Вакансии

About Sezzle: With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. They are redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. Sezzle is building an innovative, dynamic team passionate about creating a unique shopping journey. About the Role: We are seeking a talented and motivated AI Engineering Intern who is best in class with a high IQ plus a high EQ. This role offers an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement. You will join the Data Science team and play a key role in designing and building foundational A.I. systems at Sezzle. What You'll Do: — Design A.I. systems from the ground up — Generate reliable and accurate training data for A.I. systems — Collaborate closely with engineers, data analysts, and business end users to build effective systems — Write accurate and efficient SQL queries What We Look For: — Proficiency in SQL and Python — Solid understanding of data analysis and database structures — Currently enrolled in a postsecondary institution studying MIS, Business Analytics/Data Analytics, Computer — Demonstrated experience working with Claude or equivalent large language model tools is required; candidates must be comfortable leveraging AI to enhance productivity, research, and communication. About You: — You have relentlessly high standards and continually raise the bar — You ensure defects do not get sent down the line and fix problems permanently — You are not bound by convention and enjoy developing new ways to do things — You value speed and calculated risk-taking in business decisions — You earn trust by listening attentively, speaking candidly, and treating others respectfully — You can respectfully challenge decisions when you disagree and commit once a decision is made — You focus on delivering key inputs with quality and timeliness, rising to occasions despite setbacks Interview Process: — Application submitted — Wonderlic test (30-40 min) — SQL and Python Questions (30 minutes) — Interview with recruiters (30 min) — Interview with engineers (1 hour) — Interview with engineering leadership (30-45 min) — Offer Sezzle’s Technology Stack: Languages: Golang, Typescript, Python Frontend: Typescript - React and React Native Backend: Golang Database: MySQL, Postgres, Elasticsearch DevOps & Cloud: AWS, Kubernetes Version Control: Git CI/CD: Gitlab Testing: Developer-driven, focus on automated unit, integration, and end-to-end tests Compensation: The salary for the A.I. Engineering Intern is $1,000 USD monthly gross.

В компании Google открыта вакансия Engineering Manager для команды, занимающейся инструментами разработки в области искусственного интеллекта. Работа предполагает руководство инженерной группой, которая разрабатывает и поддерживает программные решения, связанные с AI. Кандидат должен обладать опытом управления командами разработчиков, глубокими знаниями в области программирования и технологий искусственного интеллекта, а также умением эффективно организовывать процессы разработки. Местом работы является Варшава, Польша.

Location: Metn, Lebanon About the Toters Toters is an on-demand e-commerce and delivery platform that enables customers to get anything in their city with the highest level of convenience. Technology is at the heart of everything we do. Our product and engineering teams work every day to build experiences that make customers’ lives easier while continuously improving internal systems to deliver faster and at the best cost. If you’re excited about working in a high-growth startup environment and want to be part of a team shaping the future of how people shop in the Middle East, we’d love to hear from you. About the Role We are looking for a Senior AI Backend Engineer to join Toters and help us build and scale the next generation of AI-powered products and engineering systems . This role sits at the intersection of Backend Engineering, AI Engineering, Platform Engineering, and Developer Enablement . We are looking for someone who not only builds AI-powered systems, but also understands how AI is adopted across an engineering organization and can help teams use AI effectively in their day-to-day development and product delivery. The ideal profile is similar to an Forward Deployed Engineer (FDE) : highly hands-on, comfortable working across different technical areas, able to understand ambiguous problems quickly, and capable of turning emerging AI capabilities into practical solutions. You will help define what good looks like for AI engineering at Toters , build reusable foundations, and enable engineering teams to adopt AI tools, agents, and AI-powered development practices. What You’ll Do Design and build backend systems and services powered by AI , integrating AI capabilities into production-grade products and internal platforms. Own and contribute to the AI engineering lifecycle , from experimentation and prototyping through deployment, observability, evaluation, and continuous improvement. Build and evolve AI-enabled developer and engineering platforms that improve productivity and accelerate software delivery. Lead the adoption of AI tools and workflows across engineering , helping teams identify high-value use cases and turn them into scalable solutions. Establish engineering standards and best practices around AI-powered development, agents, evaluation, observability, reliability, and productionization . Explore and implement emerging agentic engineering patterns , including agent-to-agent protocols, agent SDKs, tool calling, orchestration, and autonomous workflows. Build systems that leverage knowledge bases, knowledge graphs, retrieval, and contextual data to make AI applications more useful and reliable. Work closely with Backend, Platform, ML, Product, and Engineering leadership to identify opportunities where AI can meaningfully improve products and internal workflows. Prototype rapidly, validate ideas, and move successful experiments into reliable production systems. Develop reusable frameworks, libraries, and services that allow other engineers to build AI-powered applications without reinventing the foundations. Define and improve AI observability and evaluation practices, including monitoring quality, performance, reliability, cost, and model behavior. Stay current with rapidly evolving AI technologies and translate them into practical engineering solutions for Toters. What We’re Looking For 6+ years of experience software engineering , with a strong background in Backend Engineering, Platform Engineering, or a similar technical discipline. Strong experience building production-grade backend systems , preferably at significant scale. Strong programming skills in one or more backend languages such as Go, Java, or PHP . Hands-on experience building or integrating AI-powered systems and applications . Strong understanding of the AI application lifecycle , from experimentation to production deployment and monitoring. Experience with AI developer tools, LLMs, agents, agent SDKs, and AI-assisted software engineering workflows . Demonstrated experience leading AI adoption or enablement across an engineering team or organization. Ability to understand emerging AI technologies and distinguish between what is genuinely useful in production and what is experimental. Strong understanding of software architecture, distributed systems, APIs, and backend infrastructure . Experience with observability, reliability, monitoring, and production operations for complex systems. Strong problem-solving skills and the ability to work effectively in ambiguous, fast-moving environments. A builder mindset: you are comfortable going from "we should try this" → prototype → production . Nice to Have Experience working with AWS or other major cloud platforms. Experience with Platform Engineering or Developer Experience / Developer Enablement. Experience with MLOps or ML/AI infrastructure. Experience building AI agents and agentic workflows . Experience with Agent SDKs, agent-to-agent communication protocols, and orchestration frameworks . Experience with knowledge graphs, knowledge bases, RAG, or other approaches for grounding AI systems in company/domain knowledge . Experience building AI-powered developer tools or internal engineering platforms. Previous experience in an FDE, Solutions Engineer, Developer Experience, AI Platform, or similar highly cross-functional engineering role . Experience working with modern AI coding and development tools such as Claude or similar AI development platforms .

Задачи: — Проектировать, разрабатывать и оптимизировать графы знаний на базе Neo4j. — Разрабатывать решения Graph-RAG для задач поиска, извлечения информации и использования AI. — Проектировать модели графовых данных, связи между сущностями и общие модели данных. — Создавать и автоматизировать пайплайны для загрузки, трансформации и обработки данных. — Работать со структурированными и неструктурированными наборами данных, включая профилирование, сбор данных, валидацию и проверки качества. — Разрабатывать масштабируемые потоки обработки данных с использованием AWS-сервисов. — Работать с потоковыми данными и обработкой на базе Kafka. — Участвовать в развитии архитектуры, управляемой метаданными, каталогов данных и принципов Data Fabric. — Участвовать в автоматизации data pipelines и разработке пайплайнов на базе AI-агентов. Требования: — Сильный практический опыт работы с Neo4j, включая моделирование графовых данных и оптимизацию запросов. — Практический опыт проектирования и реализации решений Graph-RAG. — Сильные навыки разработки на Python. — Опыт работы со stream processing и Kafka. — Практический опыт работы с технологиями обработки данных в AWS, включая AWS Glue, Data Catalog, Data Lake/Lake Formation и связанные сервисы. — Глубокое понимание data pipelines, data modeling и data architecture. — Опыт обработки как структурированных, так и неструктурированных данных. Будет преимуществом: — Опыт работы с PostgreSQL. — Сильный опыт построения data pipelines на AWS. — Опыт работы с LangChain, CrewAI или аналогичными агентными фреймворками. — Опыт автоматизации data pipelines с использованием AI-агентов. — Знание распространенных моделей данных, metadata-driven processing и принципов Data Fabric. — Опыт интеграции Knowledge Graphs с решениями на базе RAG/LLM. Требования по доступности: — Возможность частично пересекаться с рабочими часами по тихоокеанскому времени США (US Pacific Time), включая доступность до 11:00 AM PT. Условия: — Возможности для профессионального и карьерного развития. — Поддержка в получении профессиональных сертификаций. — Программа менторства. — Медицинская страховка. — Участие в корпоративных мероприятиях. — Гибкие форматы работы (гибридный или удалённый). — Оплачиваемый отпуск и больничные.

