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Zадачи: — Kiruvchi va chiquvchi qo‘ng‘iroqlar bilan ishlash; — Mijozlarga to‘g‘ri va tezkor javob berish; — Mas’uliyat bilan ishlash. Tребования: — Kamida 6 oy sotuv tajribasi; — AmoCRM’da ishlay olish; — Rus tilini bilish afzallik bo‘ladi. Условия: — Ish vaqti: 9:00 dan 19:00 gacha; — Ish turi: Offline; — Manzil: Toshkent shahri, Olmazor tumani, 2-tug’riqxona ro’parasi; — Maosh: 3 000 000 – 8 500 000 (sotuv natijasiga qarab); — Qiz bola xodim kerak.

Location: European Union; Moldova; Latvia; Slovakia; Croatia; Czech Republic; Slovenia; Romania; Spain; Bulgaria; Poland; Hungary; Montenegro; Estonia; Ukraine; Lithuania; Greece; Bosnia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE We are looking for a Senior User Acquisition Manager to take full ownership of paid search acquisition on Google Ads and Microsoft Ads (Bing) for one of our consumer apps. You will run the channel from end to end and be the person accountable for how it grows. This is a senior, hands-on media buying role with end-to-end ownership. You will own the whole paid search acquisition process: strategy, account structure, keywords and queries, bidding, budget allocation, ad and landing page testing, measurement, scaling and account health. You decide what to test, what to scale and what to cut, and you are accountable for the results. We need someone who has scaled Google and Microsoft Ads at volume, who has promoted mobile and web apps profitably, who knows how to grow under strict platform policies, and who can operate independently on large budgets. You will manage performance against real revenue data (CPA, ROAS, payback, LTV and cohorts), not surface-level platform metrics. We also work AI-first, and we expect you to use Claude and automation to move faster. KEY RESPONSIBILITIES - Own the process end to end: take full ownership of paid search acquisition across Google Ads and Microsoft Ads (Bing): planning, launch, optimization, scaling, reporting and documentation. - Promote the app: run both web and app acquisition campaigns, including Google App Campaigns for installs, in-app events, subscriptions and purchases on iOS and Android, and optimize toward in-app value rather than installs alone. - Scale spend profitably while holding payback, ROAS and CPA targets based on real revenue and customer-value data. - Build and optimize account structure, keyword and match-type strategy, negative keywords, conversion events and value-based bidding (tCPA, tROAS, Maximize Conversion Value). - Run and scale Search, Performance Max, Demand Gen and App campaigns on Google, and Search, Performance Max and Audience campaigns on Microsoft Ads. - Decide budget allocation across Google and Microsoft and between brand, non-brand and competitor campaigns, and find new scaling levers: queries, geos, devices, audiences and campaign types. - Run a structured, high-velocity testing process on ad copy, assets, landing pages and bidding strategies, with clear hypotheses and kill/scale rules. - Manage signal quality: conversion tracking, enhanced and offline conversions, conversion value import, Consent Mode, attribution and MMP data, including iOS privacy-driven measurement (SKAdNetwork / ATT). - Own policy and account health: keep ads, keywords and landing pages within Google and Microsoft policies, handle disapprovals, appeals, suspensions and advertiser verification, and build prevention-first processes so issues are caught before launch. Maintain ad account structure, backups and recovery plans. - Work with platform reps on betas, new campaign types and escalations. - Diagnose drops and spikes quickly, including auction, query-mix and competitor changes, and act on them. - Document tests, learnings and playbooks, and use Claude and automation (scripts, the Google Ads API, rules) to speed up builds, QA, reporting and optimization. QUALIFICATIONS MUST-HAVE EXPERIENCE - 5+ years of hands-on paid search / user acquisition experience. - Proven experience promoting both web conversion campaigns and mobile apps on Google: App Campaigns for installs and in-app event / value optimization, App Store and Google Play funnels, and iOS and Android measurement. - Strong hands-on Google Ads experience scaling accounts profitably across Search, Performance Max and App campaigns. - Strong hands-on Microsoft Ads (Bing) experience, adapting campaigns to Microsoft rather than only importing them from Google. - Deep knowledge of smart and value-based bidding, keyword and match-type strategy, and search term mining. - Hands-on conversion tracking setup: GA4, Google Tag Manager, enhanced and offline conversions, and Consent Mode. - Experience with MMPs (AppsFlyer, Adjust, Singular or similar) and with SKAdNetwork / ATT-era measurement. - Direct, hands-on ownership of paid search budgets of $1M+/month. - Strong understanding of subscription / app economics: LTV, ROAS, payback windows, cohorts, and value-based optimization. - Policy and account health experience: disapprovals, appeals, suspensions, advertiser verification and how to recover and prevent them. - Strong testing discipline and measurement rigor. - Daily use of Claude or other AI tools for campaign builds, analysis and reporting. - Ownership mentality: you run channels end to end with minimal supervision and take responsibility for outcomes. NICE TO HAVE - Experience with Apple Search Ads. - Experience with Google Ads scripts, the Google Ads API or automated bidding and reporting tools. - Experience with AI or consumer-subscription products. - Experience with web-to-app subscription funnels. - Experience working under strict platform policy (subscription disclosure, ROSCA-type rules). LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

RELOCATION TO MONTENEGRO OR REMOTE | PREQUEL We’re looking for a Senior iOS Developer to join the Prequel team and take ownership of features end-to-end – from clarifying requirements with Product, Design, and Analytics to designing the technical solution, estimating and breaking down tasks, implementation, stabilization, and release.

