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Location: JP - Tokyo, Japan Scopely Explore is seeking a highly motivated AI Data Specialist/ Engineer to join our Tokyo Studio, supporting Monster Hunter Now and Pikmin Bloom . This role will sit at the intersection of data engineering, AI tooling, marketing, live game operations, and product strategy. Scopely Explore’s Tokyo Studio builds games that inspire people to explore the real world together. Monster Hunter Now brings players outside to hunt, craft, and grow stronger together, while Pikmin Bloom helps people find joy in everyday walking and real-world memories. As an AI Data Engineer, you will build the trusted data pipelines, AI-native tools, and automation systems that help our teams operate these games with more speed, rigor, and creativity. Responsibilities Partner cross-functionally with stakeholders across Product, LiveOps, Marketing, User Acquisition (UA), CRM, and Game Operations (including product managers, marketers, analysts, data scientists, engineers, and studio leadership) to identify and prioritize high-impact data and automation opportunities and translate ambiguous business needs into reliable AI-native technical systems. Build and operate scalable data models, pipelines, semantic layers, and self-service data products using BigQuery, dbt, Looker, Airflow, and related cloud technologies. Develop production-quality AI-enabled workflows using technologies such as LLMs, agents, retrieval-augmented generation (RAG) knowledge systems, evaluation frameworks, and human-in-the-loop review patterns to help teams investigate performance, detect anomalies, prepare decision briefs, and plan and evaluate campaigns. Partner with Marketing to improve and automate workflows for audience segmentation, campaign performance, UA governance and execution, reactivation, event planning, and post-launch analysis. Safeguard data quality and metric consistency across game, marketing, and executive reporting while promoting responsible AI use through appropriate evaluation, oversight, and human review. Create reusable internal tools, patterns, and documentation that make AI accessible to non-technical teams while preserving trust, reviewability, and clear source-of-truth data. Contribute hands-on to Tokyo Studio’s broader AI operating model and help teams adopt effective AI-enabled workflows. Use AI-assisted engineering tools responsibly by validating generated code and analysis through rigorous review, automated testing, and established quality gates (including linting, type checking, and CI) before production. Qualifications 5+ years of experience in data engineering, analytics engineering, machine learning engineering, or a closely related role. Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting. Exceptional SQL skills and strong data-modeling fundamentals, including dimensional modeling, metric design, semantic layers, and scalable analytical data products, along with strong ability to write clean, maintainable production code for pipelines, automation, integrations, and AI-enabled workflows. Hands-on experience building AI solutions for real business workflows, including LLM applications, AI agents, Model Context Protocol (MCP) or similar tool-integration layers, retrieval-augmented generation (RAG), prompt and tool orchestration, and model evaluation. Strong judgment and hands-on experience establishing data-quality controls, consistent metric definitions, and responsible AI practices across data and AI-enabled systems (including reliability, privacy, access control, explainability, evaluation, and human review) and validating AI-generated code and analysis through code review and automated testing. Experience building tools for and working directly with Product, LiveOps, Marketing, User Acquisition (UA), CRM, or Game Operations teams, with the ability to identify and prioritize high-impact opportunities and translate ambiguous business and operational needs into durable technical systems that teams can trust and reuse. Experience building reusable internal data and AI tools and driving adoption among technical and non-technical users through documentation, training, and hands-on enablement, while contributing to AI operating models through shared standards, governance, ownership, and review practices across functions and regions. Excellent business-level verbal and written communication in both English and Japanese. Ability to work from Scopely Explore’s Tokyo office three days per week. Plus If... You enjoy helping teams become more capable by building practical systems that combine better tools, trusted data, and thoughtful automation to support faster, better-informed decisions. You are passionate about games and player behavior, have experience with free-to-play mobile, live-service, or location-based products, and are familiar with real-world or social mobile games such as Monster Hunter Now, Pikmin Bloom, or Pokémon GO. You have experience modernizing prototype or locally operated data workflows into reliable, scalable, cloud-managed production systems. About Scopely Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play. Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come. Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play. Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/ . Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official website and verify that all Talent Partner communications come from an email address ending in @ scopely.com . Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice . Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for an ML/AI Engineer with solid knowledge of cloud technologies, Infrastructure as Code (IaC), CI/CD practices, and software engineering best practices, focused on designing, building, and operationalizing Generative AI based solutions. You will join a strategic initiative within the Emantto domain, contributing to the acceleration of the organization's AI portfolio across multiple business areas. This role combines ML/AI engineering with strong software engineering, cloud, and infrastructure expertise. You will build and operate Generative AI driven data products, support domain teams, and act as a facilitator for the Data & AI Platform. Develop and deliver data products and AI/Generative AI solutions within domain teams. Act as a facilitator of the Data & AI Platform, enabling adoption and accelerating delivery across teams. Build, deploy, and operate Generative AI and Machine Learning models in scalable, production ready environments. Manage infrastructure related aspects of environments and AI/ML products, including observability, performance, and reliability. Contribute to CI/CD pipelines, Infrastructure as Code practices, and platform automation initiatives. Collaborate with cross functional teams, including Software Engineering, Data Engineering, MLOps, and DevOps teams, to maintain high engineering standards. Support experimentation frameworks and internal tools for Generative AI model development and evaluation. Experience working with Google Cloud Platform (GCP). Experience with Terraform or other Infrastructure as Code tools. Strong proficiency in Python. Experience in backend engineering, including APIs and services, as well as Generative AI, Machine Learning, or MLOps technologies such as Airflow, MLflow, pipelines, and monitoring tools. Solid understanding of CI/CD practices, containerization using Docker, and software engineering best practices. Familiarity with model deployment, model serving, and operating Machine Learning and AI systems in production environments. Experience with observability, incident response, or platform operations.