Location: Canada; United States Role overview: We are seeking a System Engineer to perform design, integration, verification, and operational support of TT&C/PDT subsystems for current and next-generation remote sensing and communications satellites. The role will interface with spacecraft payload teams, ground-segment developers, and mission-operations teams to ensure reliable command delivery, high-fidelity telemetry acquisition, and robust data handling throughout the satellite life-cycle. Tasks summary: Architecture Concept & Requirements • Define TT&C/PDT functional architecture (command generation, uplink, telemetry downlink, on‑board data handling, RF front‑end). • Conduct trade‑studies for modulation schemes, coding, frequency plans, ranging and link budgets. • Produce System Requirements, Interface Control (ICDs), and Description documents. • Perform requirement management and maintain bidirectional traceability throughout the project lifecycle. • Collaborate with cyber-security to embed resilience and security by design. Design & Development • Lead detailed design of hardware (TT&C transceiver, RF front‑ends, antenna‑pointing) and software (command sequencer, telemetry parser, health‑monitoring). • Perform link‑budget analysis, RF simulation (e.g., STK, Matlab), and error‑budget budgeting. • Verify compliance with CCSDS, ECSS, ITU, and regulatory standards. • Support Satellite Reference Database development and validation Cross‑Functional Coordination, Stakeholder & Program Interaction • Present technical status, risk analyses, and trade‑study results to senior management. • Negotiate and maintain ICDs and interface agreements with internal & external suppliers. • Support B&P (Phase 0 & pre-Phase A). Integration & Verification (IVV) • Develop test plans, procedures, and verification matrices for unit, subsystem, and spacecraft‑level TT&C tests. • Execute RF link testing, BER, command latency, and telemetry integrity verification. • Manage anomaly investigation, root‑cause analysis, and corrective actions. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to client’s knowledge‑base, process enhancements, and standards. Configuration, Documentation & Standards Management • Ensure all artefacts, analysis, software, deliverables and documentations are version controlled in PLM environment. • Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation On‑Orbit & Operations Support • Support launch‑pre‑launch and early‑orbit checkout – validate command uplink, telemetry acquisition, and on‑board software hand‑over. • Provide real‑time C&T support during nominal and contingency operations. • Maintain ground‑segment configuration (gateways, mission control servers, monitoring dashboards). • Support SOOH development and associated operator trainings. Required Qualifications: • B.Sc. in Electrical Engineering, Aerospace or related field with 8+ years of TT&C/PDT System design experience on LEO/MEO/GEO platforms. • Strong knowledge of CCSDS TM/TC packet standards, ECSS telemetry & command protocols, PUS services and ITU frequency regulations. • Proficiency in RF link-budget analysis, S-band/X-band/Ka-band modem architecture. • Strong understanding of aerospace system engineering fundamentals, space environment and orbit mechanics. • Hands-on individual who can support systems integration processes and capability to test systems and resolve problems. • Experience with Confluence and JIRA. • Demonstrated capability to efficiently work with little supervision. • Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity. • Demonstrate excellent written and oral communication skills in English; knowledge of French will be considered an asset (Contact with clients outside Quebec and work on deliverables in English).

Location: Remote - US About the Job: We’re looking for an Engineering Manager to lead LaunchDarkly’s Cloud Engineering team, the team responsible for the foundational infrastructure our products and engineering teams depend on. Cloud Engineering owns LaunchDarkly’s AWS accounts and networking, multi-region Kubernetes infrastructure, Terraform and GitOps workflows, CockroachDB operations, disaster-recovery capabilities, and FedRAMP infrastructure posture. The team is small, senior, and recently rebuilt. This is a frontline leadership role for a manager who treats operational health as a top priority, leads calmly through incidents, and creates leverage through software, automation, and reliable paved paths. In your first year, you’ll lead a marquee infrastructure insourcing program from planning through completion. The program’s cost savings will help fund additional team growth, giving you the opportunity to deliver meaningful business impact while strengthening the infrastructure behind LaunchDarkly’s next stage of scale. This role combines people leadership, operational ownership, and technical judgment. You do not need to be the most senior individual contributor in the room, but you should be comfortable partnering with experienced engineers, guiding tradeoffs, and creating an environment where the team can do its best work. Responsibilities: Lead and develop a senior Cloud Engineering team, providing clear expectations, coaching, feedback, performance management, and career-development support. Own the operational health of LaunchDarkly’s cloud infrastructure, including incident response, on-call health, service-level objectives, resilience, and disaster recovery. Launch and deliver a multi-quarter infrastructure insourcing program, including sequencing work, managing dependencies, communicating milestones, and ensuring a successful transition. Guide technical priorities and tradeoffs across AWS infrastructure, networking, multi-region Kubernetes, infrastructure as code, GitOps, datastore operations, and compliance-related infrastructure. Build leverage through software, automation, and paved paths that help product engineering teams use infrastructure safely and independently. Support migrations by providing guidance, patterns, and enablement while maintaining clear ownership boundaries with partner teams. Establish team norms for effective AI-assisted engineering and identify opportunities to reduce operational toil through AI and automation. Maintain team health and continuity through change, fostering an inclusive, collaborative, and accountable environment. Partner with Service