Вакансии

Location: Remote Workplace: Remote Our Team Dandelion Health unlocks a layer of unexplored clinical depth that has been previously inaccessible at scale. By combining all the raw multimodal data from community health systems with validated AI models, we deliver regulatory-grade scientific insights and products that give teams the evidence to design better trials, enroll the right patients, and generate AI-powered insights that drive confident decisions across the development and commercial lifecycle. Your Role You are an experienced analytics engineer who knows your way around clinical and electronic health record data. Your primary responsibility is to build, maintain, and optimize the transformation layer of our ELT pipeline, turning raw, messy clinical data into clean, well-modeled, analysis-ready datasets that our clients and internal teams can trust. You will own the full lifecycle of our data models: designing and implementing transformation logic, enforcing data quality and testing standards, optimizing pipeline performance, and documenting data models so they're discoverable and understandable across the organization. You will use your data expertise, programming abilities, and critical thinking skills to support our technical product team in scaling and growing our ability to provide meaningful data. Your team’s ultimate goal is to deliver the highest-quality data possible to our clients, who are building products that improve patient health. You will report to the Data Science Manager, under the Chief Data Officer. In this role, you will be responsible for: - Querying complex source systems in a range of health data sources (e.g., EMRs, ECG data, DICOM data) to identify and map data elements in order to create high-quality datasets to support training AI algorithms and conducting in-depth analyses of patient journeys - Developing and maintaining data transformation pipelines using dbt and Snowflake, ensuring data quality, lineage, and transparency. - Harmonizing multimodal data from multiple health systems into a unified ontological layer ready for use by data scientists and AI developers, with input from clinical experts across the company. - Performing complex data extraction, manipulation, and summarization of large databases to create analytical data models; - Implementing data quality tests, CI/CD and version control best practices for analytics codebases throughout the data modeling pipeline. - Supporting software engineers in optimizing processes and technical solutions for de-identification and ETL of clinical data from disparate health system cloud environments to Dandelion Health’s data warehouse. - Working with experts in natural language processing (NLP) to structure and model discrete clinical concepts data that have been abstracted from unstructured and semi-structured text data. - Collaborating with technical and clinical subject matter experts and Dandelion customers to translate research and model requirements into engineering solutions. You are not afraid to dig into massive, confusing, disorganized new datasets and get them under control. You are excited to learn new environments, languages, and skills. This is a small, early stage company with enormous ambitions and everyone pitches in across the team. Qualifications Required - Bachelor’s degree in a quantitative field (ex. Data Science, Biomedical Informatics, Computer Science, Biostatistics) - 3+ years of experience in analytics or data engineering roles where you are responsible for hands-on cleaning and structuring clinical and electronic health record data - Strong dbt and SQL proficiency: writing reusable Jinja macros, implementing custom tests, and comfortable with multi-environment deployments (dev/staging/prod) - 1+ years of experience with extracting, curating, and analyzing data created within the HIT and healthcare delivery ecosystem (e.g., EMR, claims, registry); this may include knowledge of the roles of data exchange and content standards (e.g., FHIR, CDA, CQL) and clinical terminology standards (e.g., ICD, CPT, LOINC, SNOMED-CT, NDC, RxNorm) - Comfort working in a cloud environment (ideally Snowflake and/or AWS). - Proficiency with Git and version control workflows - Is an advocate for bringing software engineering best practices (modularity, unit testing, concise and well-documented code) to a data science team. - Comfortable with ambiguity and creative problem-solving in a fast-paced, rapidly growing startup environment. - Excellent communication skills to advocate for the value of robust analytics engineering solutions and translate customer needs into data solutions. - Passion for improving healthcare and building infrastructure that makes research and clinical AI safer, faster, and more reliable. Nice to Have - Practical experience integrating LLM tools (e.g., Snowflake Cortex, Amazon Bedrock, Azure OpenAI Service) and frameworks (RAG, agent workflows) into data pipelines and product - Proficiency in Python for data cleaning and model feature engineering. - Experience working with AI/ML modeling teams and a conceptual grasp of cloud model deployments and evaluation. - Familiarity with the data aspects of electronic medical records, ex. Epic, Cerner, Allscripts - Any medical ontology experience - Any experience working with DICOM or other imaging modalities - Experience with OMOP common data model - Comfortable with agile tools such as Jira, Linear. - Familiarity using dbt cloud Nature of our work Our work is fast paced and iterative. We are growing, and we want to support our team members to grow in their skills as well. We are building a team that approaches problems with a diversity of perspectives, values experimentation, and refining our approach based on that experimentation. We work with the full spectrum of healthcare data from tabular data, videos, images, waveforms, etc. If a health system collects it, we might work with it! If this looks like a partial fit, please reach out, we would love to share more about the work we do for you to understand if it would be a good fit for you. There is occasional travel for in-person company working days on roughly a quarterly basis. Team Benefits - Remote work and flexible hours. Availability needed for meetings, which we try to keep to a healthy minimum - Complete wellness benefits including healthcare, dental, vision, PTO, sick days and more. Ask for details - Professional development days to build your skills - Collegial work environment - Academic bent towards inquiry and problem solving but start-up speed and flexibility - Great balance of focus time to work on projects but easy to access team members to discuss issues and work collaboratively - Dandelion is a mission-driven company that is focused on improving patient care