Сейчас в команду ищут арт-директора, который возьмёт на себя развитие визуального языка бренда, обеспечит целостность коммуникаций во всех каналах и поможет вывести качество креативных материалов на новый уровень. Обязанности: Развивать визуальную айдентику и дизайн-систему СберМобайла, поддерживать и актуализировать брендбук и гайдлайны.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE We're hiring an experienced Performance Marketer to own and scale paid search and emerging AI advertising channels at LangChain, starting with Google Ads, Bing (Microsoft Advertising), and ChatGPT. You'll own the entire paid acquisition experience, from developing channel strategy and building campaigns to optimizing landing pages, improving conversion rates, and driving qualified pipeline. This is a highly hands-on role. You'll be the person building campaigns, analyzing performance, testing creative, improving landing pages, and identifying new opportunities to scale. We're looking for someone who combines deep paid search expertise with a willingness to experiment with emerging advertising platforms. You should be comfortable managing significant budgets, making data-driven investment decisions, and connecting advertising performance to downstream pipeline rather than just clicks, leads, or conversions. WHAT YOU'LL OWN PAID ACQUISITION STRATEGY AND PIPELINE - Own the strategy across Google Ads, Bing, and ChatGPT advertising, with the opportunity to expand into additional AI-native advertising channels. - Develop channel-specific strategies based on audience intent, available targeting capabilities, and expected pipeline contribution. - Own budget allocation, forecasting, and performance against pipeline targets. - Balance investment across branded, non-branded, competitor, and product-specific campaigns, along with emerging AI advertising opportunities. - Identify opportunities to scale high-performing campaigns and build repeatable playbooks for new channels. - Develop testing roadmaps across audiences, messaging, bidding, conversion experiences, and new advertising formats. END-TO-END CAMPAIGN EXECUTION You'll own campaign execution across all three channels: - Google Ads: Build, launch, and manage campaigns across branded, non-branded, competitor, and product search, including keyword research, match types, negative keywords, bidding, and budget optimization. - Bing / Microsoft Advertising: Develop and manage campaigns tailored to Microsoft's search audience, identifying opportunities to extend reach and capture incremental high-intent demand. - ChatGPT advertising: Develop and execute an early advertising strategy, testing available placements, audience approaches, messaging, and conversion experiences as the platform evolves. - Creative and messaging: Write and test ad copy in partnership with Product Marketing, adapting messaging to each channel and its user intent. - Experimentation: Run structured tests to improve acquisition efficiency, traffic quality, and pipeline conversion. - Campaign operations: Own campaign setup, tracking validation, launch readiness, troubleshooting, and day-to-day optimization. PAID CONVERSION EXPERIENCE AND WEBSITE OPTIMIZATION - Own the website conversion experience for traffic acquired through Google, Bing, and ChatGPT. - Build and optimize dedicated landing pages for paid acquisition campaigns using Webflow or similar tools. - Develop and execute A/B tests across landing page messaging, layouts, CTAs, and forms. - Identify friction across the full user journey, from ad interaction to product sign-up, demo request, or meeting booking. - Optimize conversion paths for both developers exploring LangSmith and enterprise buyers evaluating commercial solutions. - Partner with Marketing Operations to improve form conversion, qualification, routing, and meeting booking. - Ensure landing page experiences reflect the user's intent and context across different advertising channels. MEASUREMENT, REPORTING, AND OPTIMIZATION - Own performance reporting across spend, traffic, conversions, qualified leads, meetings, opportunities, and pipeline. - Develop channel-specific measurement frameworks for Google Ads, Bing, and ChatGPT based on their available reporting and conversion capabilities. - Partner with Marketing Operations to connect advertising conversion signals with HubSpot and Salesforce data. - Optimize established search channels toward downstream pipeline signals, including offline conversion tracking where supported. - Establish a testing and measurement approach for emerging channels where attribution and optimization capabilities may be less mature. - Analyze performance across channels, audiences, campaigns, and landing pages to identify where to invest, optimize, or reduce spend. CROSS-FUNCTIONAL PARTNERSHIP - Partner with Product Marketing to translate positioning into search campaigns, AI advertising messaging, and landing page experiences. - Work closely with Web and Design on landing page development and conversion experimentation. - Collaborate with Marketing Operations on tracking, attribution, CRM integrations, and reporting accuracy. - Align with Demand Generation on product launches, campaign priorities, budget