product challenges
Contribute to exciting domain areas; some examples: crafting and optimizing shaders for sophisticated effects, investigating improvements to anti-aliasing algorithms, improving media processing capabilities, animating spline interpolation, and more!
We'd love to hear from you if you have:
Current enrollment as a 4th or 5th year senior PhD student pursuing a PhD in Computer Graphics, Media Processing, or a related field
Experience working with OpenGL, WebGL, WebGPU, Vulkan or Metal and their respective shader languages (GLSL, WGSL) or other low-level graphics APIs
Proficiency in either C++ or Rust
A track record of rigorous problem-solving through academic or applied research, with experience thinking holistically about use cases and the low-level technology required
While it's not required, it's an added plus if you also have:
Demonstrated expertise in computer graphics, supported by publications at conferences such as SIGGRAPH, Eurographics, High Performance Graphics, NVIDIA GTC, or Pacific Graphics
Proficiency in WebAssembly, web graphics, 2D graphics, performance optimization, animation, geometry, or media
Interest in art and design applications
Experience using AI tools (e.g., GitHub Copilot, ChatGPT, Claude) to write, debug, and optimize code
Related industry experience via a past internship or full-time role
Strong communication and interpersonal skills, with demonstrated experience collaborating across functions
At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Pay Transparency Disclosure
This internship role is based in either Figma’s San Francisco or New York hub offices, and has the hourly base pay rate stated below. Figma also offers interns a housing stipend and travel reimbursement. Figma’s compensation and benefits are subject to change and may be modified in the future.
Internship
$74
—
$74 USD
At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an
equal opportunity workplace
- we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
,
or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to
accommodations-ext@figma.com
. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
Examples of accommodations include but are not limited to:
Holding interviews in an accessible location
Enabling closed captioning on video conferencing
Ensuring all written communication be compatible with screen readers
Changing the mode or format of interviews
To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with
Figma's Candidate Privacy Notice
.
Application limits:
To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles:
Candidates may submit up to 5 applications during any rolling 30-day period.
Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection.
Once the applicable days has passed, candidates are welcome to apply again.
Location: Mapbox Poland
Workplace: Remote
Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.
WHAT WE DO
The Navigation team https://www.mapbox.com/navigation at Mapbox develops and operates web services powering virtually all of Mapbox’s strategic navigation initiatives in consumer, automotive, and logistics verticals. We are a highly multidisciplinary organization, with work spanning distributed systems on AWS to geospatial localization, traffic telemetry, and mapping.
Collectively we are revolutionizing in-car experiences with technology to build fast, industry-leading maps and navigation for any vehicle. We’ve launched products such as MapGPT https://www.mapbox.com/mapgpt, Mapbox for EV https://www.mapbox.com/ev, and we’re enhancing the visual experience of in-vehicle navigation with 3D styling with our new Mapbox Standard through web and mobile SDKs. Mapbox has worked with automotive partners https://www.mapbox.com/automotive— including BMW, Toyota, and GM — to bring the best aspects of mobile app development into in-vehicle navigation and infotainment.
- Mapbox Blog: Introducing 3D Live Navigation https://www.mapbox.com/blog/mapbox-3d-navigation
- Mapbox Blog: Route Notifications Improve Driver Safety https://www.mapbox.com/blog/route-notifications-improve-driver-safety
- Mapbox Newsroom: AI Features in New Navigation SDK https://www.mapbox.com/press-releases/mapbox-unveils-ai-features-in-new-navigation-sdk
As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow.
WHAT YOU’LL DO
As a Machine Learning Engineer III on the Routing Cost team, you will lead the design, development, and delivery of highly trafficked recommendation systems for our routing cost engine. Your technical contributions will include:
- Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers).
- Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines.
- Build tools for automated quality assurance and data exploration.
- Leverage geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms.
- Partner with data scientists to make improvements to our models for determining patterns in movement and/or traffic.
- Mentor colleagues and participate in code and design reviews.
- Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends.
WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE
- 8-10+ years of backend and ML experience: Extensive hands-on experience showcasing expertise and a strong track record in the engineering field.
- Technical knowledge: Extensive experience with Python, distributed processing pipelines (Hadoop, Spark, Airflow, Dask), and very large datasets – statistical analysis, data quality control, optimizing storage.
- Cloud proficiency: Extensive experience with cloud and infrastructure services, including, as well as deploying and managing infrastructure in cloud environments.
- Operational excellence: You drive a culture of quality and continuous improvement in your organization. Strong passion for clean code and robust architecture, with a drive to elevate engineering practices and design standards across the team.
- Ownership & execution: Own the technical vision, lead the strategy and guide the team to execute towards building the future of our routing cost engine.
- Customer focus: You care deeply about your customers and their problems, and you work tirelessly to innovate on their behalf.
- Growth mindset: Have the humility to accept mistakes, learn and grow from them.
- Mentorship: Experience mentoring and leading engineering teams developing skill sets and career growth.
- Strong written and vocal communication skills: You can talk and write about complex ideas concisely to a wide audience. You are able to lead and resolve org-wide technical discussions and are able to collaborate and include input from cross-functional teams (security, devops, data, compliance and product).
- Data informed mindset: You believe in the value of data informed decision making and strive to measure things that are not straight forward but essential. You also have the right instincts to make speedy decisions in the absence of perfect & comprehensive data
WHAT WE VALUE
In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders:
- We value high-performing creative individuals who dig into problems and opportunities.
- We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people.
- We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.
- We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.
Our annual compensation for this role ranges from $102.000 - $153.000 (salaries are in USD). Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of the role).
By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here. Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application.
We are committed to a fair and equitable hiring process. We do not discriminate against any protected class.
Location: Finland; Mapbox Helsinki
Workplace: Remote
Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.