Meet Arago and the Aragonians Arago is an AI and computer hardware company whose mission is to drive the course of history forward. We do so by accelerating breakthroughs at the intersection of AI and semiconductors. Founded in 2024 by AI researchers and physicists with deep expertise in photonics, electronics, software, mathematics, and machine learning, Arago brings together a lean team of engineers and scientists from the world’s top companies and research labs. Composed of nine nationalities and operating from hubs in France, North America, and Israel, we believe in great science and fast achievements. Our work is guided by these core principles: Do great things: we deliver work we’re proud to sign our name to. High velocity: speed matters. We move quickly, one step at a time. One unit: we’re all in this together, with relationships grounded in trust, respect, and camaraderie. Arago is backed by executives from Apple, Arm, Nvidia, Microsoft, and Hugging Face, as well as prominent US and European deeptech venture firms and exited founders. Задачи: — Design and verify custom digital hardware components and architectures that enable high-performance, tightly integrated computation workloads and interface Arago’s custom tensor unit for advanced AI/ML applications. — Design, implement, and verify RTL blocks for memory, control, and compute subsystems within Arago’s custom multiphysics computation unit. — Collaborate with Arago’s system software and architecture teams to define block-level specifications and ensure alignment with performance and integration goals. — Develop and maintain functional verification infrastructure to validate design correctness across simulation and hardware testbenches. — Support synthesis, timing analysis, and backend integration, working closely with Arago’s physical design and CAD engineers. — Contribute to architectural exploration and hardware-software co-design efforts to shape future iterations of Arago’s compute platform. Требования: — Extensive experience in RTL design (Verilog/SystemVerilog) for control logic, datapaths, memory subsystems, and specialized processing units. — Strong understanding of digital architecture, including pipelining, arbitration, memory hierarchy, and system-level integration. — Proficiency in functional verification, including testbench development, assertions, coverage metrics, and debugging (UVM experience is a plus). — Familiarity with ASIC and FPGA design flows, including synthesis, timing closure, and DFT. — Comfortable working across the full hardware stack — from architectural specification and microarchitecture to physical implementation support. — Language: English at a proficient level. French is a plus. Условия: — Competitive cash compensation, with final package based on location, experience, and the pay of team members in similar positions. — Meaningful stock option plan offered at the earliest stage of the company (included in the majority of full time offers). — Relocation bonus and coverage of moving expenses for relocation within 20 minutes of the company’s location. — Healthcare coverage (including family-friendly options), pension contributions, professional development support, and 25 days of PTO, in addition to public holidays. — Ownership of a key technical domain, with significant vertical and/or horizontal growth opportunities, based on performance and individual drive. — Reimbursement of 50% of the public transport subscription fee. — A high-paced, multicultural (with 9 nationalities), and engineering-led environment. Our Hiring Process: Your Journey to Arago — Screening Call : Get to know you beyond your CV. — Technical meeting : Deep dive into your past projects and technical achievements. — CEO Interview : Assess the fit with the team’s culture and long-term vision. — Reference Calls: Mandatory calls with your former managers to validate strengths, weaknesses, and work style. — Technical Assessment: Take-home technical assignment crafted to the role you’re applying for. — Final Interview : Discuss your technical assignment and address any remaining questions with team members.

Задачи: — Разработка с нуля мультиязычного голосового ассистента (обязательно: английский + турецкий) для мобильного приложения и личного кабинета клиента. — Проектирование архитектуры: оценка решений «готовые API vs локальные модели» и последующий вывод open-source LLM в продакшн. — Интеграция AI-сервисов с текущим бэкендом платформы (основной стек: PHP/Laravel, есть элементы legacy на Yii/C#). — На перспективу: задачи на стыке Computer Vision (умный процессинг оплат) и телематики (анализ данных с датчиков топлива, предсказание поломок спецтехники). Требования: — Отличный Python (коммерческий опыт Middle+ / Senior). — Понимание архитектуры бэкенда (будет плюсом опыт соприкосновения с PHP/Laravel или Go). — Опыт разработки голосовых решений (STT/TTS, ASR/NLP), опыт развертывания и кастомизации локальных моделей (LLM) на своих серверах в проде. — English: уровень B2 и выше (чтение документации, работа с зарубежными AI-ресурсами и проектами). Условия: — Локация: Алматы, офис (для сильных кандидатов возможен гибрид или удаленка). — Занятость: Full-time.

Location: Argentina; Uruguay; Colombia AI Senior Support Engineer Hours: Aligned to Chicago time (CT) · Engagement: 80 hrs/month, full-stack + data stack remit About the Role Altoros is staffing a Senior Support Engineer for a client engagement supporting an analytics platform. This is a full-stack and data-stack role: the engineer owns the platform shell, the ingestion and semantic layer, and a bounded amount of embedded analytics component upkeep. The role is commercial-model first: month one is an observe and define phase (baseline setting, onboarding), with the engagement shifting toward outcome-based delivery from month two (issue resolution time, defect reduction against baseline, availability targets). AI-augmented delivery is central to this role and one of its most important elements. Working AI-first with Claude Code is how a single engineer credibly covers this full remit. Altoros builds its delivery on Anthropic's professional courses and certification, and the engineer uses Claude Code across the full range of work — maintenance, bug-fixing, and data work, not just new development — operating inside the client's own Claude Code / AI-tooling accounts. Scope & Responsibilities Platform Shell Maintain and extend authentication and SSO integration Own navigation and application shell components (modern front-end framework, e.g., React / TypeScript) Manage tenant and user management, including multi-tenancy considerations Data & Semantic Stack Build and maintain data ingestion pipelines Operate and extend orchestration workflows in Dagster Develop and maintain transformation logic in dbt and SQL Work with the data warehouse on Google Cloud Platform (GCP), primarily BigQuery Maintain the semantic layer in Cube, including metric definitions and data modeling Embedded Analytics (light, bounded) Customize and update Embeddable component files pulled into the client's repo Maintain theming and keep the Embeddable SDK current Note: Embeddable itself handles the builder, embed serving/rendering, security tokens, and multi-tenancy: this is a maintenance layer, not a build-from-scratch effort Delivery & Documentation Maintain centralized documentation in Confluence, including DBML/database diagrams Capture ongoing knowledge for handover and continuity purposes Work to defined outcome targets from month two: P1 issue resolution/mitigation within one business day, defect reduction against an agreed baseline, and business-hours availability once the client is live Use spare capacity (when live issues don't consume the monthly band) on preventative maintenance, hardening, and onboarding new data sources/integrations Required Skills & Experience AI-first delivery (core