allocation, and pipeline targets. WHAT WE'RE LOOKING FOR - 5–11 years in performance marketing, paid search, or B2B growth marketing, ideally in developer tools, infrastructure, or technical SaaS. - Deep hands-on expertise in Google Ads and experience managing Microsoft Advertising. - Proven experience personally building, launching, and optimizing paid search campaigns. - Strong understanding of campaign architecture, keyword intent, bidding strategies, negative keywords, and search budget optimization. - Experience testing new advertising platforms or emerging acquisition channels. Curiosity about AI-native search and advertising is important. - Strong experience with conversion rate optimization, landing page development, and A/B testing. - Experience managing meaningful budgets and optimizing toward qualified pipeline and revenue outcomes. - Strong analytical skills and fluency in CPC, CVR, CPL, cost per opportunity, pipeline contribution, and attribution. - Working knowledge of Google Ads, Microsoft Advertising, GA4, Google Tag Manager, HubSpot, Salesforce, and Flint/Webflow. - Comfortable with technical products and developer audiences. - A strong experimentation mindset and willingness to build new programs without an established playbook. - Comfortable with ambiguity and true ownership. COMPENSATION We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Salary Range: $165,000-$190,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Zada: Tizim administratori lavozimi uchun ishchi qidirilmoqda. Talablar: — Kamida 6 yil ish tajribasi talab qilinadi. — PHP, SQL, MySQL, PostgreSQL, Nginx, Apache, Linux, 1C, Bitrix, Windows Server texnologiyalari bilan ishlash tajribasi kerak. Shartlar: — Ish joyi Toshkent shahrida, ofisda (offline) ishlash. — Maosh 8 000 000 dan 12 000 000 so'mgacha. Qo'shimcha ma'lumotlar va ariza topshirish uchun havola: https://tashkent.hh.uz/vacancy/139105655

Location: San Jose, California, United States Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity We are looking for an experienced engineer to lead the architecture and hands-on development of the ML and data infrastructure behind our risk and fraud prevention systems. You will help teams move models from experimentation into reliable production services, improve model execution performance, and build scalable data foundations for training, evaluation, and real-time decisions. What You’ll Be Doing Improve model inference latency, throughput, resource utilization, and cost. Profile the full prediction path —from feature retrieval and preprocessing to model execution — and deliver measurable improvements without unacceptable model-quality regressions. Build reusable infrastructure for model packaging, versioning, deployment, serving, monitoring, and rollback across cloud platforms and regions. Design and optimize offline data pipelines on Databricks, Apache Spark, and warehouse/lakehouse technologies, addressing data modeling, partitioning, joins, shuffles, skew, incremental processing, and cost. Connect offline and online feature pipelines, ensuring point-in-time correctness, consistent feature definitions, freshness, lineage, and reproducible backfills. Evolve reliable feature services and data integrations supporting risk models and decision systems. Set technical direction, mentor engineers, and lead delivery across ML, data engineering, cloud infrastructure, security, and product teams. What We Look For In You A record of building and operating large-scale distributed systems, ML infrastructure, or data platforms, with technical ownership across teams. Hands-on experience optimizing production model performance, supported by measurable improvements in latency, throughput, utilization, or cost. Deep understanding of Databricks and Spark, or comparable offline data platforms, including execution plans, distributed query optimization, storage layouts, data correctness, and workload cost management. Experience with the model lifecycle, including training/serving integration, validation, deployment, observability, and rollback. Strong Python, SQL, and at least one backend or systems language such as Java, Scala, Go, or C++. Ability to turn ambiguous requirements into clear architecture and deliver maintainable systems through hands-on engineering and technical leadership. Nice to Haves SageMaker, Alibaba Cloud PAI/EAS, or comparable ML platforms. Inference optimization using tools such as ONNX Runtime, TensorRT, or Triton. Delta Lake, MLflow, feature stores, Kafka, Flink, and low-latency data stores. Fraud detection or financial risk systems. Fluency in Mandarin Perks & Benefits Competitive total compensation package L&D programs for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! OKX Statement: OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. The salary range for this position is $214,666 to 321,999 The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site. #LI-SK1 #LI-HYBRID Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

решать продуктовые задачи с помощью ML: от постановки гипотезы и исследования данных до запуска решения в production и оценки бизнес-эффекта; развивать ML-модели, влияющие на клиентский опыт и бизнес-метрики продукта.

