Location: Remote, Global
Workplace: Remote
ABOUT SUPABASE
Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth.
ABOUT THE ROLE
We’re looking for a Data API Engineer to join our Data API Team and help improve the feature set, reliability and performance of our Data API, based on the PostgREST project.
This role is ideal for someone who thrives in async, fast-paced environments and is excited about building developer tools that scale to millions.
WHAT YOU’LL BE RESPONSIBLE FOR
- Work on PostgREST’s PostgreSQL driver (based on Hasql) and remove bottlenecks and improve it’s performance.
- Work on PostgREST development of new features and bug fixes, aligned towards the goal of a multitenant Data API.
- Resolve incidents and escalated support issues, while also improving observability and performance.
- Collaborate cross-functionally with other teams to debug and solve integration issues with the Supabase platform.
YOU MIGHT BE A GOOD FIT IF YOU
- Strong Haskell skills with at least 3 years of experience.
- Experience using the C language.
- Solid knowledge of SQL and plpgsql scripting in PostgreSQL.
- Strong track record of contributing to and engaging with open-source projects. Bonus points if you’ve maintained an open source project.
- Strong experience with providing technical support to users with varying levels of technical expertise.
- Experience with debugging applications under the Linux operating system.
WHAT WE OFFER
- Fully Remote
We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.
- ESOP
Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.
- Tech Allowance
Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.
- Health Benefits
Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.
- Annual Off-Sites
Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.
- Flexible Work
We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.
- Professional Development
Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.
ABOUT THE TEAM
Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.
- ~400 team members
- 60+ countries
- 20+ languages spoken
- Over $1B raised (including our $500M Series F)
- 540,000+ community members
We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.
-Интеграция новых L1 / L2 блокчейнов в существующую платежную инфраструктуру и сопровождение этих интеграций в продакшене. -Реализация и поддержка полного цикла работы блокчейн-сетей:
Location: San Francisco
Perplexity is seeking software engineers to join our Training Infrastructure team. We’re responsible for the large-scale RL and agent evaluation platforms that enable Perplexity to train state-of-the-art models and optimize agent harnesses.
We are full-stack engineers with a broad remit. If you join us, you’ll build the distributed systems that orchestrate AI workloads across global-scale compute infrastructure. You’ll also define novel user and agent interfaces for designing, managing, and launching experiments. You’ll create tools that make experiment results legible to humans and agents alike, enabling everything from ad-hoc experiment retrospectives to closed-loop autoresearch. And much more!
A strong candidate will possess both experience and passion for solving difficult problems at the intersection of AI, distributed systems, and research acceleration.
QUALIFICATIONS
- 2+ years of experience developing and shipping distributed systems for compute-intensive workloads, with a focus on reliability, scalability, and performance.
- Proficiency in a general-purpose backend language such as Python, Rust, C++, or Go, and experience with cloud infrastructure and container orchestration, such as AWS and Kubernetes.
- Familiarity with reinforcement learning (RL), agent evaluation, or ML infrastructure, and an interest in building systems that accelerate experimentation and model development.
- BS, MS, or PhD in Computer Science, Engineering, or a related field, or equivalent practical experience.
WHY PERPLEXITY IS DIFFERENT
- Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious.
- Ownership. You identify the problem, design the solution and ship it.
- Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users.
- Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products.
- Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence.
Location: Beograd, Serbia
Workplace: hybrid
About the role
We’re looking for a highly autonomous Senior Data & ML Engineer who wants to be the true owner of how data works for the teams they support, delivering solutions completely end-to-end, from initial scoping and design through to delivery, implementation, and full business adoption.
Operating with full autonomy, you will work directly with both commercial stakeholders (Product, Finance, Operations, Compliance, and Marketing) and engineering teams. You will translate complex needs into well-defined and well-modelled data products, using scalable processes and pipelines, ensuring those solutions are trusted, documented, and actively used to drive business value.
Beyond foundational data architecture, you will support and lead machine learning engineering efforts. You will lead machine learning engineering efforts by transitioning predictive models into production. This involves building the infrastructure, automated MLOps pipelines, and serving architectures required to deploy, monitor, and maintain machine learning solutions at scale.