requirement): hands-on with Claude Code (or similar) / AI-assisted engineering across the full development lifecycle; Anthropic's professional courses and certification are a strong plus (or readiness to complete them) Full-stack development experience, including a modern front-end framework (e.g. React / TypeScript), authentication/SSO implementation, and multi-tenant application architecture Hands-on experience with Dagster for orchestration (or similar tools) Strong DBT and SQL experience for data transformation Experience with BigQuery and the Google Cloud Platform (GCP) data stack Experience with Cube or a comparable semantic-layer / metrics-layer tool Familiarity with embedded analytics tooling (Embeddable or similar), component customization, theming, SDK integration Comfortable working independently and engaging directly with client stakeholders Strong documentation discipline: Confluence, DBML/ER diagrams Available to work core hours aligned to Chicago time (CT) Nice to Have Background supporting analytics/BI platforms for enterprise or sports/media clients Experience setting SLA style targets (resolution time, availability) and reporting against them Engagement Details 80 hours/month, full remit across platform shell, data/semantic stack, and Embeddable upkeep Backup coverage required for continuity during absences: candidate should be able to hand off context cleanly

Location: Austin; Yerevan Workplace: OnSite About the role Teza's Data Platform team owns the data the firm trades on: every backtest, every live strategy, every portfolio decision starts with data we ingested, cleaned, stored, and served. The scale, in plain numbers: - 1 PB of raw historical vendor data, growing by ~150 GB every day - 120 TB of processed, query-ready data in historical storage - Thousands of scheduled jobs: run by cron today, actively migrating to Apache Airflow - Alternative data delivered directly into the real-time feeds of live trading strategies This is a hands-on position on a small team of data engineers with growth potential. The firm is looking for outstanding technical skills, strong attention to detail, and a desire to architect and build data platforms. Location Austin, TX / Yerevan, Armenia (in-office requirement) Key Responsibilities - Work directly with Portfolio Managers and Quantitative Developers: turn their requirements into datasets and pipelines, and be the person who knows every nuance of the data they trade on. - Design and onboard new data sources into our warehouse; improve the robustness, speed, and scalability of our systems; manage data entitlements. - Build automated systems for data cleansing, anomaly detection, monitoring, and alerting, bad data must never reach a strategy. - Evaluate new tools and technologies for organizing, querying, and streaming large datasets, and when nothing on the market fits, build it. That's how the bitemporal store happened. - Support the production data warehouse the firm depends on. - Develop and maintain vendor relationships aligned with our business objectives. What we're building right now - A bitemporal data store, designed and written in-house from scratch. Every dataset answers both "what did we know then?" and "what do we know now?", which is what lets researchers trust a backtest. - A Python 3.14 migration of a large, long-lived codebase. - Adoption of the latest Apache Airflow: writing DAGs for the thousands of jobs moving off cron. - Pipelines for market data and alternative data: everything from exchange feeds to weather. - Real-time delivery: alternative data flows straight into strategies' live feeds. Pipelines you build sit in the trading path. - CI/CD for all of it, in GitHub Actions. Our Stack Python and Java · Apache Airflow · Slurm · NATS · PostgreSQL · MongoDB · S3 · NFS · GitHub Actions   Basic Requirements - Proficiency in Python and Unix/Linux for data manipulation, scripting, and automation. - Strong SQL, including query optimization and performance tuning, and familiarity with NoSQL. - A solid grasp of data modeling: normalization and denormalization, and the judgment to know when each applies. Nice to have - Financial industry experience or internships. - Java (part of our platform is written in it). - Experience with on-premises data infrastructure. - Familiarity with a cloud platform (AWS or GCP). - Apache Airflow or similar workflow orchestration tools. Benefits - Health, visual and dental insurance - Flexible sick time policy

Location: Salt Lake City, Utah, United States About the Role iCapital is looking to hire a Site Reliability Engineer to join the Site Reliability Engineering team, which plays a critical role in ensuring the platform delivers consistent, reliable service to clients. The services run on Kubernetes in AWS, and this role is focused on maintaining the health, stability, and performance of production environments. This position is ideal for a hands-on engineer who thrives in diagnosing complex production issues where the root cause is not immediately apparent. This role transforms insights gained from production incidents into stronger reliability standards, safer deployment practices, more effective alerting, and automation that helps prevent recurring issues. While metrics, logs, and traces are leveraged daily, the core focus is identifying, resolving, and learning from the issues they reveal. Responsibilities Act as a senior escalation point for complex production issues in Kubernetes-based services, leading hands-on investigation across application, container, Kubernetes, and AWS layers through to root cause. Partner with the teams that own our cluster infrastructure to resolve platform-level issues, and feed what you learn back into reliability standards and improvements. Define and implement reliability and operability standards for Kubernetes-based services, including resource sizing, health checks, scaling patterns, rollout safety, and baseline monitoring, as part of service onboarding. Serve as the incident commander or senior technical lead for high-severity incidents, lead postmortems, and drive systemic improvements through action items and measurable follow-through. Turn recurring investigations into runbooks, diagnostic tooling, and automated remediation that shorten time to resolution and eliminate toil. Coach engineers in systematic troubleshooting and Kubernetes best practices through reviews, game days, and knowledge sharing. Define, implement, and iterate service level objectives (SLOs) and service level indicators (SLIs) that reflect customer and business expectations. Standardize monitoring and alerting through “monitors as code” (Terraform preferred), including quality gates such as severity, ownership, and runbook links. Operate and tune OpenTelemetry pipelines, including sanitizing data, managing cardinality, and enriching telemetry with consistent fields. Maintain the infrastructure behind our monitoring stack, including Helm charts, ArgoCD ApplicationSets, Kinesis streams, Lambda functions, and Prometheus. Participate in on-call rotations with a focus on improving reliability, reducing alert noise, and increasing signal quality over time. Qualifications 5+ years in SRE or related roles, with evidence of technical seniority across multiple services and teams 3+ years of hands-on experience running and