WHAT WE DO
The Navigation team https://www.mapbox.com/navigation at Mapbox develops and operates web services powering virtually all of Mapbox’s strategic navigation initiatives in consumer, automotive, and logistics verticals. We are a highly multidisciplinary organization, with work spanning distributed systems on AWS to geospatial localization, traffic telemetry, and mapping.
Collectively we are revolutionizing in-car experiences with technology to build fast, industry-leading maps and navigation for any vehicle. We’ve launched products such as MapGPT https://www.mapbox.com/mapgpt, Mapbox for EV https://www.mapbox.com/ev, and we’re enhancing the visual experience of in-vehicle navigation with 3D styling with our new Mapbox Standard through web and mobile SDKs. Mapbox has worked with automotive partners https://www.mapbox.com/automotive— including BMW, Toyota, and GM — to bring the best aspects of mobile app development into in-vehicle navigation and infotainment.
- Mapbox Blog: Introducing 3D Live Navigation https://www.mapbox.com/blog/mapbox-3d-navigation
- Mapbox Blog: Route Notifications Improve Driver Safety https://www.mapbox.com/blog/route-notifications-improve-driver-safety
- Mapbox Newsroom: AI Features in New Navigation SDK https://www.mapbox.com/press-releases/mapbox-unveils-ai-features-in-new-navigation-sdk
As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow.
WHAT YOU’LL DO
As a Machine Learning Engineer III on the Routing Cost team, you will lead the design, development, and delivery of highly trafficked recommendation systems for our routing cost engine. Your technical contributions will include:
- Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers).
- Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines.
- Build tools for automated quality assurance and data exploration.
- Leverage geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms.
- Partner with data scientists to make improvements to our models for determining patterns in movement and/or traffic.
- Mentor colleagues and participate in code and design reviews.
- Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends.
WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE
- 8-10+ years of backend and ML experience: Extensive hands-on experience showcasing expertise and a strong track record in the engineering field.
- Technical knowledge: Extensive experience with Python, distributed processing pipelines (Hadoop, Spark, Airflow, Dask), and very large datasets – statistical analysis, data quality control, optimizing storage.
- Cloud proficiency: Extensive experience with cloud and infrastructure services, including, as well as deploying and managing infrastructure in cloud environments.
- Operational excellence: You drive a culture of quality and continuous improvement in your organization. Strong passion for clean code and robust architecture, with a drive to elevate engineering practices and design standards across the team.
- Ownership & execution: Own the technical vision, lead the strategy and guide the team to execute towards building the future of our routing cost engine.
- Customer focus: You care deeply about your customers and their problems, and you work tirelessly to innovate on their behalf.
- Growth mindset: Have the humility to accept mistakes, learn and grow from them.
- Mentorship: Experience mentoring and leading engineering teams developing skill sets and career growth.
- Strong written and vocal communication skills: You can talk and write about complex ideas concisely to a wide audience. You are able to lead and resolve org-wide technical discussions and are able to collaborate and include input from cross-functional teams (security, devops, data, compliance and product).
- Data informed mindset: You believe in the value of data informed decision making and strive to measure things that are not straight forward but essential. You also have the right instincts to make speedy decisions in the absence of perfect & comprehensive data
WHAT WE VALUE
In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders:
- We value high-performing creative individuals who dig into problems and opportunities.
- We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people.
- We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.
- We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.
By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here. Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application.
We are committed to a fair and equitable hiring process. We do not discriminate against any protected class.
Location: Dubai
Workplace: hybrid
Social media is where most people meet Capital.com for the first time, and this role makes sure that first impression is calm, clear and useful. You’ll run organic social for the MENA region, including our Hindi-language channels, and own Capital.com’s global LinkedIn presence, setting the strategy, planning shoots, building our analysts’ and leaders’ profiles and growing the channel worldwide. We’re looking for someone socially native who knows how each platform works, why content lands, and wants to keep pushing us forward.
Responsibilities:
Global LinkedIn
Own the strategy.
Set and run Capital.com’s global LinkedIn strategy, calendar and cadence.
Make LinkedIn-native content.
Plan and produce shoots, carousels, short video, documents and polls built for the platform.
Grow thought leadership.
Build our analysts’ and senior leaders’ profiles, ghost-write and edit their posts, and coach them on what works.
Run newsletters and LinkedIn Live.
Launch and manage both around market events and analyst commentary.
Support employer brand.
Work with Employer Brand so the company page shows Capital.com as a great place to work.
Partner on LinkedIn Ads.
Brief creative and share organic insights with Performance Marketing.
Measure and report.
Track growth, engagement, reach and audience quality, and use the results to sharpen the approach.
MENA Social
Plan, create and publish content across Instagram, TikTok, YouTube, LinkedIn and X on a consistent calendar.
Adapt global campaigns so they feel locally relevant and stay true to the brand.
Manage our Hindi-language channels with regional stakeholders.
Brief designers, videographers and creators on platform-native content, especially short-form video.
Manage community engagement in line with our brand tone and conduct standards.
Support influencer and creator partnerships, from outreach to performance tracking.
Support paid social by briefing creative and flagging optimisation opportunities.
Brand, Innovation and Compliance
Be a brand guardian.
Make sure everything reflects our positioning, built for better decisions, and our calm, clear tone. Relevance over noise.
Keep us ahead.
Track platform changes, formats and competitors, then test, measure and scale new ideas.
Get compliance right.
Work with Compliance so content meets financial promotions rules in every market: SCA for MENA, and FCA, CySEC, ASIC and SCB for global LinkedIn, with risk warnings applied correctly on every channel.
Requirements:
3–5 years' experience managing social media for a brand, ideally in fintech, trading or another regulated financial services business.
You're socially native: a heavy, curious user of these platforms who understands how each algorithm and audience behaves.