What You’ll Be Doing
Data Engineering and Platform
Design, build, and maintain data pipelines and transformations on Databricks using Python, PySpark, and SQL.
Deploy, operationalize, and monitor machine learning models (MLOps) in production environments.
Build and maintain data marts as the primary source of truth for key business domains.
Apply data modelling practices (e.g., dimensional modelling, medallion architecture) to maintain data consistency and reusability.
Implement data quality checks, monitoring, and alerting.
Optimise pipeline performance and cost-efficiency.
Lead and actively contribute to engineering standards and process improvements across the data team.
Ownership and Stakeholder Management
Act as the primary data partner for specific business areas, understanding their processes, goals, and pain points.
Deliver end-to-end solutions, managing scoping, discovery, design, delivery, user adoption, and iteration.
Gather and translate business requirements into technical solutions.
Communicate with engineering peers and commercial stakeholders to define priorities and manage trade-offs.
Identify opportunities where data or machine learning can improve decisions, efficiency, or customer outcomes.
Enablement and Self-Service
Build and maintain datasets that power reporting and dashboards in Preset.
Onboard and support users on Preset to promote data self-sufficiency.
Promote data practices, including data definitions, documentation, and governance.
What You’ll Need to Be Successful
5+ years of experience as a Data/ML Engineer, with a track record of independently owning data/ML solutions from scoping to adoption.
Proficiency in Python, SQL, and PySpark/Spark.
Experience with modern data platforms, such as Databricks (Delta Lake, Unity Catalog, MLflow, workflows).
Stakeholder management skills, with the ability to navigate commercial and engineering discussions, manage expectations, and drive cross-functional decisions.
Data modelling skills and experience designing data marts for analytics and reporting.
Experience building production pipelines with orchestration, testing, monitoring, and version control.
Experience with BI tools (e.g., Preset, Tableau, Metabase, Power BI) and data usability principles.
Demonstrated accountability for project outcomes and commercial impact.
Clear, structured communication in English.
Nice to Have
Experience in ML Engineering, including deploying machine learning models to production, maintaining MLOps pipelines, and integrating models into data platforms.
Experience in fintech, financial services, or payments, particularly regarding transaction, reconciliation, settlement, or regulatory reporting data.
Experience with sensitive or regulated data and an understanding of data privacy and governance (e.g., GDPR).
Experience with infrastructure as code (Terraform/Tofu), cloud platforms (AWS, Azure, or GCP), and data engineering CI/CD.
Experience mentoring engineers or analysts.
Interest in applying AI tools to improve data engineering productivity and quality.
Why Join Paysend?
Make a Global Impact:
Join a company that is transforming how people and businesses move money around the world. Your work will contribute to products and services that help millions of customers stay connected globally.
Own Meaningful Outcomes:
We empower our people to take ownership, make decisions, and drive real impact. You'll have the opportunity to shape solutions, challenge the status quo, and see the results of your work firsthand.
Grow with Us:
As a fast-growing global fintech, we offer opportunities to learn, develop new skills, take on new challenges, and advance your career across functions and geographies.
Collaborate with Exceptional People:
Work alongside talented colleagues from diverse backgrounds and disciplines who are united by a shared ambition to build, innovate, and deliver great outcomes for our customers.
Move Fast and Make Things Happen:
We value action, curiosity, and continuous improvement. You'll be part of a culture that encourages experimentation, embraces change, and focuses on delivering meaningful results.
Be Part of Our Journey:
We're building the future of the global money movement. Join us at an exciting stage of growth where your ideas, expertise, and contributions can help shape what's next.
You will own the inference serving stack: prefill/decode disaggregation, continuous batching, KV-cache management, speculative decoding, MoE serving, quantization, and GPU performance engineering with CUDA/Triton.
Задачи:
— Проектировать и внедрять масштабируемые, эффективные и надежные архитектуры данных, поддерживающие бизнес и аналитические потребности.
— Создавать и поддерживать конвейеры данных, процессы ETL и интеграционные решения для больших объемов структурированных и неструктурированных данных.
— Оптимизировать конвейеры данных, базы данных, хранилища данных и озера данных для повышения производительности, надежности, масштабируемости и безопасности.