troubleshooting production workloads on Kubernetes, with a deep understanding of how Kubernetes schedules, connects, scales, and rolls out workloads Proven ability to independently diagnose complex failures in distributed systems running on Kubernetes, spanning application, configuration, resource, networking, and scaling issues, including cases where the root cause wasn't obvious Strong Linux and networking fundamentals, with the ability to troubleshoot below the container layer Strong production experience with AWS, including how cloud networking and access controls affect workloads running in Kubernetes Strong incident response skills, including leading retrospectives and postmortems and following through on systemic fixes Strong IaC skills (Terraform preferred), with examples of reusable modules, monitors-as-code patterns, or similar standardization work, and the coding ability to build automation and diagnostic tooling Track record of defining SLOs/SLIs and using an observability stack (i.e. Prometheus and Grafana, New Relic, Splunk, or similar) to drive decisions and find root causes quickly Clear written and verbal communication skills with the ability to influence engineering teams through standards, tooling, and practical guidance Kubernetes certification (CKA or CKS) or equivalent depth Experience improving rollout safety and autoscaling behavior for Kubernetes workloads Familiar with common data stores (Postgres, MongoDB, DynamoDB) and how they fail in distributed systems OpenTelemetry instrumentation experience at scale is preferred Benefits The base salary range for this role is $130,000 to $160,000 depending on level.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Задачи: — Сотрудничество с командами оптики, аналоговой и цифровой электроники для оптимизации дизайна вычислительного движка. — Проектирование и создание внутренних инструментов для точного моделирования и оптимизации аппаратного обеспечения. — Анализ влияния физического шума и искажений сигнала на производительность системы с разработкой математических методов их компенсации. — Разработка моделей взаимодействия света и материи в архитектуре для поддержки цифровой и аналоговой команд. — Математическая валидация архитектуры с обеспечением строгих численных доказательств для каждого решения. Требования: — Минимум 5 лет опыта в релевантных отраслях (телекоммуникации, высокоскоростные сенсоры, оптимальное управление, обработка сигналов или смежные области). — Глубокие знания и опыт программирования на C/C++ и Python. — Высшее образование в области математики, физики или информатики с глубокими знаниями численного анализа, оптимизации и математического моделирования. — Сильные навыки системного моделирования, включая идентификацию и моделирование источников вариабельности, шума и искажений с помощью аналитических и численных методов. — Высокий уровень любознательности и подход "первых принципов" к решению нестандартных задач в аппаратно-программном ко-дизайне. — Владение английским языком на профессиональном уровне; знание французского языка будет плюсом. Условия: — Конкурентная денежная компенсация, окончательный пакет зависит от локации, опыта и уровня команды. — Значительный пакет опционов на акции, предлагаемый на ранних этапах компании. — Бонус и покрытие расходов на переезд в радиусе 20 минут от офиса. — Медицинское страхование, включая семейные опции, пенсионные взносы, поддержку профессионального развития и 25 дней оплачиваемого отпуска плюс государственные праздники. — Владение ключевой технической областью с возможностями вертикального и горизонтального роста. — Возмещение 50% стоимости проезда на общественном транспорте. — Работа в высокоскоростной, мультикультурной (10 национальностей) и инженерно-ориентированной среде. Процесс найма: — Скрининговый звонок для знакомства. — Техническое собеседование с разбором проектов и достижений. — Интервью с CEO для оценки соответствия культуре и видению. — Референс-чек с бывшими менеджерами. — Техническое задание на дом. — Финальное интервью с обсуждением задания и ответами на вопросы.

Arago is an AI and computer hardware company focused on accelerating breakthroughs at the intersection of AI and semiconductors. The company was founded in 2024 by AI researchers and physicists with expertise in photonics, electronics, software, mathematics, and machine learning. The team is multinational and operates from hubs in France, North America, and Israel. Задачи: — Design and verify custom digital hardware components and architectures for high-performance, tightly integrated computation workloads. — Design, implement, and verify RTL blocks for memory, control, and compute subsystems within Arago’s custom multiphysics computation unit. — Collaborate with system software and architecture teams to define block-level specifications and ensure alignment with performance and integration goals. — Develop and maintain functional verification infrastructure to validate design correctness across simulation and hardware testbenches. — Support synthesis, timing analysis, and backend integration, working closely with physical design and CAD engineers. — Contribute to architectural exploration and hardware-software co-design efforts to shape future iterations of Arago’s compute platform. Требования: — Extensive experience in RTL design (Verilog/SystemVerilog) for control logic, datapaths, memory subsystems, and specialized processing units. — Strong understanding of digital architecture including pipelining, arbitration, memory hierarchy, and system-level integration. — Proficiency in functional verification including testbench development, assertions, coverage metrics, and debugging; UVM experience is a plus. — Familiarity with ASIC and FPGA design flows including synthesis, timing closure, and DFT. — Comfortable working across the full hardware stack from architectural specification and microarchitecture to physical implementation support. — Proficient English; French is a plus. Условия: — Competitive cash compensation based on location, experience, and team pay. — Meaningful stock option plan offered early. — Relocation bonus and coverage of moving expenses for relocation within 20 minutes of company location. — Healthcare coverage including family options, pension contributions, professional development support. — 25 days PTO plus public holidays. — Ownership of a key technical domain with growth opportunities. — Reimbursement of 50% of public transport subscription fee. — High-paced, multicultural, engineering-led environment. Процесс найма: — Screening Call — Technical meeting — CEO Interview — Reference Calls — Technical Assessment — Final Interview