Proven experience growing a brand or executive presence on LinkedIn, including thought leadership and B2B-style content.
Hands-on skills creating and editing platform-native content, including short-form video for TikTok, Instagram Reels and YouTube Shorts.
Strong writing in English, with the judgement to adapt tone for LinkedIn, short-form video and community replies.
Comfort with social analytics tools and the ability to turn data into clear content decisions.
Experience in the MENA market and an understanding of regional platform habits and audiences.
Familiarity with financial promotions rules, or a willingness to learn fast and work closely with Compliance.
Strong organisation and the ability to run several content workstreams and deadlines at once.
Nice to have:
Arabic and/or Hindi language skills.
Experience working with market analysts, economists or subject-matter experts on content.
Experience with LinkedIn newsletters, LinkedIn Live or LinkedIn Ads.
Basic design or editing skills (e.g. CapCut, Premiere, Canva, Figma).
What you will get in return:
Competitive Salary: We believe great work deserves great pay! Your skills and talents will be rewarded with a salary that makes you feel valued and motivated.
Work-Life Harmony: Join a company that genuinely cares about
you
—because your life outside of work matters just as much as your time on the clock.
Annual Performance Bonus: Your hard work doesn’t go unnoticed! Celebrate your achievements with a well-deserved annual bonus tied to your performance.
Generous Time Off: Need a breather? Our annual leave policy lets you recharge and enjoy life outside of work without a worry.
Employee Referral Program: Love working here? Share the love! Bring your talented friends on board and get rewarded for growing our awesome team.
Comprehensive Health & Pension Benefits: From medical insurance to pension plans, we’ve got your back. Plus, location-specific benefits and perks!
Workation Wonderland: Live your digital nomad dreams with 30 extra days to work remotely from anywhere in the world (some restrictions apply). Adventure awaits!
Volunteer Days: Make a difference! Take two additional paid days each year to support causes you care about and give back to the community
Location: Hybrid
About Us
At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.
At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.
Available Locations:
Austin, TX | Seattle, WA | Denver, CO
About the Department
The Deal Desk team is a critical component of the Finance function, acting as a strategic partner to the global Sales organization. We are responsible for partnering with sales to structure, negotiate, and close complex deals. We ensure that deals meet the requirements of "good business" while also keeping our customers' best interest in mind. We are committed to building a data-centric and AI-augmented Deal Desk that leverages predictive analytics and automated workflows to optimize pricing in real-time and automate routine approvals, allowing for deeper strategic focus.
About the Role
As a Deal Desk Manager, you will be the architect of our AI-driven deal desk, transitioning our sales process from manual workflows to an intelligent, automated engine that spans from initial scoping to final execution. By leveraging agentic workflows and automated data layers, the focus shifts to high-judgment architecture for non-standard enterprise deals. The objective is to serve as a high-influence "Sales Co-pilot," using AI-driven insights to maximize deal velocity and Long-Term Value (LTV) while relentlessly reducing friction through iterative process automation.
Responsibilities
Orchestrate Strategic Deal Architecture: Lead the structuring and execution of non-standard, high-value enterprise deals, providing high-judgment guidance that balances competitive differentiation with long-term business health.
Sales Co-pilot & Strategic Influence: Serve as a strategic partner to Sales leadership, utilizing AI-driven data to maximize deal velocity, improve LTV, and ensure discovery reflects true customer needs. Perform analysis on pricing and deal terms, leveraging AI insights to recommend "next best action" for deal structuring and margin optimization.
Curate and Tune AI Agents: Manage the enterprise deal approval ecosystem by tuning automated agents and models to ensure compliance and accuracy at scale.
Drive Process Iteration: Partner with cross-functional teams (Legal, Finance, Product) to build, streamline, and automate deal desk processes, architecting autonomous approval workflows and focusing on reducing field friction through relentless automation.
Champion AI & Automation Integration: Champion the integration of LLMs and generative AI tools to automate deal desk workflows, significantly reducing deal cycle times. Identify bottlenecks and implement AI-powered productivity solutions.
Desirable Skills, Knowledge, and Experience
6-8+ years of Deal Desk, FP&A, Revenue Operations, or similar experience, with a proven track record of supporting large-scale enterprise sales motions; 3+ years of deal desk experience preferred.
Financial & Sales Acumen: Solid understanding of SaaS metrics, pricing models, and financial concepts like ARR, Gross Margin, churn, and profitability. Experience with revenue recognition principles (e.g., ASC 606) is highly desirable. Experience selling software is a bonus.
Contract & Pricing Knowledge: Experience drafting and interpreting commercial contracts, with a focus on terms that impact revenue recognition and financial risk. Ability to analyze and recommend the best course of action for complex pricing and licensing situations.
Data & AI Literacy: Proficiency in leveraging agentic workflows and prompt engineering to scale influence, extract insights from large datasets, and automate repetitive operational tasks and internal documentation.
Algorithmic Thinking: The ability to understand and audit automated pricing models to ensure alignment with long-term company goals.
Strategic Influence: Demonstrated ability to navigate complex, cross-functional negotiations and make high-judgment decisions in fast-paced environments.
Process Design Mindset: A relentless focus on iterative automation and the ability to translate complex business policies into streamlined, automated logic.
Communication Excellence: Exceptional written and oral communication skills, capable of explaining complex deal structures and financial data to both technical and executive stakeholders.
Bonus Points
Experience in software sales or sales operations, providing a "boots on the ground" perspective of the sales cycle.
Deep knowledge of Cloud/SaaS infrastructure and the global cybersecurity competitive landscape.
If you're excited by fast-paced innovation, dedicated to driving global growth, and want to help build a better internet, we'd love to hear from you.
Application Deadline:
January 12, 2027
Compensation
Compensation may be adjusted depending on work location.