Frameworks, Core Platform, Revenue Platform, Data Platform, and product engineering teams on shared infrastructure priorities and cross-team dependencies. Communicate roadmaps, operational risks, investment needs, and progress clearly to engineering leadership and cross-functional stakeholders. Participate in hiring and team planning as the organization grows. Qualifications: 2+ years of experience managing an infrastructure, platform engineering, or site reliability engineering team at a product company, including people management of an on-call team. Demonstrated ownership of incident response, on-call health, and service-level objective frameworks for critical production systems. Experience leading at least one multi-quarter infrastructure migration or insourcing program from planning through completion. Technical fluency with AWS, Kubernetes, and infrastructure-as-code practices, with the judgment to guide discussions and tradeoffs with senior engineers. Experience taking over an established team and maintaining engagement, performance, and retention through a leadership transition. A clear point of view on team norms and practices for AI-assisted engineering. Strong written and verbal communication skills, with the ability to explain technical and operational priorities to a range of audiences. A thoughtful, calm, and accountable leadership approach, particularly during incidents and periods of change. Nice to Haves Experience with vendor negotiations or cloud cost management. Experience supporting FedRAMP or other compliance-related infrastructure and operations. Experience operating large-scale datastores or OLAP systems. Experience growing a team through funded expansion. Pay: Target pay ranges based on Geographic Zones* for Level M2: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $191,800 - $263,670** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $172,600 - $237,270** Zone 3: All other US locations - $163,000 - $224,070** All Zones Inclusive of a 10% Bonus Target LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @ launchdarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

Location: United States Position Overview Our customers are at the forefront of some of the most interesting data in the world, using SingleStore to push the boundaries every day. To do this well, they leverage the expertise of our Support Engineering Team, composed of technical subject matter experts on the frontlines of critical customer issues. This Support Engineering role skews far more towards engineering than typical technical support as you will need to delve into database internals and memory allocators, investigate Linux and host-related configurations, and diagnose SQL query behavior, all in the name of resolving complex database issues. Our Support Engineers are constantly learning a wide range of customer systems and technical concepts and are thrilled by the new and exciting challenges that they encounter on a regular basis. To accurately identify the source and solution of an issue, this team will take the time to learn about the customer’s business and systems while helping to improve their fundamental SingleStore and database operational knowledge. This often requires additional research and time spent on learning new technologies and tools outside of SingleStore while also being deeply engaged with multiple departments including development teams, query performance engineering, product management, infrastructure SREs, etc. Required Hours: Monday to Friday US West Coast (09:00 AM - 06:00 PM PST) What you'll do: Provide email and live technical support to our enterprise customers, acting as the first line of defense for complex technical issues, bug diagnosis, or resolving critical outages. Identify and reproduce product issues, perform QA, and submit formal bug reports or feature requests to the appropriate Engineering team. Collaborate closely with software developers, sales engineers, and technical account managers to keep all teams up to date with current issues a customer may be facing. Work to streamline and improve various Support and Engineering processes and tools, author new internal run-books or public documentation, and help the team continually improve efficiency and effectiveness. Ensure customers have a positive support experience during every interaction. Your Experience: 4+ years of advanced customer-facing technical support experience. Experience with MySQL or MySQL-like (MariaDB, Aurora, etc) database and SQL Query Optimization. A solid Kubernetes and sysadmin skill set. Also, comfortable testing software and finding its limits, hands-on with Linux, checking utilization of system I/O, measuring network throughput, and are comfortable navigating large log files. Experience with a scripting or coding language. Whether it’s Python, Bash, or Go, you should have a go-to solution for quick and dirty problem-solving and be able to navigate through our code base. Familiarity with distributed systems and AWS/GCP. You understand how organizations deploy and maintain distributed applications and services across multiple machines Bonus points for knowing how to analyze them for performance bottlenecks and remove single points of failure. Strong written and verbal English communication skills. Have the ability to explain technical concepts to a wide range of end-users. About us: SingleStore delivers the cloud-native database with the speed and scale to power the world’s data-intensive applications. With a distributed SQL database that introduces simplicity to your data architecture by unifying transactions and analytics, SingleStore empowers digital leaders to deliver exceptional, real-time data experiences to their customers. SingleStore is venture-backed and headquartered in San Francisco with offices in Sunnyvale, Raleigh, Seattle, Boston, London, Lisbon, Bangalore, Dublin and Kyiv. Consistent with our commitment to diversity & inclusion, we value individuals with the ability to work on diverse teams and with a diverse range of people. T o all recruitment agencies: SingleStore does not accept agency resumes. Please do not forward resumes to SingleStore employees. SingleStore is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company that does not have a signed agreement with the Company. SingleStore values individuals for their unique skills and experiences, and we’re proud to offer roles in a variety of locations across the United States. Salary is based on permissible, non-discriminatory factors such as skills, experience, and geographic location, and is just one part of our total compensation and benefits package. Certain roles are also eligible for additional rewards, including merit increases and annual bonuses. SingleStore’s base salary range for this role is $90,000 - $130,000 USD per year For candidates residing in California, please see our California Recruitment Privacy Notice . For candidates residing in the EEA, UK, and Switzerland, please see our EEA, UK, and Swiss Recruitment Privacy Notice. COG00072