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence About Reddit Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and 101M+ daily active unique visitors, we’re one of the largest sources of conversation and knowledge on the internet. For more information, visit redditinc.com . Team Overview The Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate. Our systems help ML engineers move faster across the full development lifecycle: creating features, generating training data, running offline experiments, validating model quality, launching production models, and operating ML systems reliably. We are looking for a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus will be on the feature development and training iteration loop: making it faster and easier for ML engineers to build features, generate reliable training data, run experiments, and move from idea to validated model improvement. Over time, this scope will expand into serving and online experimentation workflows, creating a more seamless path from offline iteration to production impact. This is a senior technical leadership role for someone who can combine deep systems expertise, production ML experience, architectural judgment, and cross-team influence. What You’ll Do Own the technical strategy for the end-to-end Ads ML engineer lifecycle, starting with feature development, training data, offline experimentation, and model iteration workflows. Align Ads ML platform priorities with Reddit’s broader ML Platform vision, translating Ads pain points into reusable platform capabilities where appropriate. Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency. Stay close to ML engineers and platform customers to identify high-leverage friction points and improve day-to-day development velocity. Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and more self-service. Over time, extend the platform strategy into serving and online experimentation workflows, creating a more seamless offline-to-online ML development experience. Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership, resolve ambiguity, and drive durable execution. Mentor Staff and senior engineers, raise the architecture and operational bar, and help grow the next generation of technical leaders. Who You Might Be You have 8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems. You have 4+ years building or operating production ML infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines. You have led broad, ambiguous, multi-team platform initiatives from strategy through adoption. You have built platforms used directly by ML engineers, data scientists, or product teams developing production ML systems. You have deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure. You have worked with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies. You can balance urgent customer needs with durable long-term architecture and reusable platform patterns. You influence senior engineers and leaders through clear technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms. You are excited to shape how production ML systems are built, scaled, and operated, not only how models are trained. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $292,500 — $409,500 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: IN - Jaipur iCapital is looking to hire an experienced Python Developer with expertise in web scraping, automated portal interactions, and cloud-native deployment using AWS. The ideal candidate will have hands-on experience working with Playwright for browser automation, managing multi-factor authentication (MFA) flows, and deploying scalable scraping tasks via AWS Lambda and related services. This role will assist in architecting and building robust, secure, and scalable scraping solutions that interact with complex web applications and secured portals. Responsibilities Assist with the design and implementation of advanced scraping solutions using Python, Playwright, and AWS services. Automate interactions with JavaScript-heavy and authentication-secured websites, including handling MFA, CAPTCHAs, and session or token-based login flows. Architect scraping pipelines using serverless AWS components such as Lambda, Step Functions, S3, CloudWatch, and Secrets Manager. Build systems that scale to support high volumes of data extraction with fault tolerance, retries, and intelligent logging. Integrate and manage complex workflows across multiple portals, APIs, and data sources. Contribute to architectural decisions, tooling, and best practices. Responsible for Code reviews and deployments. Qualifications Bachelor’s or master’s degree in computer science, software engineering, or related field, or equivalent professional experience 10+ years of experience in Python development, with a strong focus on automation and data extraction Proven expertise in web scraping using tools like Playwright, Selenium, Scrapy, BeautifulSoup, and requests In-depth experience handling multi-step authentication flows, including multi-factor authentication (MFA), CAPTCHA solving, and session or cookie management Proficient in deploying and managing scraping workloads in AWS, particularly Lambda, S3, IAM, CloudWatch, and Secrets Manager Experience with asynchronous programming, headless browsers, and JavaScript-rendered content Solid understanding of web protocols (i.e. HTTP, HTTPS, cookies, headers), and the ability to reverse-engineer network calls and authentication mechanisms Comfortable working with APIs, JSON/XML, and data transformation Experience with CI or CD pipelines, Docker, and infrastructure as code (i.e. CloudFormation, Terraform) Familiar with data pipeline orchestration tools such as Apache Airflow or AWS Step Functions Prior experience scraping from secure or enterprise-level portals (i.e. financial, healthcare, legal) Background in data engineering or ETL workflows is a plus Exposure to Python testing frameworks and writing unit or integration tests We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office four days, with the flexibility to work remotely one day (Friday). Benefits iCapital offers a comprehensive benefits package that includes a total compensation program consisting of competitive salary, annual performance bonus, and equity for all full-time employees; healthcare with 100% employer-paid health and dental insurance; and generous paid time off (PTO). For additional information on iCapital Network, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc

Задачи: — Разрабатывать и поддерживать масштабируемые сервисы ML-моделей, оптимизируя их производительность и эффективность. — Проектировать инфраструктуру, обеспечивающую критически важные входные данные для алгоритма диспетчеризации, влияющего на опыт миллионов клиентов по всему миру. — Тесно сотрудничать с дата-сайентистами и инженерами для понимания их потребностей и создания масштабируемых решений. — Разрабатывать и улучшать инструменты ML-инжиниринга для разработки моделей, мониторинга, обслуживания и экспериментов. — Использовать облачную инфраструктуру Delivery Hero, построенную на современных технологиях и популярных облачных платформах, для создания высокодоступных систем. — Предлагать инновационные решения и новые технологии для поддержки новых кейсов. Требования: — Опыт ML-инжиниринга или MLOps не менее 4 лет, знакомство с инструментами для обслуживания моделей, обучения, экспериментов и инженерии признаков. — Опыт построения инфраструктуры для ML-пайплайнов с использованием современных инструментов и языков программирования, таких как Python. — Значительный опыт (от 3 лет) в проектировании и реализации различных моделей машинного обучения (регрессия, классификация, ансамбли деревьев) для решения бизнес-задач, с хорошей теоретической базой в статистике и теории вероятностей. — Опыт разработки приложений с нуля и создания быстрых прототипов для решения системных задач с использованием open-source инструментов. — Опыт технической оценки технологий и предложений решений на основе анализа плюсов и минусов. — Опыт глубокого анализа существующих систем для их улучшения. — Свободное владение английским языком, четкая устная и письменная коммуникация. — Желательно: опыт работы с ML-инструментами Metaflow, Airflow, MLflow, Argo Workflows, Cloud Notebooks. — Желательно: знание публичных облачных платформ (AWS, Google Cloud или аналогичных). — Желательно: опыт работы с CI/CD пайплайнами и инфраструктурой как код (Terraform или аналог). — Желательно: знание контейнеризации и оркестрации (Docker, Kubernetes, Helm). Условия: — Релокация в Берлин, Германия. — Гибридный формат работы: 2 дня в неделю в офисе на кампусе в Берлине. — 27 дней отпуска с дополнительными днями на 2-й и 3-й год работы. — Поддержка развития и карьерного роста: образовательный бюджет 1000 €, языковые курсы, поддержка родителей, доступ к Udemy Business. — Медицинские обследования, медитация, спортзал. — Программы поддержки сотрудников: план покупки акций, банк саббатикала, скидки на транспорт, страхование жизни и несчастных случаев, корпоративная пенсия. — Питание: цифровые и обычные ваучеры на еду. Компания Delivery Hero — одна из крупнейших технологических платформ Европы, работающая в 65 странах, штаб-квартира в Берлине, котируется на Франкфуртской бирже с 2017 года.

