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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.

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. WHOOP is hiring a Sensor Intelligence Engineer II to join the Sensor Intelligence team and help advance the next generation of biomedical optical sensing technologies. In this role, you will translate optical sensing concepts into validated systems and algorithms that enable meaningful physiological insights for WHOOP members. Working at the intersection of AD, hardware, firmware, data science, and human physiology, you will combine theoretical modeling, hands-on experimentation, and data analysis to inform future sensing capabilities and product development. RESPONSIBILITIES: - Drive the evaluation and development of next-generation optical sensing concepts, including the definition of technical requirements, design tradeoffs, and validation criteria - Analyze raw time-series and multidimensional optical sensor data and construct signal processing work flows or platform for new physiological sensing etc. - Develop, validate, and improve physiological sensing principle using physics modeling and/or experimentation. - Analyze time-series and multidimensional biomedical sensor data to assess performance, identify artifacts and failure modes, and generate actionable recommendations for system and algorithm improvements - Develop or improve the multiphysics numerical simulation platform to optimize sensor performance or evaluate potential sensing concepts. - Collaborate with partners across Hardware, Firmware, Data Science, Research, and Product to communicate technical findings, influence design decisions, and translate research into scalable WHOOP capabilities QUALIFICATIONS: - Master’s degree or PhD in Electrical Engineering, Biomedical Engineering, Applied Physics, Optics, or a related technical field, or an equivalent combination of education and practical experience - 3+ years of relevant industry or research experience developing biomedical optical sensing systems, signal processing methods, or algorithms - Demonstrated depth in: Analyzing raw time-series and multidimensional optical sensor data, including but not limited to: PPG signal AC, DC, Perfusion Index, Systolic Foot, Systolic Peak, Dicrotic Notch, Diastolic Peak, Crest Time, Diastolic Time, etc. - Experience analyzing time-series or multidimensional data from biomedical sensors, such as PPG, ECG, IMU, EMG, acoustic sensors, or medical imaging systems - Proficiency in Python, C, or C++ for data analysis, algorithm development, prototyping, or system implementation, with the ability to communicate technical findings clearly and deliver high-quality work as requirements evolve - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. PREFERRED QUALIFICATIONS: - Familiarity with biomedical optics or biophotonics, with expertise in one or more areas such as diffuse optical spectroscopy, Raman spectroscopy, tissue optics, experimental optics, or a related field. - Experience with physiological sensing principles, understanding of the human circulation system and respiration system. - Hands-on experience designing, building, and characterizing optical sensing systems or laboratory experiments using components such as LEDs, lasers, photodetectors, lenses, collimators, and optical filters.