Location: Foster City, CA Workplace: Hybrid Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE Replit enables people to build software with AI. The infrastructure underneath that experience must make it straightforward to launch services, isolate workloads, and run reliable systems at scale. We're hiring a hands-on Engineering Manager to lead Cloud Infrastructure: the shared infrastructure as code (IaC), networking, storage, compute, and service mesh platforms that Replit's product and platform teams depend on. You'll lead and grow an existing engineering team building and operating these foundations, including Kubernetes, shared edge networking, service mesh and workload identity. This is a platform-building role with production accountability. You should be comfortable going deep on a design or incident while developing a team that does not depend on you for every decision. WHAT YOU'LL DO - Own the cloud-platform roadmap. Lead the team's IaC, networking, storage, compute, and service mesh platforms. Translate product, platform, reliability, and security needs into sequenced outcomes, balancing foundational investment, lifecycle work, and delivery commitments against the team's capacity. - Make infrastructure repeatable and self-service. Build maintained IaC interfaces for services, cells, connectivity, identities, and shared resources. Enable internal customer teams to provision infrastructure without bespoke coordination or dependence on individual experts. - Operate what the team builds. Own platform availability, upgrades, isolation, recovery, and incident remediation. Maintain clear SLOs, sustainable on-call coverage, and primary and backup owners for critical systems. - Stay technically engaged. Review designs and production changes, debug difficult failure modes, and use AI coding tools—including Replit—to prototype and automate. Apply rigorous review and verification to AI-generated infrastructure changes. - Build and grow a high-ownership engineering team. Coach engineers, develop technical leaders, set clear expectations, manage performance, and hire against agreed needs. Delegate meaningful ownership as the team grows. WHAT YOU'LL BRING - Demonstrated engineering management. You have led and developed engineers, made prioritization and performance decisions, hired thoughtfully, and delivered through a team—not only acted as its strongest individual contributor. - Software-oriented infrastructure depth. You have built and operated cloud platforms or distributed systems and can reason across infrastructure code, Kubernetes, networking, service identity, and stateful dependencies. - Safe-change and production judgment. You have owned consequential migrations and incidents, can explain failure modes and rollback limits, and know when simplifying a system is better than adding another platform. - Platform-product and engineering judgment. You understand internal customers, create interfaces other teams adopt, and make clear tradeoffs among reliability, developer autonomy, engineering effort, and workload efficiency. NICE TO HAVE - Experience with multi-tenant, cellular, regional, or dedicated enterprise infrastructure. - Familiarity with GCP/GKE, Terraform or similar IaC systems, Cloudflare, Envoy/Istio, SPIFFE/SPIRE, and managed data services. - Experience with large-fleet rightsizing, infrastructure consolidation, or migrating CI compute without disrupting developer workflows. - A track record using AI tools to increase engineering output while preserving production safeguards. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Location: US Remote; New England; Atlanta; North Carolina; New York; Boston; Florida Cyberhaven is looking for a Chief of Staff for Engineering to collaborate and perform as an operating partner and force multiplier for engineering leadership, driving operating cadence, cross-organizational execution, and data-driven decision making across the entire engineering org. This role is accountable for turning strategic priorities into clear execution plans, and for giving leadership the visibility, metrics, and follow-through they need to run engineering like a well-oiled machine. This is a hybrid role that blends program management, project management, and executive operations: the person in this role will sit close to engineering leadership, represent their priorities across the org, and be the connective tissue between strategy and day-to-day execution. Influence and impact come from judgment, trust, and cross-functional credibility rather than direct authority. This role also serves as the primary architect of engineering leadership's monthly and quarterly business reviews, all-hands content, org planning, and leadership offsites providing decision support, surfacing risk, and driving follow-through on the company's highest-priority engineering initiatives. This role goes well beyond traditional chief of staff work. It requires strong executive presence to represent leadership credibly in front of the org and external stakeholders, deep comfort with data and metrics to turn fragmented signals into clear decision support, and an AI-forward mindset to automate the reporting and operating mechanisms that let Cyberhaven scale how it plans, tracks, communicates, and reviews its work. WHAT YOU'LL DO STRATEGIC PARTNERSHIP AND EXECUTIVE SUPPORT - Act as a trusted advisor and thought partner to engineering leadership, helping translate strategic priorities into clear execution plans, success criteria, and operating mechanisms across the org - Own the engineering leadership operating cadence, including staff meetings, monthly and quarterly business reviews, org planning, and leadership offsites, setting agendas, preparing materials, and driving