Location: Canada What The Role Is We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless. Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting. We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help. If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on. What You'll Own You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape: Product recommendations across every surface. Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them. Personalizing the Feed. Deciding which products, editorial content and social content each family sees, and in what order. Personalizing search. Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations. Making Addie (our AI registry assistant) better at recs. Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site. In practice, you will: Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. Make the modeling and architecture calls that span surfaces and are expensive to reverse. Design the evaluation, offline and online, that tells us a model is good before and after it ships. Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. Partner with product, design and data to help shape what's worth building. Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org. Who You Are You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey. You bring: Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias. Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend. An ability to take an ambiguous problem and start moving before anyone hands you the full picture. A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings. An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue. AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next. Compensation We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is 299,300 to 372,600 CAD plus a target annual bonus of 20 percent of base. That's total target cash of roughly 359,160 to 447,120 CAD. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: United States What The Role Is We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless. Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting. We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help. If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on. What You'll Own You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape: Product recommendations across every surface. Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them. Personalizing the Feed. Deciding which products, editorial content and social content each family sees, and in what order. Personalizing search. Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations. Making Addie (our AI registry assistant) better at recs. Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site. In practice, you will: Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. Make the modeling and architecture calls that span surfaces and are expensive to reverse. Design the evaluation, offline and online, that tells us a model is good before and after it ships. Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. Partner with product, design and data to help shape what's worth building. Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org. Who You Are You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey. You bring: Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias. Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend. An ability to take an ambiguous problem and start moving before anyone hands you the full picture. A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings. An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue. AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next. Compensation We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: Australia Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker is launching a Professional Services organization to accelerate customer success, reduce time-to-value, and drive enterprise adoption for agentic workloads. As a Principal Solution Architect, you'll play a critical role in building and scaling this function. You will join a team of seasoned experts with deep experience backed by Docker's unmatched reach across Fortune 500 companies.   This is a high-visibility role working directly with senior leadership across revenue, product, marketing, and partner organizations. You'll shape service strategy, drive cross-functional alignment, and deliver offerings that accelerate both services revenue and platform expansion.   You'll serve as a trusted advisor to our largest and most strategic partners and enterprise customers, providing thought leadership on integrating Docker agentic solutions within enterprise environments. _______________________________________________________________________   RESPONSIBILITIES Build and Scale the Professional Services Practice - Develop and codify repeatable reference architecture patterns across Docker's core use cases including self-hosted and air-gapped deployments, MCP (model context protocol)/AI agent environments, IDP integrations, and secure supply chain workflows so that engagements scale consistently across customers and partners. - Translate reference architectures into customer-facing technical collateral, SOW templates, and success patterns that reduce scoping time and improve delivery consistency. - Collaborate with product, marketing, and revenue teams to integrate services into GTM motions and align delivery to Docker's AI platform roadmap. - Identify offerings that drive product expansion, renewals, and long-term customer value. - Support Partnerships & Alliances in selecting, onboarding, and enabling technical integration partners, system integrators (SIs), and service delivery partners. Drive Strategic Customer Outcomes - Act as a trusted advisor to enterprise customers, helping them adopt modern patterns for containerization, AI workflows, and secure software supply chains. - Lead technical discovery and architecture engagements that span enterprise integration layers - Architect and deliver self-hosted Docker deployments within air-gapped, regulated, and complex enterprise environments including local image registry setup, offline toolchain configuration, and compliance-driven infrastructure design. - Design and Guide customers through implementation of agentic AI toolchains, including MCP server/client architecture, tool orchestration, observability integration and secure deployment patterns aligned to Docker's AI platform. - Position Docker as a strategic and thought leadership partner, influencing long-term technology adoption and investment decisions. - Directly deliver or assign and oversee appropriate delivery partners to execute service engagements and ensure technical objectives are met. Enable Cross-Functional Success - Drive alignment and decision-making across multiple