Location: Amsterdam Workplace: OnSite ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job   Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.   The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.   Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.   What you will do   - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   How We Work in Applied AI   - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it.   About you   - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch Why join us?   You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you! WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: London Workplace: OnSite ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. About The Job   Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.   The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.   Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.   What you will do   - You’ll individually help deploy into production use cases with a considerable business impact across various industries. - You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. - You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. - You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. - Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   How We Work in Applied AI   - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it.   About you   - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. - You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases - You have deep understanding of concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: - Contributed to open-source projects in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager - You have experience with deep learning with Pytorch Why join us?   You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you! WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Tbilisi, Georgia Workplace: remote At Infomediji, we are building the next generation of Spatial Media: a new way people experience video through interaction, multi-user presence, haptics, AI, and immersive storytelling. DeoVR is a leading immersive streaming platform serving millions of users globally. Content creators and partners are central to this ecosystem, and we are looking for a Product Manager to make their experience simpler, clearer, and more scalable. If you enjoy turning complex operational and technical workflows into products people genuinely enjoy using, this role is for you. The Role We’re looking for an experienced App Store Optimization (ASO) Manager on a pay-per-hour basis to take ownership of our app presence across the Meta Store, App Store, and Google Play. In this role, you’ll focus on boosting app visibility and downloads, driving growth through in-store tools, managing user reviews, and improving join flow. What You Will Do Own and manage our app presence across the Meta Store, App Store and Google Play Develop and execute ASO/SEO strategies (metadata, content, visuals) to maximize organic visibility and conversion rates. Monitor key app store metrics daily to quickly identify, diagnose, and resolve performance or conversion drops. Track app ratings and proactively manage user reviews to improve store sentiment. Streamline the join and onboarding flows to deliver a seamless user experience and boost conversion. Plan and execute in-app events, promotional features, and push campaigns to drive user engagement. Collaborate closely with Product and Design teams to refine in-app visuals, feature touchpoints, and user flows. Stay current with store policies, platform updates, and industry trends to deliver actionable market insights to stakeholders. What We Are Looking For Solid experience as an ASO Manager or in a similar role Strong understanding of app store algorithms (Apple App Store and Google Play), keyword optimization, and ranking factors Proactive, ownership-driven, and able to manage work independently Comfortable working in a fast-paced startup environment Fluent in English Bonus Points Experience working with Meta Store , Steam, PICO Store, etc. Hiring Process HR screening (30 min) HM Interview (30 min) Case Task (2-4 hours) CEO Interview (45 min) 💼 Explore our hiring process What We Offer Please note: fully remote pay-per-hour contract role. B2B only - work as an independent contractor with your own legal entity. The chance to be part of a pioneering team in a rapidly evolving industry Direct impact on the future of immersive media Flexible working hours and remote-first culture A team that values initiative, clarity, and collaboration Access to all tools and tech you need Unlimited DeoVR Premium A work environment where ideas matter and people are treated with respect Stay Connected Join our Facebook community and follow updates as we advance interactive VR experiences through cutting-edge technology. Join us and step into a role where legal expertise meets innovation.

Location: Buenos Aires, Argentina; Bangalore, India; Medellín, Colombia; Guadalajara, Mexico; Lahore, Pakistan; Manila, Philippines Workplace: fully We're a remote, product-focused startup building AI- and algorithm-driven systems. We're looking for a FullStack Engineer who can move fluidly between React frontends and Django backends. You'll own features end-to-end: from designing the data model, building the API, to crafting the UI that brings it all together. You'll work with a small distributed team across several countries, shipping fast and iterating based on real feedback. 💰 $100 Bonus Opportunity: Candidates who successfully complete the coding assessment and meet our quality standards may be invited to an additional evaluation stage. Candidates who successfully pass this stage and are selected to proceed to the final interview will receive a $100 bonus . To be considered for the assessment, please submit your resume through this job application. If your resume is approved, we’ll send you the coding assessment with further instructions. What You'll Do Build and ship complete features across React frontend and Django backend. Develop responsive web apps using React and Material UI (MUI). Design backend services and APIs using Python + Django (DRF or similar). Create clean, responsive UIs with React that connect to our services. Implement algorithmic/AI logic (scoring, ranking, decision rules) and surface it in the UI. Write pragmatic, production-ready code that ships fast and iterates easily. What We're Looking For Strong proficiency in React and Material UI. Attention to detail: You care about alignment, spacing, and how the app feels to the user. Comfortable designing and building RESTful APIs (bonus if you’ve used DRF or similar frameworks). Experience working on non-trivial business logic or algorithms (e.g., decision flows, scoring rules, optimization logic). Good instincts around performance : understanding query behavior, avoiding obvious pitfalls, and using caching when it counts. Ability to work independently in a remote environment and communicate clearly. Bonus Points For Comfortable coding with AI assistants (Claude Code, Cursor, etc.). Experience shipping complete products in startups, side projects, or hackathons. Background in algorithms or data-heavy systems. Experience with GCP, Redis, or Docker/Kubernetes. Familiarity shipping mobile apps with React Native. This role is a central piece of our product roadmap , and we're aiming to fill it quickly once we meet the right person. If it resonates with you, go ahead and apply now . Send us your resume to start the assessment process (and get a chance at the $100 bonus).