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's researchers generate and depend on enormous amounts of data — training runs, evaluations, RL transcripts, annotations etc... The Research Data Platform team builds the systems that make that data easy to produce, find, query, and trust. We work in two modes: we build platform components that other systems plug into (for example, a metrics library that training frameworks integrate to record and retrieve run data), and we own core datasets end to end (for example, the data pipeline behind RL transcripts). As the team's tech lead, your job starts with our users. You'll work directly with researchers — and with the engineers who support them — to understand how they actually work, where managing data slows them down, and where a well-built platform component or a well-curated dataset would change what's possible. You'll turn what you learn into technical direction for the team, in partnership with the team's manager, who owns priorities and people. A central ambition you'll drive: a small set of canonical, well-documented datasets — starting with the core data model for RL — that researchers trust and standardize on, rather than every team managing its own copies. You'll spend your first few months close to the code and close to users: shipping improvements in our core systems, embedding with research teams, and building your own map of their workflows. As the team grows, this role has a natural path into formal people leadership for someone who wants it. Responsibilities Work directly with researchers and the engineers supporting them to understand their workflows, identify the highest-leverage opportunities, and shape what the team builds next Set the technical direction for the team across our platform and our datasets Design and build platform components that other teams plug into — libraries, services, and interfaces such as the metrics library used by training frameworks Own core datasets end to end: the pipelines that produce them, the schemas that define them, and the documentation and guarantees that make researchers trust them Drive convergence toward canonical datasets — including the core data model for RL transcripts — that research teams standardize on Lead complex, multi-quarter projects that span several systems and teams, staying hands-on in the code Raise the team's technical bar through design reviews, mentorship, and the quality of your own work You may be a good fit if you: Have built and operated data-intensive systems at scale — pipelines, storage layers, query systems — with strong instincts for data modeling and schema design that hold up as usage grows Have set technical direction for a team, or owned the architecture of a data platform that other teams build on Treat internal users as customers: you do the discovery work, iterate with users, and measure success by adoption rather than by shipping Understand that researchers aren’t typical internal customers — the work is exploratory by nature, workflows differ from team to team, and requirements are discovered through experiments rather than specified up front Can build for that motion — keeping interfaces stable and data trustworthy while use cases change underneath you, and judging when a quick, disposable solution serves research better than a durable one Lead through influence — aligning engineers and stakeholders without relying on formal authority Are results-oriented and pragmatic, willing to do unglamorous work when it's the highest-leverage thing Are excited about learning the fundamentals of machine learning research (deep ML expertise is not required) Care about the societal impacts of your work Strong candidates may also have Experience with large-scale ETL and columnar or analytical storage (e.g., Spark, BigQuery, ClickHouse, DuckDB, Parquet) Experience with metrics or experiment-tracking systems, or high-volume time-series data Experience with dataset management, cataloging, or lineage tooling Built developer tooling or internal data platforms for demanding technical users — including in domains like quantitative trading, where fast-moving, exploratory data work looks a lot like research A working knowledge of machine learning Worked in, or closely with, an ML research lab Interest in — or experience with — people management and growing engineers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Riyadh, Saudi Arabia The Senior Transportation Planning & Traffic Safety Engineer is responsible for leading transportation planning and traffic safety initiatives, ensuring compliance with international engineering standards and best practices. The role involves conducting technical reviews, supporting traffic engineering studies, and coordinating with internal stakeholders and government authorities to enhance road safety and traffic mobility. Experience The ideal candidate must have a minimum of 10 years of relevant experience , primarily in: Transportation Planning Traffic Engineering Traffic Safety Engineering Key Responsibilities The selected candidate will be responsible for, but not limited to, the following: Liaise with company representatives and government authorities to support and implement traffic and transportation safety improvements. Serve as the technical lead for traffic safety engineering assignments and provide technical guidance, supervision, and mentorship to junior engineering staff. Review and develop scopes of work for transportation-related studies and projects, including: Road Safety Audits (RSA) Traffic Impact Studies (TIS) Temporary Traffic Management (TTM) Plans Other transportation engineering and traffic safety studies Provide technical support and engineering recommendations to internal and external stakeholders to improve traffic operations, mobility, and road safety. Review roadway designs, engineering specifications, and proposed infrastructure improvements within and surrounding company facilities, ensuring compliance with applicable industry standards and best practices. Prepare technical reports, engineering studies, meeting minutes, correspondence, presentations, technical notes, and other project documentation. Support the continuous development of the Traffic Safety Services Engineering team by establishing technical training programs, promoting knowledge sharing, and improving engineering processes and best practices. Technical Requirements The candidate must demonstrate strong technical expertise in: Highway Design Transportation Planning Traffic Engineering Traffic Safety Studies Road Safety Audits Traffic Impact Assessments Temporary Traffic Management Traffic Operations and Mobility Analysis Required Skills Thorough knowledge of international transportation engineering standards and guidelines, including: AASHTO Green Book Highway Capacity Manual (HCM) Highway Safety Manual (HSM) Manual on Uniform Traffic Control Devices (MUTCD) Institute of Transportation Engineers (ITE) Guidelines Federal Highway Administration (FHWA) Standards and Guidelines Excellent analytical, problem-solving, and technical evaluation skills. Strong written and verbal communication skills with the ability to prepare high-quality engineering reports, technical specifications, presentations, and professional correspondence. Ability to effectively coordinate with multidisciplinary teams, government agencies, consultants, and contractors. Education Bachelor's degree in Civil Engineering or related with specialization in Transportation Planning and Traffic Engineering . A Master's degree in Transportation Engineering or a related discipline is preferred. Professional Certifications (Mandatory) The candidate must hold at least one of the following professional certifications or licenses: Professional Engineer (PE) Professional Traffic Operations Engineer (PTOE) Professional Transportation Planner (PTP) RoSPA Road Safety Certification Road Safety Professional (RSP) Equivalent internationally recognized professional certifications will also be considered.

Location: Dammam, Saudi Arabia We are seeking a motivated Industrial Engineer to support project execution and performance improvement initiatives. The successful candidate will assist in project coordination, analyze performance data and KPIs, and contribute to continuous improvement efforts to ensure projects are delivered efficiently and on schedule. Key Responsibilities Support the planning, coordination, and execution of engineering projects. Monitor and analyze project KPIs and performance metrics. Coordinate with internal teams, contractors, and stakeholders to resolve project-related issues. Assist in continuous improvement initiatives using Lean and Six Sigma principles. Prepare project reports and maintain accurate documentation. Qualifications Bachelor's degree in Industrial & Systems Engineering or a related field. Fresh graduate or up to 2 years of relevant experience. Internship, co-op, or training in project management, operational excellence, or performance management is an advantage. Knowledge of Lean, Six Sigma, and project management principles. Strong analytical, problem-solving, and communication skills. Full professional proficiency in English. Preferred Certifications Six Sigma Certification PMP Certification (preferred)

Location: Palo Alto; New York; San Francisco; Montréal Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role At Mistral, you’ll build and support the infrastructure behind sovereign AI. As a Site Reliability Engineer in the Fleet team, you’ll work at the intersection of frontier models, products, and compute, ensuring our large-scale Linux environments, cloud systems, and AI workloads run reliably. This role is about more than just systems, it’s about enabling customers to leverage Mistral’s sovereign AI solutions with confidence, while helping us evolve toward modern, cloud-native technologies.   What You Will Do - Own and operate the infrastructure powering Mistral’s sovereign AI, including Linux environments, cloud systems, and AI workloads. - Troubleshoot and resolve incidents to ensure high availability, performance, and security for our models, products, and compute platforms. - Collaborate with research, product, and infrastructure teams to align systems with AI and customer needs. - Provide technical support to customers and internal teams, diagnosing issues, guiding solutions, and ensuring smooth operations. - Explore and contribute to modern cloud-native technologies, including Kubernetes and GPU orchestration, as we evolve our sovereign AI platform.   What We're Looking For - Strong Linux system administration experience at scale. - Proficiency in Slurm and/or Kubernetes to manage workloads effectively. - Familiarity with distributed storage, high performance networking, cloud security, or GPU/AI/ML workloads is a plus. - Customer-focused mindset: Ability to diagnose, explain, and resolve technical issues for users leveraging Mistral’s AI solutions. - Pragmatic, collaborative, and hands-on - you thrive at the intersection of AI, infrastructure, and customer success, and are eager to drive modernisation in a fast-evolving landscape. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris; Stockholm; Madrid; Amsterdam; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role At Mistral, you’ll build and support the infrastructure behind sovereign AI. As a Site Reliability Engineer in the Fleet team, you’ll work at the intersection of frontier models, products, and compute, ensuring our large-scale Linux environments, cloud systems, and AI workloads run reliably. This role is about more than just systems, it’s about enabling customers to leverage Mistral’s sovereign AI solutions with confidence, while helping us evolve toward modern, cloud-native technologies. What You Will Do - Own and operate the infrastructure powering Mistral’s sovereign AI, including Linux environments, cloud systems, and AI workloads. - Troubleshoot and resolve incidents to ensure high availability, performance, and security for our models, products, and compute platforms. - Collaborate with research, product, and infrastructure teams to align systems with AI and customer needs. - Provide technical support to customers and internal teams, diagnosing issues, guiding solutions, and ensuring smooth operations. - Explore and contribute to modern cloud-native technologies, including Kubernetes and GPU orchestration, as we evolve our sovereign AI platform. What We're Looking For - Strong Linux system administration experience at scale. - Proficiency in Slurm and/or Kubernetes to manage workloads effectively. - Familiarity with distributed storage, high performance networking, cloud security, or GPU/AI/ML workloads is a plus. - Customer-focused mindset: Ability to diagnose, explain, and resolve technical issues for users leveraging Mistral’s AI solutions. - Pragmatic, collaborative, and hands-on - you thrive at the intersection of AI, infrastructure, and customer success, and are eager to drive modernisation in a fast-evolving landscape. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Remote - United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius is hiring a Forward Deployed Engineer to work alongside Physical AI customers, shape our core infrastructure products, and test ideas for what we should build next. You will work with enterprises, ISVs, and digital-native companies running training, simulation, synthetic data, evaluation, and model serving workloads. By understanding their systems and helping them reach production, you will uncover requirements that inform our Cloud, Serverless, and Token Factory teams. The goal is to connect needs across Physical AI industries with product decisions, including improvements that benefit enterprise customers more broadly. You will also investigate opportunities for new Nebius products. You will develop hypotheses about unmet needs, examine demand and existing alternatives, and build prototypes to test with customers. Your findings will help determine which opportunities deserve investment and what an initial product should deliver. The work is hands-on. You will write code, deploy and benchmark models, build agents, and troubleshoot infrastructure alongside customer engineers. The position is part of the Physical AI go-to-market team, with close collaboration across customers, NVIDIA, Product, and Engineering. What you will do Work with customer engineers to understand their workloads, infrastructure constraints, and production requirements. Translate Physical AI use cases into requirements that Cloud, Serverless, and Token Factory teams can use, backed by measurements and customer evidence. Identify enterprise adoption barriers and common needs across industries. Work with Product and Engineering to assess gaps and test improvements with customers. Build agents that set up, run, and debug Physical AI workloads, connecting them to clusters, schedulers, storage, and model servers. Deploy and benchmark open-weight models with serving stacks such as vLLM or SGLang, then tune them for customer workloads. Build prototypes and run technical evaluations to answer specific questions about performance, reliability, and product fit. Assess demand and existing alternatives for opportunities outside current product teams’ scope, then build where there is a clear market. Debug across Python, agents, model servers, Kubernetes, GPUs, networking, and storage. Turn successful setups into reusable scripts, deployments, and short guides. What we are looking for Three or more years in software engineering, cloud infrastructure, DevOps, ML infrastructure, or similar, including ownership of a production service, cluster, or platform. Experience working directly with customers or external engineers to scope problems, run evaluations, and explain technical tradeoffs. Ability to turn an unfamiliar customer problem into concrete infrastructure requirements. Practical experience building with LLMs or agents, at work or independently, with an understanding of their internals (e.g., transformers, KV caching, or tool calling) and how to evaluate their outputs. Familiarity with enterprise infrastructure requirements, including identity and access management, network isolation, security, monitoring, and reliability. Strong Python and Linux skills: you can read unfamiliar code, automate a setup, and debug from logs and metrics. Practical experience with containers and Kubernetes, including configuration, networking, storage, and scheduling. A record of getting useful software working with incomplete requirements, measuring results, and following through with the people using it. Helpful experience Enterprise customer engineering, solutions architecture, consulting, or taking a new product from an initial customer problem to adoption. Distributed compute such as Ray, Slurm, Spark, or multi-GPU jobs. NVIDIA GPU workloads, including memory management, drivers, CUDA, NCCL, and monitoring. Model serving with vLLM, SGLang, TensorRT-LLM, or TGI. Robotics, simulation, synthetic data, reinforcement learning, world models, or tools such as Isaac Sim, Isaac Lab, Omniverse, and Cosmos. Infrastructure automation and enterprise integrations, including Terraform, CI/CD, private connectivity, and identity federation. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $179,500 — $224,300 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Задачи: — Проектировать и разрабатывать ETL/ELT пайплайны по цепочке Source → ODS → DDS → витрины данных. — Строить витрины и схемы под аналитику и отчётность; оптимизировать SQL (индексы, партиционирование, предикативный pushdown). — Настраивать доступ к данным через федеративные SQL-движки, REST/JSON API, батч- и файловые выгрузки, асинхронную обработку тяжёлых выборок. — Вести пайплайны в Airflow с инкрементальной загрузкой, идемпотентностью и контролем качества данных (DQ). — Вести каталог данных, глоссарий и data lineage; следить за согласованностью источников. — Доводить задачи до прода в GitOps-флоу (GitLab CI + ArgoCD), контейнеризация (Docker / K8s). Требования: — Уверенный Python и очень уверенный SQL (оконные функции, оптимизация запросов). — Опыт построения ETL/ELT-пайплайнов и оркестрации (Airflow или аналог). — Понимание моделирования данных и хранилищ (DWH / DataMart, слои ODS/DDS, нормализация, партиционирование). — Опыт с реляционными и аналитическими СУБД (PostgreSQL; плюсом — Vertica / Trino / ClickHouse). — Понимание Git, CI/CD и контейнеризации (Docker), базовое понимание Kubernetes. — Внимание к качеству данных, идемпотентности и инкрементальной загрузке. — Интерес к финансовому домену: транзакции, отчётность, регуляторные данные, справочники. Плюсом будет: — Федеративные движки (Trino / Presto), каталоги данных и data lineage (OpenMetadata / DataHub). GitOps (ArgoCD), стриминг (Kafka), dbt, IaC. — Опыт с финансовыми и регуляторными данными, витринами для отчётности, безопасностью данных. — Базовое понимание LLM/RAG (эмбеддинги, retrieval) — как смежное направление команды. Условия: — Работа с современным data-стеком в финансовом домене национального масштаба. — Менторство и турбо-рост в команде, которая катает продукты в прод каждый месяц. — ДМС для вас и членов семьи. — Оплачиваемый отпуск и 100% официальное оформление.