For Seattle based hires: Estimated annual salary of $147,000 - $202,000
For Denver based hires: Estimated annual salary of $134,000 - $184,000
Equity
This role is eligible to participate in Cloudflare’s equity plan.
Benefits
Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun! The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.
Health & Welfare Benefits
Medical/Rx Insurance
Dental Insurance
Vision Insurance
Flexible Spending Accounts
Commuter Spending Accounts
Fertility & Family Forming Benefits
On-demand mental health support and Employee Assistance Program
Global Travel Medical Insurance
Financial Benefits
Short and Long Term Disability Insurance
Life & Accident Insurance
401(k) Retirement Savings Plan
Employee Stock Participation Plan
Time Off
Flexible paid time off covering vacation and sick leave
Leave programs, including parental, pregnancy health, medical, and bereavement leave
What Makes Cloudflare Special?
We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.
Project Galileo
: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.
Athenian Project
: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.
1.1.1.1
: We released
1.1.1.1
to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our
privacy commitment
and ensure that no user data is sold to advertisers or used to target consumers.
Sound like something you’d like to be a part of? We’d love to hear from you!
Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs. More details about this will be available at that stage of the interview process.
This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.
Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual
race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law.
We are an AA/Veterans/Disabled Employer.
Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at
hr@cloudflare.com
or via mail at 101 Townsend St. San Francisco, CA 94107.
Location: GE; PL
Workplace: remote
Overview:
SOFTSWISS is looking for SEO Team Lead to manage a team of SEO Specialists and Link Builders, drive the SEO function forward, oversee key performance indicators, and ensure sustainable growth in organic search visibility.
Key responsibilities:
Manage a team of SEO Specialists and Link Builders: plan workloads, delegate tasks, track progress, and ensure high-quality execution
Participate in weekly sprint planning and assign tasks related to research, link building, web development, copywriting, and other SEO activities
Coordinate SEO reporting and KPI tracking for the team and the Head of Content Marketing
Regularly review, crawl, and audit company websites to maintain their technical health
Monitor target keyword rankings and take action to maintain and improve search visibility
Analyze competitor websites and share relevant insights with stakeholders
Monitor major Google algorithm updates and keep the team informed about upcoming changes, risks, and action plans
Lead the bi-weekly SEO Sync with the CMT, DMT, and R&A teams
Participate in ad hoc research initiatives and special SEO projects
Participate in the hiring and onboarding of new SEO Team members
Improve team processes, cross-functional collaboration, and the overall effectiveness of SEO operations
Required Experience:
5+ years of experience in SEO, up to 2 years of experience managing an SEO team
Strong understanding of SEO and SEM principles
Intermediate to advanced project management skills
Strong analytical and problem-solving skills
Hands-on experience with SEO tools such as Semrush, Ahrefs, SE Ranking or similar platforms
Experience with project management tools such as Jira, Asana, Trello, or similar
Experience with analytics and search tools, including GA4, Looker, and Google Search Console
Basic knowledge of Google Ads and HTML
Confident use of Google Workspace, including email and writing tools
Knowledge of ChatGPT and Generative Search Experience principles is a plus
Russian; English proficiency level B1 or higher.
Nice to have:
Relevant SEO certification
Knowledge of additional languages: Spanish, Portuguese
Experience working with WordPress.
Main Advantages
Private health insurance
Sports benefits
Comprehensive Mental Health Program
Free English lessons (online)
Local language courses
Paid time off
Maternity leave support
Referral program rewards
Upskilling, internal workshops, and participation in professional conferences and corporate events
Location: Boston, MA
Workplace: OnSite
At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies, behaviors, and daily lives.
WHOOP Labs is the on-site research facility for product development and innovation at WHOOP. We conduct human-centered hardware and algorithm research to create best-in-class product experiences that work for all members.
WHOOP is hiring a Researcher II to support research planning and execution on weekends, supporting critical data collection windows for participant diversity and expanded access. This role will cover a broad range of research studies for algorithm training, hardware validation, and design testing. While your home base will be WHOOP’s on-site product research facility, WHOOP Labs, studies will include field collections across the metro Boston area to widen access for diverse communities. Your efforts will support the organization as we continue to develop a best-in-class experience and lead the wearables industry.
*This role is fully onsite at our Boston, MA office and follows a 4x10 schedule, with four 10-hour workdays each week, Friday through Monday, and three days off Tuesday through Thursday.
RESPONSIBILITIES
- Execute testing protocols across multiple concurrent studies, owning research execution on weekends and collaborating with other researchers on Friday and Monday to ensure consistent protocol administration across all days and shifts.
- Own research documentation for weekend hours, collaborating with other researchers on Friday and Monday to ensure effective handoffs and information transfer across shifts.
- Provide coaching and guidance to participants during exercise protocols, balancing data integrity, research best practices, and participant experience
- Create a supportive and welcoming environment for participants engaging in a range of research tasks, from exercises to device interactions
- Manage the use, troubleshooting, and upkeep of sensitive data collection equipment and prototype devices
- Develop strong working knowledge of WHOOP’s research platform tooling suite, with the ability to troubleshoot issues in real time—including during active data collections—and problem-solve on the fly
- Develop junior researchers by providing technical coaching, delegation, constructive feedback, and growth opportunities
- Own daily lab management tasks required for data collections to be successful, such as laundry, equipment cleaning, material organization, and overall lab readiness
- Serve as an ambassador for WHOOP Labs and the WHOOP brand
QUALIFICATIONS
- Bachelor’s Degree in human physiology, biomedical engineering, psychology, HCI, or similar
- Professional experience in research & development, human subjects research, or a related field, including 2+ years of experience conducting human subjects research
- Strong technological background and working knowledge of data management systems including the Google Suite
- Familiarity with research platform tools and hardware testing environments preferred
- Strong interpersonal communication skills with a savvy for working as part of a highly collaborative, fast-paced team
- Ability to manage multiple priorities and adapt quickly in dynamic research settings
- Prior experience in customer service or other public-facing roles a plus
- Strong written, verbal, and presentation skills, with confidence giving and receiving feedback across disciplines
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $75,000 - $95,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.