— Сотрудничать с заинтересованными сторонами для понимания требований к данным, развивать доменную экспертизу и преобразовывать бизнес-потребности в эффективные модели данных и решения.
— Устанавливать и улучшать стандарты качества данных, правила валидации, документацию и практики управления данными.
— Внедрять практики мониторинга и наблюдаемости для выявления узких мест, улучшения производительности и повышения надежности платформы.
— Обеспечивать техническое руководство по архитектуре, масштабируемости, надежности, мониторингу, интеграции и расширяемости.
— Руководить и участвовать в код-ревью, поддерживая высокие стандарты качества кода, производительности и сопровождаемости.
— Наставлять младших инженеров и поддерживать культуру непрерывного обучения и технического совершенства.
— Брать на себя ответственность за производственные инциденты, включая устранение неполадок, анализ корневых причин, эскалацию и долгосрочное решение.
— Независимо вести несколько функций и проектов, координировать работу инженеров и информировать заинтересованных лиц о прогрессе, рисках и зависимостях.
— Помогать развивать инженерные инструменты, платформы и практики, поощрять внедрение лучших методов работы.
— Искать практические способы использования AI-инструментов для повышения продуктивности инженерии, анализа, документации и решения проблем.
Требования:
— Опыт работы в области инженерии данных не менее 8 лет, с сильными навыками в архитектуре данных, ETL и управлении базами данных.
— Отличные навыки программирования на Python или PySpark, а также опыт с Java или Scala.
— Опыт создания сложных сквозных конвейеров данных и интеграционных решений.
— Глубокие знания SQL и опыт работы с реляционными и NoSQL базами данных.
— Опыт работы с технологиями больших данных, такими как Spark, Kafka, Hadoop или аналогичными платформами.
— Опыт работы с инструментами оркестрации и планирования, такими как Airflow, Databricks, Jenkins или аналогичными.
— Опыт проектирования и эксплуатации масштабируемых, надежных и безопасных систем данных.
— Знакомство с облачными платформами AWS, Azure или GCP и соответствующими сервисами данных.
— Опыт работы в Agile-средах, таких как Scrum, Lean или Kanban.
— Сильные навыки решения проблем и принятия решений.
— Опыт наставничества младших инженеров и участия в техническом лидерстве.
— Отличные письменные и устные коммуникативные навыки для эффективной работы с техническими и нетехническими командами.
Будет плюсом:
— Степень бакалавра или магистра в области компьютерных наук, науки о данных или смежных областях.
— Опыт или сертификация Databricks.
— Опыт работы с AWS Redshift, S3, Azure SQL Data Warehouse или аналогичными облачными сервисами данных.
— Опыт внедрения практик управления данными, качества данных или наблюдаемости.
— Опыт руководства кросс-функциональными или многомесячными инженерными инициативами.
— Опыт использования AI-инструментов для повышения эффективности разработки, устранения неполадок, документации или продуктивности.
Условия:
— Полная удалённая работа из Мексики.
— Конкурентоспособный компенсационный пакет и социальные гарантии, включая медицинскую страховку, фонд сбережений и страхование жизни, отпуск и декретный отпуск, а также компенсацию интернета и электроэнергии (условия зависят от страны трудоустройства).
Контакт для отклика и ссылка для подачи заявки:
https://weworkremotely.com/remote-jobs/oportun-sr-data-analytics-engineer-r14153
Act as a trusted/strategic advisor for customers, driving the entire Customer Success lifecycle from onboarding to expansion. Become the trusted Cribl product expert as customers build out observability pipelines to transform data in their organization.
УдалённоSydney; We are a remote-first company and work happens across many time-zones - you may be required to occasionally perform duties outside your standard working hours
As an Associate Data Engineer at BeyondTrust, you will contribute to building and enhancing our data lake which currently consumes billions of events each day. Contribute to data modelling efforts that support identity security use cases and analytical requirements.
You'll design, build, test, deploy, and maintain scalable, reliable platform services and shared libraries. You'll contribute to platform and system architecture decisions with a focus on reliability, scalability, and developer experience.