Location: Los Angeles, USA Riot’s Enterprise Technology organization ensures Rioters have what they need to unlock their full potential, from efficient business platforms to next-generation AI capabilities. As a Staff Data and AI Engineer on the Enterprise Data & AI team, you will operate at the intersection of data engineering, data architecture, and AI solutions for Riot Enterprise. You will be instrumental in designing and building the enterprise data warehouse, developing scalable data integrations (connecting platforms like OneStream, Oracle, Workday, and Databricks), and delivering critical Enterprise agentic analytics and AI services. The ideal candidate blends hands-on technical expertise with a strategic, platform-oriented mindset. You will be responsible for creating robust technical solutions, including scalable data pipelines, comprehensive data warehouse models, and AI enabled workflow and process automations. This work involves close collaboration with Enterprise leaders, architects, and system owners, and data specialists to translate corporate strategic and operations business requirements into secure, high-value, and maintainable solutions. The role will report to the Senior Manager, Enterprise Data and AI. Responsibilities: Partner with stakeholders across Finance, HR, Legal, IT, and Operations to understand business workflows, clarify requirements, and translate them into technical designs, with an immediate focus on process automation, conversational agents, and data integrations for key corporate systems. Design, build, and maintain the data and platform components of Riot’s Enterprise AI ecosystem, contributing to reference architectures for RAG/agents (indexing, vector stores, caching) and orchestration frameworks. Contribute to conceptual and logical data models for enterprise domains and help connect those models to business capabilities, processes, and downstream applications. Design, build, and maintain data pipelines, transformations, integrations, and warehouse-oriented data products across enterprise platforms and data systems. Support reporting, analytics, and application capabilities by helping shape reliable data foundations and implementation patterns. Required Qualifications: Bachelor’s degree in Computer Engineering, Computer Science, Information Systems, or related field (or equivalent experience delivering enterprise technology solutions). 8+ years of experience in enterprise applications, data engineering, or platform engineering spaces, including delivery of data and automation solutions at scale. Experience delivering AI (traditional or generative) or advanced agentic automation solutions at scale. Strong technical knowledge of orchestration platforms (Workato, n8n, Camunda) and AI platforms (e.g., Google Vertex/Agent Platform, Anthropic Claude Platform, OpenAI Platform) and their enterprise applications, including Retrieval-Augmented Generation (RAG), as well as knowledge management, data governance, quality, and architecture in enterprise contexts. Hands-on experience building or supporting data pipelines and integrations across enterprise applications, APIs, middleware, and data platforms. Required hands-on experience with Databricks for developing, transforming, and operationalizing data workflows or warehouse-oriented solutions. Strong familiarity with data transformation and data warehousing methodologies, including dimensional modeling and medallion architecture patterns. Strong technical knowledge of enterprise platforms (e.g., Workday, ServiceNow, Coupa, Concur, Oracle, IronClad) and respective integration options. Desired Qualifications: Experience supporting master data, reporting, analytics, or business intelligence use cases. Strong hands-on experience with Workato, including implementing agentic workflows and AI-powered operational analytics and automations. Familiarity with frameworks for agent development (e.g., LangChain, Pydantic AI) and orchestration platforms (e.g., LangGraph, CrewAI, Vertex AI Agent Builder, Microsoft AutoGen, or similar). Experience building or integrating enterprise knowledge search platforms (e.g., federated search, vector DBs, retrieval-augmented generation) for enterprise use cases. Experience with cloud data and application technologies such as AWS data services, dbt, or event-driven integration patterns. Experience leading change in complex organizations and mentoring teammates or helping less technical partners adopt better data and systems practices. For this role, you'll find success through craft expertise, a collaborative spirit, and choices that focus on your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position! Our Perks: Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information. At Riot Games, we put players first . That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application. It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act. Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories: Safeguarding confidential and sensitive Company data Communication with others, including Rioters and third parties such as vendors, and/or players, including minors Accessing Company assets, secure digital systems, and networks Ensuring a safe interactive environment for players and other Rioters These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.