About the project
The Project is a Smart City video-surveillance platform. The platform handles video conversion, integrates with storage, and uses an event-driven architecture. Deployed across several countries, it focuses on scalability, observability, and reliability.
Stack
Language & Frameworks: Kotlin, Spring Boot, Spring MVC, Spring Security
Database: PostgreSQL, ClickHouse, JPA / Hibernate, Spring Data JPA
Security: JWT, Spring Security, RBAC, permission-based authorization
Async: Kotlin Coroutines
Testing: JUnit, MockK, Testcontainers
Infra: Docker, Kubernetes, Linux
Monitoring: Prometheus, Grafana, logging, metrics, tracing
Docs: OpenAPI / Swagger
Responsibilities
Develop and maintain backend services in Kotlin / Spring Boot;
design and implement REST APIs and business logic;
work with PostgreSQL / ClickHouse, JPA / Hibernate and optimize database access;
identify and resolve N+1, lazy-loading and transaction-related issues;
design and implement RBAC and permission-based authorization;
implement tenant- and resource-level access control;
work with JWT authentication and Spring Security;
deploy and troubleshoot services in Docker / Kubernetes environments;
refactor and optimize existing Kotlin code;
write unit and integration tests;
participate in code reviews and backend architecture decisions.
Must-have
2+ years of commercial backend development experience with Kotlin / Spring Boot (Middle+ level);
strong Kotlin knowledge and good understanding of Java ecosystem;
production experience with Spring Boot / Spring MVC;
solid understanding of Spring IoC, DI, proxies and @Transactional;
practical experience with PostgreSQL and JPA / Hibernate;
understanding of persistence context, lazy loading, N+1 and dirty checking;
experience with Spring Security and JWT;
good understanding of roles, permissions and RBAC;
understanding of resource-level authorization and multi-tenant access control;
hands-on experience with Docker, Kubernetes and Linux;
ability to analyze and optimize existing code and database queries;
solid understanding of collections, algorithmic complexity and basic performance trade-offs.
Nice-to-have
ClickHouse production experience;
Kotlin Coroutines / Flow;
experience with high-load or distributed backend systems;
ABAC / policy-based authorization experience;
Testcontainers;
Kafka / RabbitMQ;
Kubernetes operations and troubleshooting;
Prometheus / Grafana / distributed tracing;
OAuth2 / OpenID Connect;
experience designing multi-tenant systems.
Offer
Strong engineering team and real impact on backend architecture;
modern Kotlin / Spring stack, CI/CD, Kubernetes and code reviews;
opportunity to work on security- and performance-critical backend components;
flexible schedule;
competitive compensation based on experience and interview performance.
Location: Berlin, Germany
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on.
Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production.
Your responsibilities
Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff.
Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization.
Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components.
Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost.
Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices.
Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets.
Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact.
Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs.
Must-haves
A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline.
A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas.
Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes.
Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs.
Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis.
Excellent written and verbal communication.
Nice-to-haves
First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA.
Experience deploying ML models or inference optimizations in production.
Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals.
Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency.
Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems.
Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP.
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Location: Zurich, Switzerland
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on.
Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production.
Your responsibilities
Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff.
Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization.
Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components.
Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost.
Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices.
Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets.
Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact.
Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs.
Must-haves
A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline.
A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas.
Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes.
Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs.
Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis.
Excellent written and verbal communication.
Nice-to-haves
First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA.
Experience deploying ML models or inference optimizations in production.
Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals.
Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency.
Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems.
Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP.
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Location: London, United Kingdom
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on.
Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production.
Your responsibilities
Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff.
Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization.
Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components.
Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost.
Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices.
Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets.
Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact.
Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs.
Must-haves
A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline.
A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas.
Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes.
Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs.
Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis.
Excellent written and verbal communication.
Nice-to-haves
First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA.
Experience deploying ML models or inference optimizations in production.
Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals.
Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency.
Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems.
Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP.
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Location: Boston, MA
Workplace: OnSite
At WHOOP, we’re on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep.
The Health team develops the algorithms and features that expand WHOOP's health sensing capabilities. The work spans women's health, software as a medical device, wellness and longevity, member insights, and emerging health signals. We combine continuous physiological data with clinical research and domain expertise to ship features that are scientifically grounded and useful to millions of members.
As a Staff Applied Machine Learning Scientist on the Health team, you will turn ambiguous clinical and product questions into defensible studies, models, and evaluation plans on WHOOP's longitudinal wearable and member data (physiological signals, behavioral logs, labs and integrations, and related streams). You will set the methodological bar for a Health domain. You will partner with Machine Learning Engineers on the path to production, and with Product, clinical, and Digital Health partners on what the data can and cannot support.
Success in this role requires applied algorithm and statistical craft, the judgment to operate across Health problem types, and Staff-level leadership: launching domain work independently, raising the quality and velocity of the people around you, and making clear prioritization calls under uncertainty.
RESPONSIBILITIES
- Lead the design, development, and validation of machine learning and statistical methods for Health features, using wearable physiological and behavioral data and related member sources.
- Frame ambiguous health and product questions into well-scoped modeling or study problems, with clear performance criteria, evaluation plans, and honest treatment of uncertainty and failure modes.
- Set the methodological and quality standard for a Health domain: reusable evaluation practices, review expectations, and documentation that others can inherit.
- Develop and refine approaches for time-series, longitudinal, and multimodal data, including data curation, labeling strategy, feature and representation choices, and offline evaluation that holds up under real-world noise, missingness, and population shift.