stakeholders and teams without direct reporting lines. - Translate field insights including enterprise integration patterns, IDP/SSO friction points, observability gaps, and AI deployment challenges into actionable product and services strategy, roadmap, and partner capabilities. _______________________________________________________________________   QUALIFICATIONS REQUIRED - 7+ years as a Professional Services Solution Architect, Technical Consultant, or similar role at a SaaS/infrastructure company or consulting firm. - Demonstrated experience architecting and deploying self-hosted and air-gapped deployment architectures: local image registries, offline toolchain configuration, network-isolated Kubernetes clusters, and compliance-driven infrastructure constraints common in regulated industries. - Enterprise integration experience across Identity Providers (Okta, Azure AD, LDAP/Active Directory) and federated identity protocols (OIDC, SAML, SSO), including RBAC design within complex, multi-tenant enterprise environments. - Working knowledge of Model Context Protocol (MCP) and its application to agentic AI toolchains including MCP server/client architecture, tool and resource orchestration, and secure containerized deployment patterns. - Hands-on experience with AI/ML workflows, LLM deployment, and agentic AI architectures in enterprise environments with awareness of Docker's AI platform roadmap including AI agent containerization, model provenance, and AI supply chain security. - Deep understanding of container and software supply chain security: Docker Hardened Images (DHI), Secure Supply Chain (SSC), SBOM generation, image signing and attestation, vulnerability management, and runtime governance. - Excellent facilitation and stakeholder management skills; able to lead executive-level architecture conversations and influence senior stakeholders without formal authority. - Direct experience delivering high-quality services engagements that achieve customer value while meeting revenue and ARR growth targets within a revenue organization. - Recognition by enterprise customers as a strategic technical advisor. BONUS - Experience architecting AI platforms in large enterprise environments LLM deployment pipelines, model provenance, artifact signing, and secure AI supply chain patterns. - Background enabling system integrators, consultancies, or partner ecosystems. - Consulting experience with Fortune 500 clients in highly regulated sectors such as financial services, healthcare, or government. - Led AI security architecture engagements that addressed model provenance, artifact signing, and supply chain integrity for containerized AI workloads including secure MCP server deployment, tool and resource access controls, secrets management within agentic pipelines, and runtime isolation patterns for LLM-based applications. _______________________________________________________________________   WHAT TO EXPECT FIRST 30 DAYS - Onboard to Docker's mission, values, and operating model. - Deeply familiarize yourself with our product portfolio, AI platform roadmap, and strategic customers. - Build strong partnerships with Product, Engineering, and Sales functions. - Plug into the team's rhythm of business (standups, reviews, shadow customer engagements). FIRST 90 DAYS - Scope, define SOWs, delivery, and oversight of customer service engagements. - Participate in the creation of reference architectures for key use cases.. - Participate in initiatives to build out and improve the services department's offerings. ONE-YEAR OUTLOOK - Successful delivery and oversight of customer service engagements. - Contribute materially to the build-out of Docker's service offerings across AI, security, and enterprise integration practices. - Institutionalize continuous improvement by providing field feedback including enterprise integration patterns, deployment blockers, and observability gaps to the product team.   Visa sponsorship: Not available for this role. ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: In-Office 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. Locations: Austin, Lisbon, San Francisco, NYC, or London About the Role Search is being rebuilt around AI. People increasingly get answers from AI instead of a list of links, agents run dozens of searches to answer a single question, and more than half of the traffic reaching sites on Cloudflare is now automated . Search is shifting from a destination to a utility, and Cloudflare is building the search layer for this agentic Internet. Agentic Search at Cloudflare gives agents everything they need to find information, whether it lives in a customer’s own data or on the open web. It spans two products: AI Search for internal data, and Web Search API for the open web. AI Search (internal data), now generally available , is the search primitive for applications and agents . It is a fully managed indexing and retrieval pipeline built on Workers AI , Vectorize , R2 , and Browser Run . Developers connect a website or R2 bucket, or upload their own files, and query them with natural language through a Workers binding, REST API, or MCP server. Under the hood: continuous indexing, hybrid vector and keyword retrieval, reranking, metadata filtering, native multimodal (image) embeddings, and OCR for scanned documents. We use it to power search on our own blog and developer docs. Web Search API (external data), now in open beta , gives agents real-time web context with a single API call. It runs on AI Gateway , so every search gets the same logging, analytics, billing, and access controls as model inference. Developers can choose from multiple search providers and always get results back in one normalized format. Your mission in this role is to make Cloudflare the default place developers and agents go to search, across both their own data and the open web, and eventually in a single call. You’ll also help build a search ecosystem that works for AI companies, site owners, and creators alike. What You’ll Do Talk directly with developers, AI companies, publishers, and customers every day. Own the strategy, roadmap, and execution for Agentic Search (AI Search and Web Search API), from ingestion and indexing through retrieval, ranking, and answer generation. Define and measure what “good search” means, including relevance, freshness, latency, and cost, and build the evals that improve it with every release. Scale AI Search for the workloads that matter most, like multi-tenant platforms, enterprise agents, and website search, with support for billions of documents, rich media, and built-in observability. Take Web Search API and shape what comes next: provider partnerships, search and page extraction in one call, blending web and private data, Own pricing and packaging, and make our products first-class for agents through MCP, agent-friendly APIs, and templates like NLWeb . Partner with engineering, ML, and product teams across Workers AI , Vectorize , AI Gateway , Browser Run , and AI Crawl Control , as well as Marketing, DevRel, BD, Sales, and Support. Represent Cloudflare at conferences, community events, and customer and partner meetings. Examples of Desirable Skills, Knowledge, and Experience Proven experience as a PM, EM, or founder shipping search, information retrieval, data infrastructure, or developer platform products. You’ve led teams to ship before and can point to impact. Deep understanding of how search works end to end: crawling, indexing, chunking, embeddings, hybrid retrieval (BM25 + vector), query rewriting, reranking, and retrieval-augmented generation (RAG). You understand the tradeoffs between relevance, freshness, latency, and cost. Experience defining and measuring search quality, including offline evals, relevance judgments, metrics like recall, MRR, and NDCG, and online experimentation. Fluency in the modern AI ecosystem: LLMs, text and multimodal embedding models, agents, tool calling, and MCP. You’ve built with them yourself and know where they break. Hands-on ability to write code and use AI and the Internet to learn new things fast. You’ve built a RAG pipeline or an agent that searches the web, and you have opinions about what made it good or bad. Deep empathy for developers and understanding of their workflows, pain points, and how they adopt new tools and platforms. Understanding of the web publishing ecosystem: crawlers, bots, SEO and answer engine optimization (AEO), and the changing economics of AI search for content creators. Comfortable working where technology, business, and policy meet. Experience with usage-based pricing, two-sided marketplaces, or partner and business development relationships, including build-vs-partner decisions, is a plus. Exceptional communication and collaboration skills. You can translate between ML research, infrastructure engineering, and business stakeholders, and align diverse teams on goals. Passion for design details and polish. You raise the bar for sweating the details. External presentation skills. You can walk into a room of developers or AI company leaders and build trust and credibility. Compensation Compensation may be adjusted depending on work location. For Seattle/NYC/California based hires - Estimated annual salary of: $172,000 - $215,000 For SF/Bay Area based hires - Estimated annual salary of: $179,000 - $224,000 For Lisbon based hires - Estimated annual salary of: €68,000 - €85,000 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.

Workplace: remote Requirements 3+ years of relevant experience Strong Python skills and experience with ML ecosystems (AWS Sagemaker, MLFlow) Hands-on experience working with tabular/time series data with usage of ML Solid understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation; Overfitting, regularization, cross-validation Knowledge of statistical methods and probability theory Experience with experiment design and offline evaluation Ability to work with large datasets and build efficient data processing pipelines Familiarity with SQL and data querying Strong analytical and problem-solving mindset Ability to clearly communicate findings and trade-offs Ownership of tasks from research to implementation Curiosity and willingness to explore new approaches English proficiency at B1 level or higher Nice to have Experience in financial machine learning, quantitative finance, or trading systems knowledge of signal generation, alpha research, portfolio construction or risk modeling Experience with: Deep learning for tabular/time series data (Transformers, RNNs, etc.); Probabilistic modeling or Bayesian methods Hands-on experience with production ML systems (MLOps, monitoring, retraining) Ability to define research direction and identify high-impact opportunities Decision-making under uncertainty Ability to translate business problems into ML solutions Responsibilities Develop and validate machine learning models for financial time series and cross-sectional data Conduct research on alpha signals, feature engineering, and predictive modelling techniques Design experiments and backtesting frameworks with proper statistical rigor Work with large-scale structured and unstructured financial datasets Collaborate with engineering teams to deploy models into production pipelines Analyze model performance, stability, and robustness under changing market conditions Improve data pipelines, labeling strategies, and evaluation methodologies We offer Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule Options to work remotely Any questions? Veronika hh@itransition.com

Location: Canada What the Role Is We’re hiring a Staff Software Engineer who’ll be the technical lead for a new Search team at Babylist. This new team will be focused on moving Babylist’s search capability in-house, making our search results more relevant and personalized, and partnering with other teams to transform search in the product from functional to delightful. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting search and personalization problems in consumer e-commerce. This is zero-to-one work, with big ambitions. You’d build a search capability from the ground up, with a clear mandate from leadership to do it. In your first year, we expect to have rebuilt search to be highly relevant and personalized, and delivered big bets like universal search: one experience across items we sell and items from other retailers, and across products, guides and registries. We also want to work with Addie, our AI registry assistant, to have LLMs play a role in the search experience. If you want to tune an established search system, this isn’t the right role. If you’ve worked inside a strong search team and want to build a new system from scratch at a company earlier in that journey, read on. What You'll Own A Staff Engineer at Babylist sets direction. You’ll be the technical lead for search: you decide where it goes over the next year or two, sequence the bets that get there, and make the technical and product calls along the way. You’re still in the code and will drive initiatives forward across multiple teams. You’ll have software engineering and machine learning engineering support on the team. A few examples of initiatives you’d drive on the Search team: Build search in-house. Choose the architecture for indexing, retrieval and serving, and plan a seamless migration. The system you design replaces what we use today and is the foundation for everything below. Define what a good result is. Decide how we measure result quality, then improve it through query understanding, ranking and the behavioral signals we collect. Unify search across everything we show. One experience across items we sell and items from other retailers, and across products, guides and registries, including how to rank items we don’t sell next to ones we do. Decide how search and recommendations fit together. Bring what we know about a user and their registry into results, and decide how much retrieval and ranking search shares with our recommendation models. Make search conversational. Work with the Addie team, our AI registry assistant, on queries like “best stroller for urban family,” where the shopper describes a need instead of naming a product. Like every Staff Engineer here, you will: Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers. Build the platform or tooling other teams adopt by choice, and own it as it scales. Set the standard for how search builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships. Partner with product, design and data as a peer, shaping what's worth building from the start. Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones Who You Are You meet the Staff bar at Babylist. You’ve shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You’ve already changed how a team builds with AI, and the new way stuck. On top of that, you’ve worked on search problems before, ideally in an e-commerce setting. This role needs depth in the systems behind search and a clear focus on the people using it. You bring: Hands-on search experience: building and running search in production, including indexing, retrieval, ranking and query understanding. You know how to keep a search service fast, relevant and reliable as traffic and catalog size grow. Experience evaluating search quality: offline and online, including relevance judgments and A/B tests. A focus on the user: you use query data, behavior and judgment about result quality to decide what to build, and you can connect a search change to what shoppers do, and to conversion or revenue. Comfort building from zero: you can define the problem, design the system and own it end to end. You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on. Compensation We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is $299,300 to $372,600 CAD, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $359,160 to $447,120 CAD. On top of that you get meaningful equity and an RRSP match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things to Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: Almaty, Kazakhstan Workplace: hybrid The Head of Supply is one of the key leadership roles in the vertical, owning supply performance across a large portfolio of markets and ensuring we can both run the current business efficiently and build the supply model required for future growth. The role combines two core mandates: Run the business: maintain a healthy marketplace, sufficient supply, efficient acquisition, strong courier economics, and consistent operational performance across markets. Change the business: build new supply models, fleet structures, operating approaches, product capabilities, and scalable solutions required to support new products, monetisations streams, and business models. This is a global ownership role with direct accountability for supply strategy, marketplace performance, economics, execution, and transformation. Key Responsibilities Marketplace Health Own supply-demand balance by market, zone, and time of day based on marketplace efficiency inputs. Maintain courier availability, utilisation, productivity, and overall marketplace health. Own geographic coverage gaps, supply density, and market expansion readiness. Build and maintain supply forecasting models with measurable accuracy targets. Own SLA achievement, done rate, acceptance rate, and other critical supply-side marketplace metrics. Identify structural marketplace issues early and drive corrective actions together with country teams and Product. Supply Acquisition Own the end-to-end courier acquisition funnel from awareness through activation and 1/3/10 completed deliveries. Define and manage CAC targets, acquisition budgets, channel mix, and activation efficiency. Run digital, referral, offline, partnership, and local acquisition programmes across markets. Design scalable acquisition playbooks while adapting execution to local market realities. Build and maintain a structured experimentation framework to continuously improve acquisition efficiency and activation quality. Ensure acquisition is directly linked to marketplace demand rather than managed as an isolated growth function. Supply Marketing Own global courier positioning and the courier value proposition. Define why couriers should choose, stay with, and prioritise our platform versus alternatives. Drive supply performance marketing together with the central Marketing team. Test and optimise creative, messaging, channels, and offers across acquisition and retention. Define communication strategy for active, lapsing, and reactivated couriers. Ensure courier communication supports both marketplace performance and long-term retention. Budget & ROI Ownership Own and allocate acquisition, incentive, referral, supply marketing, and other relevant supply budgets. Define clear СAC, payback, ROI, and incremental impact frameworks for all supply investments. Build quarterly and annual budget plans with scenarios and clear business assumptions. Reallocate investment across markets based on performance, opportunity, and marketplace needs. Hold country teams accountable for supply investment efficiency. Ensure every material supply investment has a clear expected business outcome and measurable return. Strategy Author and own the global supply strategy, updated annually and reviewed quarterly. Define how our supply model should evolve across different market maturity stages and business models. Build the country prioritisations framework based on marketplace maturity, growth opportunity, economics, and strategic importance. Lead quarterly and annual planning cycles, including OKR-setting with country teams. Define the long-term evolution of courier, fleet, partner, and hybrid supply models. Identify structural opportunities to improve supply quality, scalability, cost, and competitive advantage. Ensure supply strategy supports new verticals, products, monetisation models, and future business growth. Operations Run weekly global supply business reviews with country teams. Maintain a clear view of performance, key risks, priorities, and required actions across all markets. Manage country escalations and unblock critical operational issues with speed. Build scalable operating standards while preserving necessary local flexibility. Drive cross-functional alignment across Product, Marketing, Finance, Legal, GR, Commercial, and Operations. Step into critical markets or projects when performance requires direct leadership intervention. Build strong accountability across country teams for execution and results. Product Represent supply requirements in all relevant product roadmap decisions. Own prioritisation of supply-side product needs based on business impact and marketplace performance. Maintain and prioritise the supply product backlog together with Product. Translate operational problems into scalable product solutions rather than permanent manual processes. Coordinate experiment sequencing, pilots, rollout planning, and post-launch evaluation. Ensure new products and business models have a viable supply operating model before scale. Lead the supply side of major change initiatives including new fleet models, fulfilment models, courier tools, and marketplace mechanics. Analytics Own the supply performance framework across all markets. Own supply dashboards, country scorecards, and management reporting. Run regular funnel analysis, cohort analysis, marketplace diagnostics, and investment performance reviews. Build forecasting, scenario planning, and capacity models required for business planning. Track forecast accuracy and continuously improve planning quality. Ensure decisions are based on clear data and comparable metrics across markets. Move the organisation from reporting what happened to understanding why it happened and what needs to change. Qualifications 7+ years in marketplace operations, supply growth, or platform scale. Proven ownership of acquisition budgets ($1M+ annually). Experience leading multi-country or global teams of 8+ people. Track record of improving CAC and supply retention simultaneously. Background in on-demand logistics, ride-hailing or food delivery preferred. Advanced level of English proficiency. The Head of Supply is not only responsible for managing the existing supply organisation. The expectation is to build a global supply engine that can scale with the business. The person should be equally comfortable running marketplace performance today and redesigning the operating model for tomorrow - moving between country execution, economics, strategy, product, and complex transformation topics. Success in this role means having the right supply, in the right place, at the right time and cost today, while continuously building a stronger and more scalable supply model for the future. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location

Location: Lisbon Workplace: Hybrid Build with us Businesses deserve better from finance. Less friction, more freedom. Since 2004, Mollie has been on a mission to make payments and money management effortless for every business in Europe. Today, more than 250,000 companies trust our all-in-one platform to get paid, manage money and grow on their terms. Simple, scalable and built with real businesses in mind. We're one of Europe's fastest-growing fintechs, with 900+ Mollies across 12+ locations. Our people make this growth possible. We move fast, build with purpose and care deeply about our customers. Whether you're solving problems, building market-leading products or exploring how AI can make work smarter, you'll have the freedom to create and the trust to deliver. If you're ready to grow, shape the future of fintech and join an ambitious, high-performing team, this is the place for you. Your impact This is a critical, customer-obsessed role at the frontline of Mollie's mission. You'll be the first point of contact for our merchants, ensuring they get the excellent support they need to succeed and grow. Your impact is immediate: you help make our customers proud to work with us by providing outstanding, proactive service. You'll do more than just answer questions - you'll be the voice of the customer, using their feedback to drive real, innovative changes within Mollie. This role is about listening, solving problems fast, and making a direct contribution to the customer experience. Join a new and growing team in Lisbon to own the success of our growing merchant base.   What you'll ship - Act as the first point of contact across live chat, email, and phone to resolve customer inquiries quickly and effectively. - Proactively advise customers on Mollie products that fit their activities and help boost their online and offline presence and revenue. - Contribute to improving the customer experience by providing actionable feedback and proposing innovative solutions to internal teams. - Listen closely to customer feedback and challenges to align our support efforts with Mollie's mission of being customer-obsessed. What you'll bring - Fluent in Polish and English. Any other language is nice to have. - At least 1 year of experience in (customer) support - Ability to easily adapt to changing environments and quickly grasp new information and processes. - A fast learner who can take on complex problems and rapidly find solutions. - An easy communicator with a knack for clarifying complex topics and maintaining a human connection. - Nice to have: beginner to experienced professional—what matters is your drive to deliver impact for our customers.   Grow your way At Mollie, growth is personal. We believe everyone should have the chance to develop their skills, explore new challenges and shape their career on their own terms. You'll get regular feedback and performance reviews to support your development, with fair and transparent salary reviews along the way. Many Mollies move into new roles or take on new projects to stretch themselves, and we actively hire from within to help you take the next step. No matter if you're aiming for promotion, exploring a different career path or building new skills, you'll be supported with the tools, trust and opportunities to grow your way. Unlock your full potential and join us to eliminate financial bureaucracy If you're excited by the idea of building what's next, for yourself and for thousands of businesses across Europe, we'd love to hear from you. Apply with your CV (in English) using the form below. Want a peek behind the scenes? Check out what life at Mollie https://jobs.mollie.com/ is really like. AI at Mollie We believe in Always Be Shipping, and AI brings https://jobs.mollie.com/ai-manifesto that philosophy to life across every team, every role, every day AI is core to how we build. It helps us move faster, simplify work and make smarter decisions, creating real impact for the businesses we serve. We're looking for people who are excited to use AI to shape the future of finance with us.

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Проведение комплексного анализа текущего состояния защищенности ИТ-инфраструктуры, выявление уязвимостей и векторов угроз; Полный цикл внедрения, настройки и последующего сопровождения систем защиты информации (СЗИ);