Location: Berlin, Germany Workplace: remote ABOUT YOU We are looking for an Operations Engineer who is technically curious, detail-oriented, a strong communicator, and proactive to join our Global Technical Operations (GTO) team. The best candidate will be someone who thrives in a fast-paced, highly collaborative, and exceptionally dynamic setting and is excited to monitor and investigate production issues across a global platform, help improve how we detect and respond to incidents, analyze trends and patterns in production data, and contribute to better communication with partners and stakeholders during incidents. Strong troubleshooting skills, observability platform experience, and scripting ability are essential, along with experience in SRE, DevOps, production operations, or NOC environments supporting high-availability platforms in the gaming industry. The ability to communicate clearly and effectively in English — both written and verbal — when writing incident updates, shift handoffs, and status page communications will be key to your success in this role. If you’re passionate about keeping critical systems running and continuously improving operational processes and love being the first to spot issues and the one who drives them to resolution for game developers and players worldwide, we would love 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: Serve as the primary dashboard monitor during your shift — continuously watch the GTO Operational Dashboard in Datadog, detect anomalies by correlating signals across APM, logs, metrics, synthetic tests, and Real User Monitoring, and determine whether alerts warrant an incident ticket or can be resolved through immediate investigation. Triage and investigate production incidents — create incident tickets in JIRA Service Management, perform initial technical investigation using Datadog (traces, logs, infrastructure and application metrics), determine blast radius and likely root cause domain, and route to the correct team (Product SRE, Infrastructure SRE, or Engineering) using the smart routing model. Own lower-severity incidents end-to-end from detection through resolution — diagnose, execute runbook procedures, and resolve without escalation where possible. Escalate promptly when an incident is unresolved within defined thresholds or requires a code-level fix. Support the TSO Lead during major incidents as the technical right hand in the war room — surface real-time data (error rates, impact scope, deployment history, related alerts), maintain the incident ticket with live timeline entries and linked evidence, and execute mitigation actions as directed. Draft incident communications under TSO Lead direction, including internal Slack updates, stakeholder notifications, and customer-facing status page updates (status.xsolla.com). Support clear, timely communication throughout the incident lifecycle. During non-incident periods, analyze incident trends, recurring issues, and production bugs — compile data from Datadog, JIRA, and Slack, identify patterns, and contribute findings to regular reports for product and engineering teams. Compile incident timelines and draft initial PIR documents for Post-Incident Review preparation. Track PIR action items post-session and flag overdue items to the TSO Lead. Build and maintain operational automation (alert enrichment scripts, incident templates, Slack workflows, dashboard widgets) and contribute to runbook development — documenting new resolution procedures so they can be repeated by any Operations Engineer on any shift. Conduct structured shift handoffs covering active incidents, at-risk services, upcoming deployments, and follow-up items. Participate in knowledge transfer sessions with SREs to continuously expand independent resolution capability. Cover for the TSO Lead during vacations, absences, or emergencies — including severity classification, escalation decisions, stakeholder communications, and basic Incident Commander functions. Publish health reports of critical apps periodically. Qualifications: Previous experience working at a gaming company is required — you understand the pace, player expectations, live operations dynamics, and the operational demands of the gaming industry. 4+ years of experience in SRE, DevOps, production operations, NOC, or technical operations in a high-availability environment. Strong troubleshooting and investigation skills — ability to take an alert or user-reported symptom and methodically trace it through the stack: application logs, APM traces, infrastructure metrics, database queries, and network paths. Hands-on experience with Datadog (or equivalent observability platform: Grafana, Splunk, New Relic, Elastic) — navigating APM, building log queries, reading infrastructure dashboards, interpreting SLO burn rates, and configuring monitors and alerts. Proficiency in at least one scripting language: Python, Go, or Bash. You will write automation scripts, build operational tooling, and work with APIs. Clear written and verbal communication skills in English — ability to write incident tickets, investigation notes, Slack updates, shift handoff reports, status page communications, and PIR drafts that are clear, concise, and useful to both technical and non-technical audiences. Working knowledge of Kubernetes and cloud infrastructure (GCP preferred, AWS/Azure acceptable) — understanding of pods, deployments, services, ingress, node health, and how to investigate Kubernetes-related production issues. Understanding of SLOs, error budgets, and burn-rate alerting — knowing what a multi-window burn-rate alert means, how error budgets deplete, and how SLO breaches translate into incident severity. Experience with incident management tooling: JIRA or JIRA Service Management, PagerDuty or OpsGenie, Slack, and Confluence. Experience with or strong interest in AI/ML-assisted operations: anomaly detection, alert correlation, predictive monitoring, or automated remediation. Comfort with 24x7 shift-based operations as part of a follow-the-sun model with handoff overlaps. Weekend on-call (rotating) is required. Nice to Have: Familiarity with Datadog Service Catalog, synthetic monitoring, and RUM (Real User Monitoring). Experience with distributed systems debugging: tracing failures across microservices, understanding cascading failures, and reading distributed traces end-to-end. Exposure to database operations (MySQL, PostgreSQL, Redis, Kafka) at a level sufficient to investigate connection pool exhaustion, replication lag, slow queries, or queue backlogs during incidents. Familiarity with CI/CD pipelines and deployment tooling (GitLab CI, ArgoCD, Helm) — enough to correlate recent deployments with production issues and identify rollback targets. JIRA Service Management administration experience: workflows, automation rules, SLA timers, and queues. ITIL Foundation certification is a plus but not required — practical experience matters more. 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 through a comprehensive Benefits Program. This includes unlimited Flexible Time Off, Gym membership, monthly train ticket 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. The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com Explore more opportunities at: https://xsolla.com/careers

Location: Costa Mesa, United States WHAT YOU'LL DO Aerodynamic design of unmanned air vehicles/missiles at conceptual, preliminary, and detail design maturities Aerodynamic analysis of unmanned air vehicles, using both low and high order methods, including analysis tool development and improvement as needed Stability and control analysis Aircraft performance modeling and simulation Aerodynamic loads generation Wind tunnel test planning, execution, and analysis Flight test planning, execution, and analysis REQUIRED QUALIFICATIONS BS or higher degree in Aerospace Engineering 3+ work experience as an individual contributing engineer Experience with aircraft performance and analysis predictions Competent in a variety of aerodynamic analysis techniques including hand calculations, vortex, lattice methods, panel methods, and computational fluid dynamics (CFD) Wind tunnel and flight test experience including data acquisition, data analysis and project coordination Strong programming skills in higher-level languages (e.g., MATLAB, Python) for internal tool development in a version-controlled environment Experience preparing formal documentation (i.e., specifications, test procedures, technical reports, etc.) Passion for defending the United States and her allies Eligible to obtain and maintain an active U.S. Secret security clearance PREFERRED QUALIFICATIONS StarCCM+ experience Ice accretion or icing analysis experience Missile DATCOM, OTIS, or DYMOS Experience with transonic and supersonic flow regimes Active U.S. Secret security clearance