- Partner with Machine Learning Engineers to translate validated methods into production-ready systems, making modeling choices that account for scalability, reliability, latency, cost, monitoring, and (where relevant) controlled-release constraints.
- Serve as a technical counterpart to Product and Digital Health (clinical science, regulatory, quality): pressure-test performance requirements, study design, and evidence quality, and push back when a claim is not supportable.
- Raise the quality and velocity of the scientists and engineers around you through design reviews, mentorship, and the judgment of when to coach someone else to champion a problem versus taking it yourself.
- Communicate trade-offs, risks, and results clearly to technical, clinical, product, and leadership audiences; prevent misalignment early; drive decisions with evidence and a clear point of view on domain direction.
QUALIFICATIONS
- Master's or PhD (or equivalent professional experience) in Biomedical Engineering, Electrical Engineering, Computer Science, Applied Mathematics, Biostatistics, Bioinformatics, Physiology, or a related quantitative or health-science field.
- 7+ years of professional experience developing algorithms, applied ML models, or statistically rigorous analyses in health, wearables, medical devices, digital health, or a closely related domain.
- Demonstrated Staff-level technical leadership: setting methodological standards others reuse, influencing multi-team outcomes, mentoring senior ICs, and making prioritization calls under uncertainty. End-to-end project ownership alone is not sufficient.
- Strong foundation in statistics (Bayesian and frequentist) and machine learning for time-series and longitudinal data, with the ability to draw defensible conclusions from observational, noisy, or otherwise messy real-world data.
- Experience with wearable or physiological signals (PPG, IMU, HR/HRV, sleep, activity, temperature, or similar) or a closely related adjacent time-series domain.
- Hands-on experience designing studies or evaluation protocols end-to-end: data curation, metric choice, validation splits, subgroup and failure analysis, and documentation of assumptions and limitations.
- Strong Python skills with reproducible scientific / ML engineering hygiene (clean, reviewable code; comfort with stacks such as NumPy/SciPy/pandas, scikit-learn, PyTorch/TensorFlow).
- Clear, high-signal communicator who can move between deeply technical method discussions and cross-functional conversations with Product, clinical partners, and leadership.
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Location: Remote (USA)
Workplace: remote
Arcadia is the most trusted healthcare platform powering outcomes. We transform complex healthcare data into trusted intelligence, helping providers, payers, and life sciences organizations act with clarity, make confident decisions, and achieve measurable clinical, operational, and financial outcomes.
Built on a comprehensive data foundation spanning tens of millions of patient lives, Arcadia combines advanced analytics and responsible AI to surface meaningful insights, coordinate action, and improve performance at scale. Our approach to AI and automation is governed and transparent — designed to strengthen human expertise, not replace judgment or obscure responsibility.
Hundreds of organizations rely on Arcadia to improve cost, quality, and outcomes. Backed by Nordic Capital, we continue to invest in our platform, AI capabilities, and people as we pursue our purpose: helping healthcare deliver better outcomes for every person, every community, and every generation.
Why This Role Is Important to Arcadia
Customer Insights takes on the work that doesn't fit a one-size-fits-all product — custom data models, bespoke dashboards, registries, and long-running embedded programs — sitting between a platform and a plan.
This role is the first at Arcadia dedicated to Medicaid policy analysis, and it sits on one of our most visible accounts: a state Medicaid agency that is taking direct responsibility for a much larger fee-for-service population. A broader Arcadia team already serves the agency in a variety of ways — risk stratification, dashboards and reporting, quality measurement, and analytics on the state's Medicaid member and claims data — and that relationship is growing. You will work alongside that team and take the lead on the policy-driven analytic work: interpreting program rules and policy documents into analytic logic, and building the registries, data marts, and dashboards that put it to use.
That takes a rare combination: policy fluency to tell a customer what the data can and cannot support, customer presence to be trusted in the room with state program staff and partners, and the technical skill to build the deliverables yourself. We are looking for someone who can ramp on all three quickly. Just as important, this work moves at a pace that is only possible with AI-assisted development: you will be expected to pick up our AI coding and analysis tools quickly and use them heavily from your first weeks, with careful human review.