follow-through on decisions and action items - Represent engineering leadership's priorities across the organization, ensuring alignment between engineering, product, and go-to-market teams on key initiatives - Prepare executive-facing communications, board and all-hands content, and cross-functional updates on behalf of engineering leadership - Act as a sounding board and extension of leadership on sensitive or ambiguous organizational topics, including headcount planning, org design, and prioritization tradeoffs - Build trust and credibility across engineering, product, and business stakeholders to effectively drive alignment without formal authority PROGRAM AND PROJECT MANAGEMENT - Own end-to-end planning, execution, and coordination across complex, multi-team programs and time-sensitive strategic projects for engineering leadership - Improve predictability in Cyberhaven's release and planning model by tracking scope changes, readiness risks, and cross-team dependencies - Build and maintain review cadences, status updates, and action follow-up systems that surface execution risk and areas needing intervention across teams and programs - Support high-priority or ambiguous engineering initiatives that need additional structure, executive visibility, and follow-through, often stepping in where no clear owner exists - Improve data hygiene and governance in systems like Jira and related planning artifacts so that ownership, status, and progress signals are reliable DATA AND METRICS-DRIVEN OPERATIONS - Define and standardize success metrics across quality, release health, velocity, and team health to drive greater predictability and accountability - Turn operational signals from across the org into clear, data-backed reporting and decision support for engineering leadership - Own the metrics and narrative behind monthly and quarterly business reviews, ensuring leadership has accurate, timely, and actionable data - Bring a data-driven lens to org health, from delivery metrics to team sentiment, to help leadership spot risk early AI-FORWARD AUTOMATION - Build AI-assisted dashboards and reporting workflows that improve visibility into program health, release scope, delivery risk, and team performance - Create automations that connect tools like Jira, Notion, GitHub, and Slack to surface planning, execution, release, and other delivery signals - Automate recurring chief of staff and program management processes such as status collection, follow-up tracking, review preparation, and stakeholder reporting - Use these workflows to improve business review inputs, leadership updates, and recurring status reporting while reducing manual status chasing WHO YOU ARE - 7+ years of experience in a role combining program management, project management, and executive or leadership support - Prior experience as a Chief of Staff or Engineering Leadership roles a plus - Strong executive presence and the judgment to represent leadership credibly across the org and with external stakeholders - A data-driven, metrics-driven approach to decision making, with the ability to turn fragmented operational signals into clear reporting and insight - Proven ability to drive accountability, coordination, and follow-through across engineering and product teams without direct authority - Strong written and verbal communication skills, including experience owning monthly and quarterly business reviews, executive-facing updates, and cross-functional status reporting - Comfort using automation and AI to improve reporting quality, operating efficiency, and recurring workflow execution - Good judgment in prioritization, escalation, and leadership support in ambiguous or fast-moving situations - Experience owning QBRs, executive reporting, all-hands content, or org planning processes - Familiarity with DORA-style metrics, SLO/SLA thinking, release hygiene, and delivery scorecards - Experience building AI-assisted dashboards, automations, or reporting systems - Experience working in security, SaaS, endpoint, platform, or infrastructure-heavy environments - Experience supporting globally distributed engineering organizations - Prior experience transitioning from a technical or program management background into a Chief of Staff or executive operations role - Located in the Eastern Timezone to support our Global team. Joining Cyberhaven means joining the team building Data Security for the Agentic Enterprise. Traditional tools fall short. Cyberhaven traces the full lifecycle of your data, adapting protection to changing context, so protection moves with the way people actually work, not against it. AI Changed Work. We Protect It. Backed by $250M from leading investors like Khosla and Redpoint, our team includes leaders who built industry-defining technologies at CrowdStrike, Palo Alto Networks, Meta, Google, and more. This role lets you shape the future of data security, working alongside people driven to protect workflows, not just data, for customers who cannot afford to slow down to stay safe. AI Tools Disclosure: As part of Cyberhaven's hiring process, we use recruiting tools that include AI-powered features to help with tasks like scheduling, note-taking, workflow automation, and other recruiting activities ("AI Tools"). The AI Tools may process information you provide during the application and interview process. When AI-assisted interview note taking is used, candidates are notified in advance and have the option to opt out of the AI-assisted interview note taking. Cyberhaven is committed to creating a diverse environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world’s leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You’ll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing’s products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing’s products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing’s research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We’re Looking For Research background: PhD or Master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world’s leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You’ll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing’s products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing’s products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing’s research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We’re Looking For Research background: PhD or Master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $350,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world’s leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You’ll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing’s products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing’s products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing’s research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We’re Looking For Research background: PhD or Master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $350,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Задачи: — Создавать AI-агенты и платформы для них — Строить MLOps-инфраструктуру — Работать с данными для ML Требования: — Опыт работы в роли MLOps Engineer/Data Engineer/Python ML от 3,5 лет — Production-опыт с фреймворками MLOps: Kubeflow, MLflow, Airflow для оркестрации, понимание их интеграции в CI/CD пайплайны — Опыт работы с Docker и Kubernetes (в контексте развертывания моделей как сервисов) — Опыт работы с одним из major cloud-провайдеров (желательно GCP или AWS/Azure с пониманием hybrid-cloud) — Умение работать с большими данными, опыт с Greenplum или аналогичными MPP-системами (Teradata, Exasol) — Знание распределенных вычислений (Spark) — Опыт работы с LangChain/LlamaIndex, FastAPI, знание фреймворков для работы с LLM (Hugging Face, vLLM и т.д.) — Отличные знания Python, SQL на очень высоком уровне для работы с data vault — Знания Git, GitLab CI/CD

Ищем Data Scientist / ML Engineer для запуска кредитного скоринга на международных рынках. Предстоит адаптировать модели и scoring pipeline к новым странам, оценивать качество и обрабатывать разнородные данные — от финансовой отчётности и документов до внешних и альтернативных источников.

Delivery Hero — сервис доставки еды, работающий в 70+ странах мира. Размер команды — 10 000+ | Компания оценивается в $8B+. Задачи и требования в тексте не указаны. Помогают с релокацией.

Location: Vilnius Workplace: remote About Finom   Finom is a European tech startup headquartered in Amsterdam, and we’re on a journey towards revolutionizing the financial landscape for entrepreneurs worldwide. Our mission is to develop an all-in-one financial B2B solution that integrates banking functions, accounting, financial management, and invoicing into a seamless, mobile-first platform.   We recently closed a €115 million Series C equity round (around $133 million), bringing our total funding to approximately $346 million. This significant investment follows a $105 million growth funding round from General Catalyst, a long-term backer since 2021 known for supporting companies like Airbnb, HubSpot, KAYAK, and Stripe.   Finom's platform goes beyond traditional banking, offering invoicing and a growing suite of features, including AI-enabled accounting, aiming to simplify financial management for entrepreneurs. We're actively expanding our reach across key EU markets like Germany, France, the Netherlands, Italy, and Spain.   At Finom, we’re not just redefining the entrepreneurial experience — we’re empowering our employees to make a real difference. Your work matters, and your impact extends far beyond product metrics. We nurture innovation and an inspiring work environment where bold ideas thrive, prioritizing thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and our business as a whole.   Maintaining our start-up spirit, we prioritize thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and, of course, our business. At Finom, we're transforming how small and medium businesses across Europe manage their money - and financial crime prevention sits right at the heart of that promise. As a Senior Machine Learning Engineer, you'll take over DRS: a production ML product that scores our whole client base daily and drives our quarantine, alert suppression, and soon our credit decisions. This is genuine end-to-end ownership on a small team - you'll deploy, serve, monitor, and improve the system rather than inherit a finished one. If you're the kind of engineer who quietly keeps production models honest and wants their decisions to actually reach live traffic, this is your seat. What You Will Be Doing Full-stack ML model development (binary classification and regression) for the detection and prevention of financial crime during transaction processing and client onboarding: gathering requirements, prototyping, and deployment in a production environment. Own and evolve the Dynamic Risk Score (DRS) across all markets — daily scoring of the full client base that feeds decisioning across the client lifecycle. Handle a portfolio of transaction rules with ML-driven detection inside, optimizing their performance and the number of generated alerts. Set up continuous monitoring of model and rule performance in production, and develop the champion-challenger framework so the best-performing model is always the one live in production. Participate in infrastructure development for ML model operationalization and inter-service interactions, so models of varying complexity can be served and inferred. Who You Are At least 5 years as a Machine Learning Engineer or Full-stack Data Scientist, with production deployment experience (incl. API services like FastAPI). Strong in SQL and Python, and with cloud data platforms (e.g. Databricks). Strong architectural skills — able to design and improve infrastructure that serves models of varying complexity. Experience with model monitoring and champion-challenger / A-B evaluation in production. Exposure to graph modeling or foundation models/embeddings is a plus. Critical, analytical thinker — proactive, result-driven, comfortable working with little supervision in a start-up setting. A quantitative education (math, engineering, economics, or CS) and full working proficiency in English. What You Will Get In Return   Make a genuine impact on the product   Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product.   Work in the EU   Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe.   Become a stock options holder   Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders.   Receive unwavering support and care   Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling.   Work & Swim program   Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views.   Equal Opportunity Statement    At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.

Location: Poland Workplace: remote About Finom   Finom is a European tech startup headquartered in Amsterdam, and we’re on a journey towards revolutionizing the financial landscape for entrepreneurs worldwide. Our mission is to develop an all-in-one financial B2B solution that integrates banking functions, accounting, financial management, and invoicing into a seamless, mobile-first platform.   We recently closed a €115 million Series C equity round (around $133 million), bringing our total funding to approximately $346 million. This significant investment follows a $105 million growth funding round from General Catalyst, a long-term backer since 2021 known for supporting companies like Airbnb, HubSpot, KAYAK, and Stripe.   Finom's platform goes beyond traditional banking, offering invoicing and a growing suite of features, including AI-enabled accounting, aiming to simplify financial management for entrepreneurs. We're actively expanding our reach across key EU markets like Germany, France, the Netherlands, Italy, and Spain.   At Finom, we’re not just redefining the entrepreneurial experience — we’re empowering our employees to make a real difference. Your work matters, and your impact extends far beyond product metrics. We nurture innovation and an inspiring work environment where bold ideas thrive, prioritizing thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and our business as a whole.   Maintaining our start-up spirit, we prioritize thorough research, swift implementation of solutions, and ensuring that every effort we make benefits our users, employees, partners, and, of course, our business. At Finom, we're transforming how small and medium businesses across Europe manage their money - and financial crime prevention sits right at the heart of that promise. As a Senior Machine Learning Engineer, you'll take over DRS: a production ML product that scores our whole client base daily and drives our quarantine, alert suppression, and soon our credit decisions. This is genuine end-to-end ownership on a small team - you'll deploy, serve, monitor, and improve the system rather than inherit a finished one. If you're the kind of engineer who quietly keeps production models honest and wants their decisions to actually reach live traffic, this is your seat. What You Will Be Doing Full-stack ML model development (binary classification and regression) for the detection and prevention of financial crime during transaction processing and client onboarding: gathering requirements, prototyping, and deployment in a production environment. Own and evolve the Dynamic Risk Score (DRS) across all markets — daily scoring of the full client base that feeds decisioning across the client lifecycle. Handle a portfolio of transaction rules with ML-driven detection inside, optimizing their performance and the number of generated alerts. Set up continuous monitoring of model and rule performance in production, and develop the champion-challenger framework so the best-performing model is always the one live in production. Participate in infrastructure development for ML model operationalization and inter-service interactions, so models of varying complexity can be served and inferred. Who You Are At least 5 years as a Machine Learning Engineer or Full-stack Data Scientist, with production deployment experience (incl. API services like FastAPI). Strong in SQL and Python, and with cloud data platforms (e.g. Databricks). Strong architectural skills — able to design and improve infrastructure that serves models of varying complexity. Experience with model monitoring and champion-challenger / A-B evaluation in production. Exposure to graph modeling or foundation models/embeddings is a plus. Critical, analytical thinker — proactive, result-driven, comfortable working with little supervision in a start-up setting. A quantitative education (math, engineering, economics, or CS) and full working proficiency in English. What You Will Get In Return   Make a genuine impact on the product   Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product.   Work in the EU   Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe.   Become a stock options holder   Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders.   Receive unwavering support and care   Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling.   Work & Swim program   Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views.   Equal Opportunity Statement    At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.