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 and live longer through a deeper understanding of their bodies and daily lives. WHOOP is seeking a Director of Embedded Software Engineering to lead our Firmware organization and the embedded software at the core of every WHOOP device. This leader will set the technical and organizational direction for Firmware, develop engineering managers and senior technical leaders, and ensure the organization delivers reliably across an ambitious roadmap of new products, platform investments, and continuous improvements to products already in the field. Firmware sits at the intersection of WHOOP’s hardware, sensing, algorithms, mobile software, manufacturing, and member experience. This role will lead multiple teams responsible for building stable, accurate, and power-efficient firmware platforms that operate continuously in highly constrained wearable devices. You will translate business and product priorities into clear technical strategies, build an organization capable of executing at scale, and strengthen the processes and platforms through which WHOOP develops and delivers firmware. RESPONSIBILITIES: - Lead and scale multiple Firmware teams with clear ownership and accountability, hiring and developing engineering managers, technical leaders, and senior individual contributors. - Set the multi-year strategy for firmware in alignment with product and business priorities. - Own predictable delivery across new products, platform investments, and sustaining work. - Raise the firmware development and quality bar through strong planning, architecture and design reviews, CI/CD, automated testing, validation, release practices, and field feedback. - Guide system architecture and major technical decisions that account for tradeoffs across member experience, power, performance, quality, cost, schedule, and long-term platform health. - Partner across Hardware, Sensor Intelligence, Algorithms, Mobile, Product, Manufacturing, Quality, and Program Management to bring products from concept through production and continuous improvement. - Establish meaningful engineering metrics and adopt tools and AI-enabled practices that improve quality and productivity. QUALIFICATIONS: - Proven experience leading multiple firmware or embedded software teams through engineering managers and senior technical leaders. - Extensive experience shipping firmware for high-volume, constrained products. - Deep technical fluency in C/C++, RTOS-based architectures, microcontrollers, device drivers, connectivity, low-power systems, and hardware-software integration. - Track record of setting firmware architecture and improving development practices, including planning, design reviews, CI/CD, automated testing, release management, and quality measurement. - Strong communication and leadership skills, with the ability to align Product, Hardware, Algorithms, Manufacturing, and senior leaders around clear priorities and decisions. - Bachelor’s or advanced degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field, or equivalent professional experience. Experience developing battery-constrained wearable products, physiological sensing systems, or other products in which firmware directly affects data accuracy preferred. - Familiarity with embedded security, secure boot, over-the-air updates, device identity, and production provisioning preferred. - Experience scaling engineering organizations in a high-growth environment and working with global suppliers or contract manufacturers preferred. Learn more about our Software Org and how to be successful in your engineering career at WHOOP via our Career Framework https://engineering.prod.whoop.com/careerframework.   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.   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 $220,000-$245,000. 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: Belgrade; London; Berlin Workplace: Hybrid The internet is vast, containing trillions of URLs. Perplexity’s crawling and storage system is complex and has multiple stages (URL discovery, crawling, parsing, indexing). Each stage offers many opportunities for improvement and room for intricate bugs. You’ll work at the intersection of data analysis and engineering — designing metrics, building data pipelines, and improving the quality of our search and answer systems. Responsibilities - Find and diagnose quality issues in our crawling pipeline - Train small models that optimize particular aspects of the pipeline (e.g. parsing quality) - Build datasets for model training, including LLM-as-a-judge labeling pipelines - Improve page selection algorithms for indexing - Design and analyze experiments to validate improvements Qualifications - 4+ years of experience as a data analyst, ML engineer, or in a related role - Strong coding skills: you should be able to write production-grade code at the level of a mid-level backend engineer - Experience designing metrics from scratch - Experience training ML models that shipped to production with measurable metric improvements Nice to have - Direct experience working on web crawling or indexing pipelines