What Success Looks Like
In 3 months
Get productive quickly with the team's AI-assisted workflow — using AI coding and analysis tools to ramp into the state program's eligibility, claims, and provider data, the program rules and policy context behind it, and the analytic logic and deliverables already in production
Join customer and partner working sessions and begin contributing in the room — answering, in real time, what a proposed definition, threshold, or policy change does to the data and the member population
Independently deliver your first piece of work end to end — a stratification or registry refinement, a data mart component, or a dashboard — with your own policy interpretation and QA behind it
In 6 months
What You'll Be Doing
Medicaid policy analysis
Interpret state and federal Medicaid program rules, eligibility and aid-code structures, benefit and coverage design, and program guidance — translating them into precise, testable analytic logic (cohort definitions, code sets, exclusions, stratification criteria) and documenting the interpretation so decisions are auditable
Advise senior customer leadership on what the data can and cannot support — whether a proposed definition is measurable, what the volumes look like, what a threshold does to caseload, cost, or provider capacity — and anticipate how policy changes (fee-for-service transitions, waivers, provider network rules) affect the data and the questions ahead
Technical analytical delivery
Turn ambiguous policy and operational questions into member and provider data marts, cohort and stratification logic, and registry extracts — in SQL (and Python where needed) on Foundry and Redshift/Athena
Deliver them in the format the customer needs — dashboards, recurring reports, Excel, and leadership decks
Root-cause data-quality issues — reconcile counts across sources, trace bad fields to the source, and agree definitions for undocumented fields and codes with the customer's data staff
Customer presence and engagement
Serve as the senior analytic voice for state program leadership, policy and data staff, prime contractors, and vendor partners — participating in recurring working sessions and translating between policy, operational, and technical audiences
Set priorities, scope, and timelines with Customer Management, and hold real authority to push back on what is and isn't feasible or worth building
Create client-facing materials — leadership summaries, detailed methodology decks, decision memos, technical explainers — tailored to audiences from highly technical data counterparts to policy and executive stakeholders
What You'll Need To Have
Working knowledge of how health programs and managed care plans work, and the ability to turn policy documents and program rules into analytic logic. Direct Medicaid or managed care plan experience is a plus
Clinical code and claims fluency — ICD-10, CPT/HCPCS, and revenue codes to build clinical cohorts; claims, eligibility, and provider/NPI data (NPPES, enrollment files); and judgment about claims timing and completeness
Hands-on, demonstrable fluency with AI coding and analysis tools (Claude Code, Cursor, or similar) as the core of how you work. Picking these tools up quickly and using them heavily is central to how you will onboard and how much you can deliver in this role. Be ready to show us what you have built with AI assistance, how fast you turn work around, and how you review and validate it
Advanced SQL (CTEs, window functions, performance on large claims and eligibility tables) and data modeling, to a real engineering standard
Hands-on experience building dashboards and reports in a BI tool (QuickSight, Power BI, Tableau) and Excel, plus executive-ready decks
Direct customer-facing experience with senior stakeholders — comfortable scoping ambiguous requests, navigating competing priorities, and exercising sound analytical judgment about what to build and what the data can support, on short timelines and without close oversight
A track record of leading an analytic program end to end for senior customer or executive audiences — setting your own priorities, and operating without a project manager or close direction
Sound judgment with sensitive data and PHI
What “Principal” means here
This is the most senior analytic role on the Customer Insights team. It is expected that you can:
Set your own priorities and make the call with incomplete information
Act as the senior analytic voice with agency and partner leadership
Raise the bar for the analysts around you — through standards, review, and example
Don't need a project manager or close direction
We are hiring for the combination of policy fluency, customer presence, and technical skill — we understand candidates may be strongest in one or two of these areas and will build the rest quickly, and speed of ramp matters more to us than any one credential. Tell us where you are strongest and how you have ramped before.
Would Love For You To Have
Direct experience with a state Medicaid agency, a Medicaid-serving prime contractor or consultancy, or a Medicaid managed care plan — California Medi-Cal experience is a real plus
Familiarity with population health concepts: risk stratification, registries, care management, network adequacy, and access and equity analysis
Experience with Python and dbt; familiarity with the AWS ecosystem and its analytics tools (e.g., Athena, Redshift, QuickSight); comfort with orchestration tooling, Jira, Confluence, and GitHub-based workflows
Experience mentoring less experienced analysts
Note: this list spans skills relevant to several facets of the role — we don't expect any given candidate to have all of them. Bring what you have; we'll talk through the rest during the interview process.
What You'll Get
Become a member of the talented, energized, diverse and purpose-driven Arcadian Community with decades of collective experience in population health, product development, and data science
Employee driven programs and initiatives for personal and professional development
A flexible, remote-friendly company with personality and heart
Competitive Compensation, Amazing Benefits including Unlimited FTO
The opportunity to:
Be the senior analytic and policy voice on a high-visibility state Medicaid program serving millions of members, at a pivotal moment for the program
Build the practice — the methodology standards, playbooks, and data assets a growing team will inherit — on problems where analytic choices directly shape which members get reached and how care is delivered and funded
About Arcadia
Arcadia.io helps innovative providers and payers across the country transform healthcare to reduce cost while improving patient health. We do this by aggregating large amounts of disparate data, applying algorithms to identify opportunities to provide better patient care, and making those opportunities actionable by physicians at the point of care in near-real time. We are passionate about helping our customers drive meaningful outcomes. We are growing fast and have emerged as a market leader in the highly competitive population health management software market and have been recognized by industry analysts KLAS, IDC, Forrester, and Chilmark for our leadership. For a better sense of our brand and products, please explore our website.
Protect Yourself
If you have concerns about the authenticity of a job offer or recruitment-related communication claiming to be from Arcadia, verify it by calling us directly at (781) 202-3600 and selecting option 3. You can find more information at Arcadia Careers.
In this role, you are responsible for following all security policies and procedures to protect all PHI under Arcadia's custodianship, as well as Arcadia intellectual property. For security-specific roles, the hiring manager defines any additional responsibilities.
Arcadia does not discriminate based on race, color, sex (including pregnancy and related conditions, sexual orientation, or transgender status), national origin, religion, age (40 and older), equal pay, disability or genetic information (including family medical history or genetic tests or services), and retaliation for filing a charge, reasonably opposing discrimination, or participating in a discrimination lawsuit, investigation, or proceeding.
Location: Boston, MA
Workplace: OnSite
At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives.
The Health team develops the algorithms and features that expand WHOOP's health sensing capabilities. The work spans women's health, wellness and longevity, member insights, emerging health signals, and software as a medical device. Applied ML Scientists and ML Engineers work as a production unit: scientists own problem framing and modeling; engineers own the path to production.
As a Senior Manager, Machine Learning on the Health team, you will own delivery and people outcomes across a mixed team of scientists and engineers. You will translate department strategy into clear quarterly plans, develop senior ICs (and, as the team grows, the next layer of managers), hire against a high bar for both crafts, and partner with Product and adjacent Health partners on what is worth building and what the data can support. You will stay close enough to the ML lifecycle to evaluate the team's most important decisions without becoming the default contributor.
Success in this role requires enough ML and health-domain fluency to earn trust from senior ICs, plus the people-leadership skill to grow that team, hold delivery across multiple workstreams, and make prioritization calls under uncertainty.
RESPONSIBILITIES:
- Own delivery, team health, and people outcomes across Health ML workstreams on a mixed Applied ML Scientist and ML Engineer team.
- Translate department strategy into quarterly plans, milestones, and success criteria; keep the team on the highest-leverage work and adapt deliberately as priorities shift.
- Build the team: lead hiring across science and engineering roles, calibrate the bar for each craft, and shape onboarding, leveling, and growth practices.
- Develop the next layer of leadership: coach senior ICs (and managers, as the scope grows), manage performance with clarity and care, and create the conditions for people to operate above their level.
- Set the standard for how Health ML gets built: work quality, evaluation rigor, review practices, and an operating model that holds as people and workstreams change.
- Partner directly with Product (and with clinical, software, and Digital Health partners as the work requires) to align on roadmap, evidence, and sequencing; broker trade-offs between iteration speed, scientific integrity, and member value.
- Own the risk posture for the team: anticipate execution, technical, and people risks, design mitigation into how the team operates, and keep senior leadership clearly informed of the most consequential decisions.
- Define and own the operating model: planning cadences, design reviews, decision forums, and quality gates appropriate to member-facing health ML.
- Build and continuously raise AI-enabled workflows that create measurable leverage across the team, for development, evaluation, documentation, and stakeholder communication.
- Represent the team's work credibly to executive and cross-functional audiences with brevity, evidence, and clarity.
QUALIFICATIONS:
- 7+ years of experience in machine learning, applied science, or software engineering, with 3+ years managing engineering and/or science teams.
- Bachelor's degree in Computer Science, Engineering, Applied Math, Biomedical Engineering, or a related field; advanced degree preferred.
- Demonstrated track record managing highly senior ICs: hiring, performance management, and developing people who in turn raise the bar around them.
- Deep familiarity with the ML development lifecycle (data collection, model training, evaluation, validation, deployment, and monitoring), sufficient to evaluate the most important technical and methodological decisions the team makes.
- Experience shipping algorithms or ML-enabled product in health, wearables, digital health, or a closely related applied domain.
- Demonstrated ability to set direction and make timely prioritization calls under uncertainty, keeping team focused on the highest-leverage work.
- Demonstrated AI-tooling sophistication: a track record of building or adopting AI-enabled workflows that materially improved team speed, quality, or decision confidence.
- Clear, high-signal communicator who can move fluidly between technical ML discussions and executive-level summaries of risk, trade-offs, and direction.
- Depth in a Health domain WHOOP already works preferred (member insights, women's health, cardiometabolic or respiratory health, sleep, strength / healthspan, neuroscience, or related physiological time-series work).
- Preferred experience as a counterpart to Product on ambiguous health or member-insight problems: scoping, sequencing, and pushing back when a claim is not supportable.
- Familiarity with clinical validation, evidence packages, or Digital Health partnership on higher-stakes regulated health features preferred.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $170,000 - $230,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.
Learn more about WHOOP https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg.
Location: Hamburg
Workplace: Hybrid
adjoe builds the technologies behind mobile apps growth and monetization. With our core product Playtime Arcade, we've become the global leader in rewarded advertising, an ad unit built on a simple premise: users earn real in-app rewards for engaging with new apps. The result is one of the most effective value exchanges in adtech, connecting advertisers and publishers with over 770 million users annually.
Investigating 770 Million User Interactions Across a 100TB Data Lake
When a platform serves 770 million users, every optimization from reward mechanics to SDK integrations needs to be grounded in data. The Rewarded Analytics team builds the internal dashboards, alerting systems, and data pipelines that monitor the user funnel, traffic engagement, and reward consistency.
SQL and Python power deep-dive investigations and automated 100 terabyte-sized data analyses queried through Trino. Using Tableau as the main visualization tool, stakeholders have access to real-time insights on the product performance. Airflow orchestrates the pipelines that keep everything up to date. This team provides the data that turns questions into answers: every A/B experiment the product team runs, every anomaly a publisher flags, and every new SDK integration. These answers guide all the business decisions.
Your Mission & Who We Are Looking For:
- Data analyst with a strong technical foundation. You have 5+ years as a Data Analyst and work fluently in both SQL and Python, writing complex queries, big data optimizations, and analysis pipelines to support product and growth initiatives.
- Master of experimentation and A/B testing. You have deep experience designing experiments, calculating sample sizes, managing variance reduction techniques, and analyzing A/B/n tests to ensure statistically sound business decisions.
- Statistically grounded. You can reason confidently about core statistical concepts—hypothesis testing, confidence intervals, p-values, power analysis, and Bayesian vs. Frequentist approaches—and apply them to real-world product decisions.
- Not a stranger to anomaly detection. You have experience working with anomaly detection algorithms and approaches like distribution analysis and cross-population comparison to monitor test guardrail metrics and identify unexpected shifts in experiment data.
- You own the systems, not just your slice. You understand the end-to-end telemetry and feature flagging systems that power experimentation. You can speak to data flows, event tracking pipelines, architecture tradeoffs, and why things were built the way they were.
- Automation-minded across the stack. You think beyond one-off test analyses and build automated experiment reporting dashboards, reusable analytical frameworks, and data visibility solutions. Experience with dbt, Airflow, or experiment platforms (e.g., Optimizely, GrowthBook) is a strong plus.
- Collaborative and business-aware. You work closely with product managers, engineers, and growth leads to translate complex statistical results into clear, actionable recommendations that drive executive decision-making.
🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.
What’s in It for You?
At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day.
- Go Big. Own projects with impact on 770M users and push adtech boundaries.
- Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.
- Be Direct. Solve problems openly and collaborate across teams.
- Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.
- Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.
We welcome applications from people who will contribute to the diversity of our company.
СтажёрSan Francisco, CA • New York, NY
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