Location: Europe We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones. Currently, we are looking for Senior Backend Engineer for Elva. Location: Remote Job Type: Full-Time ABOUT THE PRODUCT: We’re building an AI-driven video production platform that transforms ideas, references, and media fragments into structured video content. The product uses a multi-agent AI system to handle different stages of the creative process — from content analysis and scripting to editing and video production. It is designed for both professional creators and everyday users, allowing them to go from an initial concept to a finished video with significantly less manual work. ABOUT THE ROLE: We’re looking for an engineer who will help build and scale the core AI infrastructure behind the product. You’ll work on LLM-powered workflows, multi-agent systems, integrations, and backend services that turn user inputs into reliable production pipelines. The role combines hands-on engineering with architectural ownership: designing how agents interact, improving system reliability and performance, and experimenting with new AI capabilities. You’ll work closely with the product team and have significant influence over both the technical architecture and the quality of the final user experience. Our stack: - Python 3.12, FastAPI, Pydantic, SQLAlchemy 2.0 (async, asyncpg), Alembic - PostgreSQL (Cloud SQL) - Google Cloud: GKE (Kubernetes + Helm), Cloud Storage, BigQuery, Secret Manager - Ory Oathkeeper (API gateway), Centrifugo (real-time), n8n (worker orchestration), KEDA (autoscaling) - Docker, GitHub Actions, Artifact Registry - pytest (asyncio) + Testcontainers - structlog, Google Cloud Monitoring / Logging What we expect: - 5+ years of professional Python development, a solid share of it on an async stack (FastAPI / aiohttp / Starlette); deep understanding of asyncio. - Strong PostgreSQL: schema design, transactions and locking, indexes, slow query analysis. - Experience designing REST APIs and webhook integrations: idempotency, retries, consistent error handling. - Hands-on performance work: profiling, metrics, load testing, and fixing the bottlenecks you find. - Docker as a daily tool; Kubernetes at the "I deploy and debug my own service" level (each service ships its own Helm chart). - A habit of writing tests (unit + integration) and taking features to production end-to-end: from design to monitoring. Nice to have: - GCP experience (or AWS/Azure with willingness to switch to GCP), Terraform. - Mobile app billing: RevenueCat, Paddle, App Store / Google Play subscriptions. - Auth systems: JWT, refresh token rotation, API gateways. - Real-time messaging (WebSocket), workflow orchestration (n8n, Airflow, Temporal, Celery). - BigQuery and analytics pipelines. - Backend experience in mobile products. What’s next? If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider. We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.

Location: Worldwide We are looking for an experienced and driven Engineering Manager to manage our DWH Data Tools team . This team is responsible for managing and evolving our critical data ecosystem tools, including Superset, Jupyter Hub, and DataHub, while also developing new, in-house solutions - including internal BI and data-exploration tools - to fit specific business needs. This role merges technical leadership with comprehensive team management. The ideal candidate will possess strong leadership skills and technical expertise across the team's stack - Python, plus Node.js and Go - along with a proven track record managing engineering teams and data platforms. You will be pivotal in planning, optimizing development processes, and translating product ideas into robust technical solutions that solve real user pain points - often while navigating shifting priorities and evolving business needs. Challenges that await you: People Management: Lead, mentor, and manage a team of engineers. Take ownership of their performance, regular 1-on-1s, and continuous professional development Product Collaboration & Solution Brainstorming: Collaborate closely with product stakeholders to understand user pain points. Lead the brainstorming of technical solutions and translate product vision into actionable designs Planning & Execution: Drive planning activities for the team. Create and manage development plans, adeptly handling flexible deadlines and shifting business priorities Service Maintenance: Oversee service maintenance in strict alignment with SRE processes, taking responsibility for the reliability, stability, and incident control of the tools within the DWH Architecture & Development: Oversee the architecture, design, and implementation of data tools (Superset, Jupyter Hub, DataHub) and lead the development of custom solutions to meet new business requirements Stakeholder Communication: Manage communication with data engineers, analysts, and other stakeholders to ensure seamless data integration and tool usability What makes you a great fit: 1+ years of experience managing engineering teams in fast-paced settings, preferably fintech with Python or Go stack Hiring, development, performance, and delivery management and strong skills in cross-functional collaboration and the ability to build partnerships Strong technical expertise in designing, deploying, and managing data tools (e.g., BI platforms, data notebooks, or data catalogs) Proven ability to manage flexible planning, balancing dynamic priorities and deadlines Excellent communication and collaboration skills, with the ability to partner effectively across teams and regions An adaptable, structured mindset — able to prioritize effectively and stay grounded amid ambiguity and change B1 or higher English level for effective communication with an international team Your bonus skills: Experience implementing or maintaining services alongside SRE processes Work experience in DWH and/or the banking/fintech sphere Familiarity with the technical stacks or internals of Superset, Jupyter Hub, or DataHub Experience with data integration frameworks (e.g., Apache Kafka) Knowledge of ETL tools (e.g., Airflow, DBT) Experience with Kubernetes Experience with Snowflake or Lake House architectures Our ways of working: Innovative Spirit: A commitment to creativity and groundbreaking solutions Honest Feedback: valuing open, transparent communication Supportive Team: a strong, collaborative community Celebrating Achievements: recognizing our wins together High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances Our benefits: Relocation support to one of our hubs — Cyprus, Spain or Georgia — with assistance for the employee and their family Flexible work from one of our offices or remote Healthcare Coverage Education Budget: Language lessons, professional training and certifications Wellness Budget: Mental health and fitness activity reimbursements Vacation Policy: Annual leave and paid sick leave as per applicable policies

Location: Remote USA Workplace: remote ABOUT YOU You are a technical product manager who owns what a model optimises for, not just the roadmap around it. You have real depth in recommendation and ranking systems, and you will own the recommendation engine behind the Xsolla Advertising Products: the ranking that decides which offers millions of players see, and in what order. You hold the bar high for how decisions get made. You can read a readout and say plainly what it does and does not support. You connect model performance to revenue without overclaiming, and you bring a low-ego, people-first approach to work that spans ML, analytics, ads operations, and commercial teams. If you are excited about using ML to build building the next generation of advertising, rewards and loyalty programs for mobile apps and games we want to hear from you. ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Responsibilities: Own the recommendation engine as a product: ranking, relevance, and the model roadmap. Ranking quality is the product. Set the objective the ranker optimises for, the constraints it works inside, and the guardrails and kill conditions that bound it. The target is eCPM today; what comes next is your call. Own the metric definitions the whole team measures against, and settle the definitional questions that change the answer: gross against publisher-side RPU, app-load against impression-user denominators, mean of daily values against window totals. Collaborate with on ML frameworks, experiment design, hold-outs, including pre-registered decision rules, power calculations, sample-ratio-mismatch checks, A/A validation, multiplicity correction, and named rollback triggers. Collaborate with DS on readouts to evaluate model performace and readouts to business stakeholders readout: what the model did, what it cost, and what happens next. Contribute the ranking perspective to the wider ads roadmap, including the seams where pricing, identity, and event telemetry meet ranking. Qualifications & Skills: 6+ years in product management, with 3+ years owning a recommendation, ranking, personalization, or relevance system in production. Deep understanding of experiment design and inference, including minimum detectable effect, statistical power, sample ratio mismatch, A/A testing, multiple-comparison correction, and pre-registration. You can tell when a readout will not support the claim being made from it, and you say so. Working knowledge of the modelling itself: classification and regression, probability calibration, predicted conversion rate, expected-value objectives, and how the choice of objective changes model behavior. Hands-on experience with ML and data platforms such as Snowflake, BigQuery, Spark, Airflow, dbt, MLFlow, Vertex AI, and feature stores. Proven record of moving model changes into production traffic through a controlled experiment process, rather than shipping on a dashboard reading. Knowledge of performance advertising economics and ad tech ecosystems, including eCPM, RPU, bid multipliers, campaign hierarchies, and attribution models. SQL you write yourself, and enough comfort reading application code to verify a claim instead of taking it on trust. Excellent written communication and stakeholder management across technical and non-technical audiences. Specs, decision records, and readouts are the output of this role, and other teams act on them without you in the room. Bachelor's or Master's in Computer Science, Engineering, Statistics, Economics, or a related field. Offerwall, rewarded advertising, loyalty and rewards programs and/or mobile app monetization experience is a plus. Experience with a two-stage ranking system, where an external service supplies the base order and local logic adjusts it, is a plus. Pricing, yield management, or marketplace experience alongside ranking is a plus. Benefits: We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes 100% company-paid medical, dental, and vision plans, unlimited Flexible Time Off, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.   Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the Sr. Technical Product Manager, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements Handling sensitive financial information/managing budgets/accessing funds   Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com.

Location: Remote (Peru) Zeal is an AI-enabled software consultancy purpose-built for Fortune 1000 companies, and we’re now part of Livefront . We help companies navigate technology to drive business outcomes by attracting, retaining, and growing exceptional talent and empowering them to use innovative technologies and process frameworks. We’re a values-driven technology company grounded in kindness, generosity, and integrity. Our mission is to build a place where our employees love their future and where clients trust us to deliver what we promise: to improve their business through technology. Love your future. We’re looking for an outstanding Java Engineer to join our team. This role is available across our primary LATAM hub in Peru. Who you are You are a pragmatic problem-solver who enjoys turning complex business challenges into effective, high-quality technology solutions. You communicate clearly with both clients and technical peers, you adapt easily across industries and technical stacks, and you have a keen interest in consulting. You are curious about new tools—including AI tools that improve your productivity. What you will be doing Work directly with clients to analyze business problems and implement technology solutions. Develop software, design solutions, and collaborate with senior consultants to deliver high-quality outcomes. Learn and apply best practices in software engineering, cloud technologies, and system architecture. Gain experience across multiple clients and industries, adapting to different technical and business environments. Build trust with clients and internal teams through strong communication, problem-solving, and execution. Execute custom software development, primarily utilizing established languages and frameworks, including: C#, Entity Framework, ASP.NET, Java, Spring Boot, and Python; JavaScript, TypeScript, React, Angular, Next.js, .NET MAUI, Flutter, and Xamarin. Implement automated verification protocols for software systems to ensure operational integrity. Design and enhance CI/CD pipelines, incorporating comprehensive deployment and observability solutions through industry-standard tooling, such as: TerraForm, Azure Bicep, AWS CloudFormation, GitHub Actions, and Jenkins; Dynatrace, New Relic, Jaeger, Grafana, Prometheus, and Azure Monitor. Develop and maintain robust data pipelines and sophisticated analytics platforms utilizing: SQL Server, PostgreSQL, Oracle, MongoDB, Kafka, Databricks, Snowflake, dbt, Apache Airflow, Azure Data Factory, Power BI, and Google Looker. Why you should apply You want to work with passionate, talented people who are always looking for ways to make things better. You value a work environment where kindness, mutual trust, and egoless collaboration are paramount. You have a history of keeping promises, doing what is right, and spending energy on what matters. You enjoy the variety and growth that comes with consulting for Fortune 1000 companies across industries and technical stacks. You want to work on projects that have outsized impact and reach. You believe in sweating the details, committing to quality, and taking pride in going the extra mile. What you bring to the table We expect candidates to demonstrate a solid foundation in software development and a keen interest in consulting. Technical Skills: Proficiency in at least one modern programming language (e.g., Python, Java, JavaScript, C#). Communication: Excellent verbal and written communication skills. Problem-Solving: Proven ability to analyze complex problems and propose practical solutions. What to expect When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn). Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete. Additional information We go out of our way to evaluate all employees and job applicants equitably based on merit, competence, and qualifications. We encourage candidates from all backgrounds and identities to apply, and we consider every applicant with an open mind. Don't worry, every application will be reviewed by a human.

Location: Remote (Peru) Zeal is an AI-enabled software consultancy purpose-built for Fortune 1000 companies, and we’re now part of Livefront . We help companies navigate technology to drive business outcomes by attracting, retaining, and growing exceptional talent and empowering them to use innovative technologies and process frameworks. We’re a values-driven technology company grounded in kindness, generosity, and integrity. Our mission is to build a place where our employees love their future and where clients trust us to deliver what we promise: to improve their business through technology. Love your future. We’re looking for an outstanding C# / .NET Engineer to join our team. This role is available across our primary LATAM hub in Peru. Who you are You are a pragmatic problem-solver who enjoys turning complex business challenges into effective, high-quality technology solutions. You communicate clearly with both clients and technical peers, you adapt easily across industries and technical stacks, and you have a keen interest in consulting. You are curious about new tools—including AI tools that improve your productivity. What you will be doing Work directly with clients to analyze business problems and implement technology solutions. Develop software, design solutions, and collaborate with senior consultants to deliver high-quality outcomes. Learn and apply best practices in software engineering, cloud technologies, and system architecture. Gain experience across multiple clients and industries, adapting to different technical and business environments. Build trust with clients and internal teams through strong communication, problem-solving, and execution. Execute custom software development, primarily utilizing established languages and frameworks, including: C#, Entity Framework, ASP.NET, Java, Spring Boot, and Python; JavaScript, TypeScript, React, Angular, Next.js, .NET MAUI, Flutter, and Xamarin. Implement automated verification protocols for software systems to ensure operational integrity. Design and enhance CI/CD pipelines, incorporating comprehensive deployment and observability solutions through industry-standard tooling, such as: Terraform, Azure Bicep, AWS CloudFormation, GitHub Actions, and Jenkins; Dynatrace, New Relic, Jaeger, Grafana, Prometheus, and Azure Monitor. Develop and maintain robust data pipelines and sophisticated analytics platforms utilizing: SQL Server, PostgreSQL, Oracle, MongoDB, Kafka, Databricks, Snowflake, dbt, Apache Airflow, Azure Data Factory, Power BI, and Google Looker. Why you should apply You want to work with passionate, talented people who are always looking for ways to make things better. You value a work environment where kindness, mutual trust, and egoless collaboration are paramount. You have a history of keeping promises, doing what is right, and spending energy on what matters. You enjoy the variety and growth that comes with consulting for Fortune 1000 companies across industries and technical stacks. You want to work on projects that have outsized impact and reach. You believe in sweating the details, committing to quality, and taking pride in going the extra mile. What you bring to the table We expect candidates to demonstrate a solid foundation in software development and a keen interest in consulting. Technical Skills: Proficiency in at least one modern programming language (e.g., Python, Java, JavaScript, C#). Communication: Excellent verbal and written communication skills. Problem-Solving: Proven ability to analyze complex problems and propose practical solutions. What to expect When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn). Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete. Additional information We go out of our way to evaluate all employees and job applicants equitably based on merit, competence, and qualifications. We encourage candidates from all backgrounds and identities to apply, and we consider every applicant with an open mind. Don't worry, every application will be reviewed by a human.

Location: Remote (US) About the company Hi, we're Ondo Finance. Our mission is to provide institutional-grade, blockchain-enabled investment products and services. We have both a technology arm that develops decentralized finance technology, and an asset management arm that creates and manages tokenized funds. We are the global leader in tokenized treasuries, tokenized stocks and ETFs, and are building the future of institutional-grade financial services onchain. Founded by alumni of Goldman Sachs' Digital Assets team, we're backed by some of the best investors in the world, including Founders Fund, Coinbase Ventures, Pantera Capital, Tiger Global, and more. We are the category leader by AUM, well-capitalized, and growing quickly. We're fully remote, with team members across the U.S. About the role Our Data Science team turns on-chain and off-chain data into the analytics, risk, and decision-making infrastructure behind Ondo Global Markets (tokenized stocks) and Ondo Perps. We're hiring Ondo's first Data Engineer to build the foundational data platform that this work depends on—consolidating fragmented data sources, standing up a unified warehouse in BigQuery, and making trustworthy, well-modeled data available to the entire team. This is a hands-on infrastructure role with end-to-end ownership. You'll lead the migration of analytics into BigQuery, work directly in the Go services that power Ondo Perps to ingest additional data into the warehouse, and build the repeatable ETL pipelines that let data scientists, risk, and analytics move quickly and self-serve. You'll partner closely with Data Science, Backend Engineering, Risk, and Product to replace today's siloed, ad-hoc pipelines with reliable, observable, and reusable data infrastructure. Our team operates with high autonomy, high trust, urgency, and an uncompromising quality bar. We're looking for someone who improves the platform without waiting to be asked, cares deeply about data quality and correctness, and pairs strong engineering judgment with humility. You'll shape both Ondo's data foundation and how our Data Science team builds and scales analytics. Responsibilities Lead the migration of analytics and existing data workflows into BigQuery, establishing it as Ondo's unified, trusted warehouse and reporting layer. Read, understand, and extend the Go services powering Ondo Perps to ingest additional data into the warehouse (e.g. changefeeds and streaming/batch sinks from production systems). Design, build, and operate repeatable, well-tested ETL/ELT pipelines that the wider Data Science team can rely on and reuse. Consolidate fragmented and siloed data sources—internal databases (CockroachDB, QuestDB), on-chain and market-data vendors (Allium, Dune, Databento), and product analytics—into consistent, well-modeled datasets. Establish standards for data ingestion, transformation (e.g. dbt), orchestration, testing, lineage, and documentation so definitions are consistent and self-serve. Experience building foundational metrics and dashboards, with strong opinions on data lineage and quality, in partnership with Data Science. Own data quality, observability, monitoring, access controls, and cost management across the pipelines and warehouse. Partner with Data Science, Backend Engineering, Risk, and Product to turn analytical and reporting needs into durable data infrastructure. Requirements 5+ years of data engineering experience building and operating production data pipelines and warehouses. Deep hands-on experience with a cloud data warehouse—BigQuery strongly preferred—including performance, partitioning, and cost optimization. Strong SQL and data modeling skills, plus experience with modern transformation and orchestration tooling (e.g. dbt, Airflow, Dagflow-style schedulers, or similar). Experience designing batch and streaming ingestion (CDC/changefeeds, event pipelines) from operational databases into a warehouse. Experience building data infrastructure for fintech, trading, or other high-integrity financial systems where correctness and auditability matter. High standards for data quality, reliability, testing, observability, and documentation. Clear communication, high ownership, and a track record of delivering effectively with both technical and non-technical partners. Nice to haves Proficiency reading and writing Go, or strong general software-engineering ability and a track record of quickly ramping on unfamiliar production codebases. Experience with crypto-native or on-chain data, and vendors such as Allium, Dune, or Databento. Familiarity with CockroachDB, QuestDB, Snowflake, or similar operational and analytical stores. Experience enabling self-serve analytics and AI-over-data workflows for analytics and data science teams. Exposure to risk, quantitative analytics, or trading microstructure data. What we offer Competitive compensation including salary, future token rights, and/or equity, according to your preferences. We're well-funded and believe that great talent deserves great compensation. Full benefits, including medical, vision, and dental coverage, plus a flexible vacation policy. A remote-first team across many countries. You'll be an early team member helping shape our vision, culture, and engineering practices. A+ colleagues. Our team includes alumni from Goldman Sachs, BlackRock, Two Sigma, Bridgewater, SpaceX, AWS, Meta, Google, McKinsey, Coinbase, Circle, and Uniswap. Best-in-class investors. We are proud to be backed by leading crypto experts and venture firms, including Pantera Capital, Founders Fund, and Coinbase Ventures.

Location: Ukraine; Poland; Spain; Portugal; Germany; Romania At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. And now we are looking for a Engineering Manager, Applied AI & Machine Learning Engineering to join us as part of our team. About Role PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. As an Engineering Manager, AI/ML, you will support a cross-functional team of MLE and MLOps engineers working across several AI/ML initiatives. Your primary focus will be resource planning, execution, and people management. You will work closely with project leads, technical leads, functional managers, and product partners to ensure projects are appropriately staffed, plans are realistic, risks are visible, and teams can deliver effectively. You will manage capacity and resource allocation across multiple projects, help coordinate dependencies and priorities, and provide stakeholders with a clear view of delivery progress. Project and technical leads will continue to own product direction and technical decisions. You will also support the career growth and performance of team members. This includes gathering feedback, coaching employees, creating development plans, and contributing to performance, promotion, and compensation reviews. You should have enough AI/ML experience to understand the work, communicate effectively with engineers, and identify technical delivery risks. However, this is not expected to be a hands-on engineering or architecture role. Our Tech Stack & Focus Areas Generative AI & LLMs: Develop and maintain LLM-based solutions for generative features. Classic ML Models: Develop and maintain predictive and classification models for financial data Vector Databases: Implementing efficient storage and retrieval systems for high-dimensional data embeddings. Embeddings: Developing hybrid models to extract insights from diverse data sources. High-Volume Data Management: Engineering systems capable of handling massive, real-time data streams. Work Environment Flexible schedule with participation in team ceremonies and cross-functional collaboration. Time zone: Europe/Kyiv. As a qualified expert, You will: Manage resource allocation and capacity planning across multiple AI/ML projects and operational commitments Partner with project and technical leads to create realistic delivery plans, milestones, and staffing models Maintain a clear view of project progress, dependencies, risks, and resource constraints Help resolve delivery blockers, priority conflicts, and cross-team dependencies Facilitate quarterly and ongoing planning across MLEs and MLOps teams Provide clear delivery and staffing updates to functional managers and other stakeholders Manage and coach engineers through regular one-to-one meetings and career discussions Gather and synthesize feedback from project leads, technical leads, and cross-functional partners Create development plans and support performance, promotion, and compensation review processes Identify team capability gaps and contribute to hiring, onboarding, retention, and workforce planning Foster an inclusive, collaborative, and high-performing team environment Apply Agile, Lean, and Fast-Flow practices to improve team effectiveness and delivery predictability We’re looking for you if you have At least three years of experience in software engineering, AI/ML, or a related field At least three years of experience in people management, engineering management, or technical program leadership Working knowledge of AI/ML modeling, systems and the development lifecycle Experience managing multiple technical projects with shared resources and cross-team dependencies Strong skills in capacity planning, resource allocation, project execution, risk management, and stakeholder communication Experience supporting the performance and career development of technical employees Ability to understand technical discussions and work effectively with MLE and MLOps teams Experience working with distributed or geographically dispersed teams English — Upper Intermediate or higher; Ukrainian — fluent Bonus points Experience managing or supporting MLE and MLOps teams Experience working in a matrix organization with separate people, project, product, and technical leadership roles Experience with planning or allocating engineers across multiple projects Familiarity with production ML, generative AI, semantic search, summarization, prediction, or similar capabilities Familiarity with technologies such as Kubernetes, Docker, Kafka, Airflow, Snowflake, and cloud platforms Experience conducting performance reviews and building employee development plans Experience working with staffing partners, contractors, or blended internal and external teams Experience in fintech, SaaS, market data, or another data-intensive industry What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling clients growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Work fully remote around the globe, or in a hybrid work model from our office hubs which are equipped with everything needed for comfortable work. Enjoy a flexible working schedule and create work and rest balance for yourself. Empower yourself with a stable workload and a stable income, focusing on lasting cooperation and high-performance culture. Embrace the opportunity for personal and professional growth Take advantage of performance review and career path. Elevate your skills with mentorship program, personal development plan, and individual learnings through the corporate library, public speaking support, and more. Feel cared about Be among like-minded people and feel supported with collaboration, open communication and mutual respect. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Interview Steps: Interview with the recruiter Codebase review Interview System design Interview Cross-functional execution case Interview Final сlient Interview

Location: Portugal; Georgia; Bulgaria; Vietnam; Cyprus; Montenegro Engage with the business objectives behind key tasks: pricing for B2B/B2C, forecasting and optimization of financial and operational metrics, incident prioritization, and improving customer journey efficiency (revenue growth, cost savings, business impact). Drive ML projects end-to-end: from problem definition and formalization to modeling, piloting, and presenting results. Collaborate with data engineers to collect the necessary datasets and assess implementation feasibility. Work with analysts on A/B test design: defining metrics, splits, and interpreting results. Develop models (classic ML and DL, time series, uplift modeling), conduct error analysis and performance evaluation. Prepare models and code for transfer to production infrastructure (deployment and releases handled by the technical team). Take ownership of model quality, monitor key metrics, and collaborate with the team on degradation issues and improvement plans. Requirements 3+ years of experience as a Data Scientist. Proven experience with end-to-end ML projects (ability to oversee the entire process). Strong knowledge of classical machine learning techniques (feature engineering, classification, regression, boosting, etc.). Hands-on experience with uplift modeling and time series tasks (with real business applications). Experience working with business stakeholders and understanding optimization problems: pricing, B2C, LTV, retention, AB testing, and more. Proficient in Python for DS/ML (writing clean, readable code for models and experiments). Confident SQL user (able to build datasets, write joins, and perform data analysis). Nice to have: experience with MLflow/DVC, pipelines (Airflow or similar), anomaly detection/anti-fraud, deep learning (PyTorch/TensorFlow), and model monitoring. Benefits A fully flexible work schedule — there’s no pressure to start work at exactly 9:00 AM; what matters is achieving results and moving forward; Each person in our team is encouraged to choose their preferred work format. You can work fully remotely, come to the office, or choose a hybrid work model; We are an ambitious and supportive team who love what they do, appreciate each other, and grow together; The growth and development of each employee is our priority, so we have internal programs available for adaptation and training, development of soft skills and leadership abilities that are tailored individually to each employee; We also provide partial compensation for employees participating in external training and conferences; In tourism, it's difficult to grow without an excellent knowledge of English, and we support our employees' language learning goals — we organize group and individual lessons, plus speaking clubs with colleagues from all over the world; And, of course, to encourage you to travel more, we offer corporate prices on hotels and other travel services; We prioritize well-being and are committed to supporting the overall health and work-life balance at ETG. As part of this commitment, we provide MyTime Day Off - an extra day off that is designed to give our employees the flexibility to focus on important matters, whether it’s taking care of their health, mental recharge, addressing personal issues, or any other important activities. Learn more about our data protection practices in our Privacy Policy: https://www.emergingtravel.com/career/hr-policy/

Location: Warszawa, Poland; Rīga, Latvia; Tallinn, Estonia; Vilnius, Lithuania Workplace: fully Join an International Banking Project as a Senior Data Engineer. Project/Client: Banking Location: Baltic States and Poland Citizen (remote) Start Date: ASAP Duration: 12 months Language: English Role Overview: We are looking for an experienced Senior Data Engineer to join a cross-functional Agile team within the banking domain. The role focuses on designing and improving end-to-end data solutions across AWS cloud and on-premises ( Oracle DB ) environments, working with Airflow , dbt , and SAP Data Services , and contributing to Data Mesh and Medallion architecture implementations. Key Responsibilities: Design, implement, and improve data ingestion, processing, storage, and sharing within a Data Mesh platform across AWS cloud and legacy DWH environments Build and optimize ETL/ELT pipelines and data architectures using Airflow , dbt , and SAP Data Services Support modernization and migration of legacy data systems toward cloud-native architecture Ensure high standards of data quality, security, and performance across all data workflows Collaborate with analysts, engineers, and business stakeholders to deliver scalable data solutions Perform code reviews, implement monitoring and alerting, and resolve data pipeline defects Participate in the EOD ROTA rotation, with availability for incident resolution until 23:00-24:00 Must-Have Requirements: Proven hands-on experience with SQL and Python Hands-on experience with cloud platforms - AWS , Azure , or GCP Good understanding of data pipeline tools such as Airflow or dbt Working knowledge of enterprise data platforms: Oracle DB , SAP IQ , SAP Data Services , and SAP Business Objects Knowledge of solution integrations - real-time, message-based, and event-driven architectures - including bridging legacy systems with modern data platforms Exposure to test automation and DevOps practices, including infrastructure as code, security best practices, CI/CD , and SDLC Experience with Data Products deliveries, Medallion architecture , and Data Mesh architecture Strong communication and collaboration skills Nice to Have: Experience within the banking / customer business domain Experience with container orchestration tools: Kubernetes , Docker Understanding of streaming data pipelines and platforms: Kafka , Spark , Flink Experience with reporting tools such as Power BI Experience with both SQL and NoSQL databases Java development experience 💼 What we offer Model: B2B contract with Bonapolia- one contract, one monthly invoice Rate: negotiated per candidate seniority and client budget Payment: monthly invoice, paid on the same schedule the client pays us (usually 30 days) Contract written under your country's law We handle the client-side paperwork: MSA, NDA, invoicing 🏢 About Bonapolia Bonapolia is a family-owned IT staff augmentation team based in Lisbon. We build engineering teams for product companies and IT consultancies across Europe and the US. More at bonapolia.com 📩 Ready to Join? We look forward to receiving your application and welcoming you to our team!

Location: Helsinki; Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile gaming industry. The Voodoo Ad-Network is an autonomous product group of around 60 highly driven professionals with an ambitious mission: building top-tier ad network services. Our primary goal is to leverage Voodoo's massive first-party data ecosystem to optimize and scale monetization. We are in a rapid growth phase, expanding into new ventures such as opening to external inventory, penetrating the external advertiser market, and driving social network monetization following our recent acquisition of BeReal. To support this incredible trajectory and promising early results, we are scaling our team. The Models team is a core element of the targeting performance. It leverages machine learning and a strong business understanding to directly impact the product's financial performance. It's composed of mostly senior Data Analysts, Analytics Engineers, Data Engineers and Data Scientists/ML Engineers that iterate together on finding and building the next performing iteration. This role can be either Paris or Helsinki based and done in a hybrid setup. ROLE We're looking for a Senior ML Engineer to join our Models team. You will be joining a dedicated squad of Data Engineers, Data Scientists, and ML Engineers focused on building and maintaining the ML training infrastructure that powers our ad-targeting models from data preprocessing through model deployment to production monitoring. In this role, you will be leading the following topics: - Architectural Ownership: Take end-to-end ownership of highly visible projects from ideation to production release. This includes feature scoping, timeline estimation, architecture design, and benchmarking new technologies. - Pipeline Engineering: Build and maintain quality data and ML pipelines to align with ever-evolving business and machine learning needs. Optimize training pipelines for performance, memory efficiency, and cost (e.g. spot instance strategies, efficient data loading, preprocessed artifact reuse). - Data Scientists Enablement: Enable Data Scientists to iterate faster by providing reusable, well-tested pipeline components (transformers, dataloaders, training utilities) and reviewing their contributions to shared code. Extend dataset capabilities: integrating new data sources, scaling feature windows, and increasing training data volumes without breaking pipeline constraints. - Deep Learning Development: Contribute to deep learning development: GPU workload orchestration, custom PyTorch training loops, and model architecture support. - ML Lifecycle & Reproducibility: Maintain reproducibility and consistency across the ML lifecycle: versioned configs, experiment tracking, and online-offline consistency tooling. - Scalability & Reliability: Collaborate with infrastructure teams on scalability — node pools, resource monitoring, CI/CD migrations. Participate in weekly rotation to triage and resolve alerts from Airflow, dbt, and related systems. - Agile Collaboration: Thrive in a fast-paced agile environment with rapid decision-making processes. You will collaborate daily with back-end developers, data scientists, infrastructure engineers, and product managers. - Mentorship & Team Culture: You will actively contribute to our engineering culture, share knowledge, and ensure every team member feels comfortable, supported, and empowered to grow in their role. PROFILE We are looking for a Senior ML Engineer who deeply understands both the ML training lifecycle and the specific challenges of putting machine learning models into production at scale. - 5+ years minimum of experience as an ML Engineer or a similar role - End-to-End ML Ownership: Problem framing, baselines, experimentation, deployment, and iteration - Python Proficiency: Extensive knowledge for ML pipeline code: preprocessing, training/evaluation workflows, experiment utilities, and reproducible configs - Training Mechanics: Comfortable implementing training mechanics where needed (custom steps/metrics, dataloading patterns, performance-conscious preprocessing), not only notebook-level prototyping - ML Frameworks: Practical experience training and evaluating models with scikit-learn, LightGBM, PyTorch for deep learning - Performance Optimization: Experience optimizing memory usage during data preprocessing and model training - Experiment Management: Hyperparameter tuning, experiment tracking, and reproducible training (configs, seeds, versioning) - Cloud & Infrastructure: Experience with Amazon Web Services. Familiarity with scalability, reliability, and security topics - ML Production Awareness: Understanding of the challenges involved in running ML models in production (familiar with topics such as feature store, training-serving skew, etc.) - Model Serving: Experience with model serving infrastructure (real-time or batch inference, latency/throughput optimization) is a plus - Excellent communication skills in English OUR STACK Python · Scikit-learn · LightGBM · PyTorch · DBT · Spark · MLflow · Prometheus · Terraform · Airflow · Kubernetes · Amazon Web Services BENEFITS - Excellent benefits that will depend on the country you're based in

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company that alters the entertainment industry to a new level of perception and engagement. We are building the future of live entertainment. We believe that by providing people with the best and highest-quality live streaming experience in entertainment, we can tackle the world’s “problems” better, together! We are seeking an experienced Python Developer (ML) to join our dynamic team ML team. Our technology stack: Languages: Python; Monitoring: Prometheus, VictoriaMetrics, Grafana, Grafana Loki, Sentry; DBs: MariaDB, Clickhouse, Redis; Streaming: Apache Kafka; Workflow management: Apache Airflow, Argo Workflow; Infrastructure: k8s, gitlab. Job Responsibilities Design and build production-grade Python services for running and maintaining ML applications for different domains: RecSys, CV, Classic ML, NLP. Develop and maintain data pipelines for training, validation, batch inference workflows Build internal tools and reusable modules for the ML team Implement monitoring and observability for ML services using metrics, logs, and dashboards. Contribute to continuous integration and delivery pipelines (testing, packaging, and automation). Develop visualization and debugging tools for model outputs — including active learning and content analysis interfaces. Ensure that all components are reliable, testable, and easy to maintain. You’ll thrive here if you have 3+ years of experience as a Python Developer, Backend Engineer, or Data Engineer. Strong Python skills (asyncio, FastAPI, pydantic, typing, modular architecture). Proven experience designing and deploying production systems with Docker, Kubernetes and CI/CD. Familiarity with ML workflows (you don’t need to train models yourself, but you understand how they’re served, retrained, and monitored). Experience building data pipelines and integrating with various data sources. Knowledge of metrics, logging, and observability best practices (Grafana, Prometheus, Loki, etc.). Strong understanding of testing, clean code, and maintainable software design. Qualification that can be a plus: Experience working with machine learning teams or MLOps pipelines. Experience with distributed systems or high-load backend services. Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR Interview (40 min); Technical Interview + Live Coding (1.5 hour); Final Interview (1 hour).

Location: Riga, Latvia Workplace: hybrid About the Client Our client is an international Electronic Money Institution specializing in online payment processing solutions. They offer a range of services including payment gateway services, global payment processing, merchant accounts, open banking, and recurring and mass payments. Their diverse clientele includes online businesses from various sectors, supporting multiple currencies and payment methods. Role Overview As a Data Engineer, you will have the opportunity to work with cutting-edge data technologies and play a key role in transforming complex data into actionable insights. You will be part of a skilled team that values innovation and collaboration, working in a hybrid environment based in Riga, Latvia. This role offers a unique chance to impact a growing fintech company while developing your expertise in data engineering. Key Responsibilities Work with various data sources and integrate them into internal systems. Develop, optimize, and maintain ETL pipelines and data ingestion processes. Take ownership of data lakes, including their maintenance and documentation. Transform complex data structures into machine-readable formats. Design and maintain databases and data infrastructure. Work closely with other departments to verify the relevance, quality, and accuracy of data. Identify opportunities to improve the reliability and efficiency of existing data processes. Requirements Strong proficiency in Python. Strong knowledge of SQL. Experience with Git. Hands-on experience designing and maintaining databases. Good understanding of data engineering best practices. Strong attention to detail and critical-thinking skills. Ability to effectively manage priorities and work on multiple tasks. Experience with Apache Airflow - nice to have. Experience with Docker - nice to have. Languages: English, Russian Experience in fintech Key Soft Skills Strong analytical and problem-solving skills with excellent attention to detail. Ownership mindset, proactivity, and ability to work independently and manage priorities. Strong communication and collaboration skills with the ability to work effectively across teams. What We Offer Competitive salary aligned with experience Collaborative and transparent team culture High-impact role in a scaling fintech company Recognition of personal milestones and achievements Social benefits

Обязанности: • разработка и совершенствование End-to-End ML-пайплайнов • разработка продакшен-пайплайнов обработки данных • работа с огромными объёмами данных Сбера (петабайты) на PySpark, исследование подходов применения их в моделях • писать эффективный и масштабируемый код для тренировки и инференса моделей на PyTorch, проводить эксперименты на GPU-кластере • performance оптимизации кода по обработке больших массивов данных или онлайн сервисов рекомендаций с высокой нагрузкой • менторинг младших членов команды, обмен знаниями и экспертизой. Требования: • математический бэкграунд • хорошее знание Python и ключевых фреймворков для работы с данными (PySpark, PyArrow, Pandas) • опыт написания качественного production кода • опыт написания промышленных пайплайнов обработки данных, содержащих множество шагов, зависимостей и сложную логику • опыт использования Airflow (или другого industry-standard оркестраторов пайплайнов, т.к. Luigi, Dagster и т.д.) • хорошее понимание баз данных SQL / NoSQL • навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимуществом • опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки. Условия: • комфортный современный офис рядом с м. Кутузовская (опционально) • возможность выбрать удобный график – офис/гибрид/удаленка (опционально) • ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования) • корпоративный спортзал и зоны отдыха • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития • программа адаптации и помощь руководителя на старте (для вакансий уровня Junior) • расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа • гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ • подписка Прайм с возможностью совместного использования на трёх близких • вознаграждение за рекомендацию друзей в команду Сбера.