Location: Belgrade; London; Berlin Workplace: Hybrid The internet is vast, containing trillions of URLs. Perplexity’s crawling and storage system is complex and has multiple stages (URL discovery, crawling, parsing, indexing). Each stage offers many opportunities for improvement and room for intricate bugs. You’ll work at the intersection of data analysis and engineering — designing metrics, building data pipelines, and improving the quality of our search and answer systems. Responsibilities - Find and diagnose quality issues in our crawling pipeline - Train small models that optimize particular aspects of the pipeline (e.g. parsing quality) - Build datasets for model training, including LLM-as-a-judge labeling pipelines - Improve page selection algorithms for indexing - Design and analyze experiments to validate improvements Qualifications - 4+ years of experience as a data analyst, ML engineer, or in a related role - Strong coding skills: you should be able to write production-grade code at the level of a mid-level backend engineer - Experience designing metrics from scratch - Experience training ML models that shipped to production with measurable metric improvements Nice to have - Direct experience working on web crawling or indexing pipelines

Location: London, England, United Kingdom About Wheely Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. Having recently launched in New York City, we’re expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you. About The Role We’re looking for a Senior Backend Engineer to join one of our teams that keeps frameworks lean and focuses on what matters: clean, maintainable code, shipped fast with TDD, DDD, and continuous integration and delivery. We are a Go shop, and while we’re busy migrating away from our Ruby monolith, our stack includes PostgreSQL, MongoDB, RabbitMQ, Redis, gRPC, and Thrift. Everything runs on AWS and Kubernetes, managed via Terraform. Our interview process includes a recruiter screen, algorithms, live coding and a system design section. Responsibilities Write high-quality, performant code primarily in Go. Implement new microservices while helping us responsibly manage and migrate away from legacy services. Work closely with product managers, designers, and data scientists to turn abstract requirements into concrete technical designs. Ensure our systems stay responsive under heavy load, optimising for both latency and reliability. Requirements 6+ years of experience building and maintaining scalable backend services. We use Go. If you know it, great. If not, we’ll interview you in your strongest language (Python, C++, Ruby.). In-depth knowledge of relational and NoSQL databases (PostgreSQL, MongoDB, Redis) and experience with message brokers like RabbitMQ or Kafka. Upper-Intermediate (B2) English proficiency or higher. You should be comfortable debating technical trade-offs with your peers. What We Offer Office-based role in West London, four days a week with flexible start and finish times, plus one remote day of your choice Salary starting from £120,000 Employee stock options plan Private medical and dental insurance Life and critical illness cover Latest-generation MacBook Pro and 4k display Monthly credit towards Wheely journeys Cycle to Work scheme Professional development stipend Relocation support, including visa sponsorship and allowance All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice

Location: Λευκωσία, Nicosia, Cyprus About Wheely Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. Having recently launched in New York City, we’re expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you. About The Role We’re looking for a Senior Backend Engineer to join one of our teams that keeps frameworks lean and focuses on what matters: clean, maintainable code, shipped fast with TDD, DDD, and continuous integration and delivery. We are a Go shop, and while we’re busy migrating away from our Ruby monolith, our stack includes PostgreSQL, MongoDB, RabbitMQ, Redis, gRPC, and Thrift. Everything runs on AWS and Kubernetes, managed via Terraform. Our interview process includes a recruiter screen, algorithms, live coding and a system design section. Responsibilities Write high-quality, performant code primarily in Go. Implement new microservices while helping us responsibly manage and migrate away from legacy services. Work closely with product managers, designers, and data scientists to turn abstract requirements into concrete technical designs. Ensure our systems stay responsive under heavy load, optimising for both latency and reliability. Requirements 6+ years of experience building and maintaining scalable backend services. We use Go. If you know it, great. If not, we’ll interview you in your strongest language (Python, C++, Ruby.). In-depth knowledge of relational and NoSQL databases (PostgreSQL, MongoDB, Redis) and experience with message brokers like RabbitMQ or Kafka. Upper-Intermediate (B2) English proficiency or higher. You should be comfortable debating technical trade-offs with your peers. What We Offer Office-based role in Nicosia, four days a week with flexible start and finish times, plus one remote day of your choice Competitive salary Employee stock options plan Private medical and dental insurance Daily Lunch allowance Latest-generation MacBook Pro and 4k display Professional development stipend Relocation support, including visa sponsorship and allowance All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice

Location: London, England, United Kingdom About Wheely Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. Having recently launched in New York City, we’re expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you. About The Role We’re looking for a Backend Engineer to join one of our teams that keeps frameworks lean and focuses on what matters: clean, maintainable code, shipped fast with TDD, DDD, and continuous integration and delivery. We are a Go shop, and while we’re busy migrating away from our Ruby monolith, our stack includes PostgreSQL, MongoDB, RabbitMQ, Redis, gRPC, and Thrift. Everything runs on AWS and Kubernetes, managed via Terraform. Our interview process includes a recruiter screen, algorithms and live coding. Senior+ candidates also complete a system design section. Responsibilities Write high-quality, performant code primarily in Go. Implement new microservices while helping us responsibly manage and migrate away from legacy services. Work closely with product managers, designers, and data scientists to turn abstract requirements into concrete technical designs. Ensure our systems stay responsive under heavy load, optimising for both latency and reliability. Requirements 3+ years of experience building and maintaining scalable backend services. We use Go. If you know it, great. If not, we’ll interview you in your strongest language (Python, C++, Ruby). In-depth knowledge of relational and NoSQL databases (PostgreSQL, MongoDB, Redis) and experience with message brokers like RabbitMQ or Kafka. Upper-Intermediate (B2) English proficiency or higher. You should be comfortable debating technical trade-offs with your peers. What We Offer What We Offer Office-based role in West London, four days a week with flexible start and finish times, plus one remote day of your choice Salary starting from £90,000 Employee stock options plan Private medical and dental insurance Life and critical illness cover Latest-generation MacBook Pro and 4k display Monthly credit towards Wheely journeys Cycle to Work scheme Professional development stipend Relocation support, including visa sponsorship and allowance All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice

Location: London, England, United Kingdom About Wheely Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. Having recently launched in New York City, we’re expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you. About The Role Our Marketplace team builds the models and algorithms that balance supply and demand, optimising pricing and matching to ensure chauffeurs earn and passengers aren't left waiting. We’re looking for a Mid/Senior Backend Engineer to join a team that keeps frameworks lean and focuses on what matters: clean, maintainable code, shipped fast with TDD, DDD, and continuous integration and delivery. We are a Go shop, and while we’re busy migrating away from our Ruby monolith, our stack includes PostgreSQL, MongoDB, RabbitMQ, Redis, gRPC, and Thrift. Everything runs on AWS and Kubernetes, managed via Terraform. Our interview process includes a recruiter screen, algorithms and live coding. Senior+ candidates also complete a system design section. Responsibilities Write high-quality, performant code primarily in Go. Implement new microservices while helping us responsibly manage and migrate away from legacy services. Work closely with product managers, designers, and data scientists to turn abstract requirements into concrete technical designs. Ensure our systems stay responsive under heavy load, optimising for both latency and reliability. Requirements 3+ years of experience (5+ years for seniors) building and maintaining scalable backend services. We use Go. If you know it, great. If not, we’ll interview you in your strongest language (Python, C++, Ruby). In-depth knowledge of relational and NoSQL databases (PostgreSQL, MongoDB, Redis) and experience with message brokers like RabbitMQ or Kafka. Upper-Intermediate (B2) English proficiency or higher. You should be comfortable debating technical trade-offs with your peers. What We Offer Office-based role in West London, four days a week with flexible start and finish times, plus one remote day of your choice Salary starting from £90,000 Employee stock options plan Private medical and dental insurance Life and critical illness cover Latest-generation MacBook Pro and 4k display Monthly credit towards Wheely journeys Cycle to Work scheme Professional development stipend Relocation support, including visa sponsorship and allowance All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice