Вакансии

Задачи: — разработка LLM агентов — создание логики работы и взаимодействия агентов — дообучение NLP моделей — создание RAG систем — вывод и сопровождение моделей — написание API для выводимых моделей. Требования: — знания в области математики, data science — владение Python (pandas, numpy, torch, fastapi, langchain, etc) — знание SQL, spark — приветствуется опыт работы с git, docker — опыт работы с NLP пайплайнами. Условия: — комфортный современный офис рядом с м. Кутузовская — возможность выбрать удобный график – офис/гибрид — ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования) — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте (для вакансий уровня Junior) — расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера.

Location: New York, 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 Tavily, part of Nebius, is the web access layer for AI agents. Over two million developers use us, and our customers include Fortune 500 companies running agents in production. You will own our enterprise product: the roadmap for what large customers need, and the control plane that makes it possible. These are the capabilities that decide whether a large customer can adopt us, trust us, and expand with us. Our product is an API, and our enterprise buyer is an engineering organization. The people you build for are platform teams, architects, and the developers inside those companies who are putting agents into production. You need to be comfortable making product decisions about API surfaces, developer workflows, and technical tradeoffs, not only about business requirements. To build this well, you have to be in the room. You will work alongside customer success, sales, and our forward-deployed engineers, who are in these accounts every week and already know where we fall short, and you will spend real time with customers alongside them. Delivery and implementation stay with forward-deployed engineering and go-to-market. Your job is to turn what you learn into product. The hard part is judgment. Knowing which request is one account's edge case, and which one is the thing every enterprise customer will ask for six months from now. Getting that right is the difference between a platform and a pile of custom work. In your first year, we expect you to own a clear enterprise roadmap, ship the controls that block deals today, and become the person the go-to-market team comes to before a deal gets stuck. This is a hands-on senior IC role with real ownership, reporting to the Director of Product. The product team is small, so you will work directly with the engineers building your roadmap and with the go-to-market teams selling it. Your responsibilities will include Own the enterprise roadmap: what we build for large customers, in what order, and why. Own the platform behind it: organizations and identity, keys and quotas, spend controls, usage observability and audit, policy enforcement, and data residency. Make product decisions on our API surface for enterprise use, so that the developers inside those accounts can build on us without friction. Work with customer success, sales, and forward-deployed engineering to understand what enterprise customers need, and spend time in accounts alongside them to see it first hand. Tell the difference between a single-account request and a pattern worth building for, and be able to defend the call either way. Hand off what belongs to another product area, with the evidence that makes it actionable. Give sales and marketing the positioning, materials, and product understanding they need to sell a technical product well. Represent enterprise customers in roadmap decisions with evidence rather than anecdote. We expect you to have 6+ years of product management experience, with a meaningful part of it spent on enterprise products in B2B, developer platform, or API businesses. Experience building developer-facing or API products, with real understanding of what makes an API good to build against. Experience building platform capabilities that enterprises depend on, such as identity, permissions, quotas, usage controls, audit, or compliance. A track record of working with large enterprise accounts, including recognized logos, and turning what you learned into shipped product. Credibility with technical buyers: platform teams, architects, security, and procurement. Strong understanding of LLMs, AI agents, and how search and retrieval fit into agentic workflows. Hands-on technical background is a strong plus. The ability to turn many messy customer conversations into one clear, prioritized product argument. Proven ability to drive alignment without formal authority, including with product owners who do not report to you. It will be a bonus if you have Background as a forward-deployed engineer, solutions engineer, or solutions architect before moving into product. Experience in search, information retrieval, or NLP. Experience in API-first businesses running both self-serve and enterprise motions. Experience building for regulated industries such as financial services, insurance, or healthcare. 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: • Проектирование и разработка сложных Агентных и AgenticRAG систем. Обеспечение воспроизводимости и отказоустойчивости • Разработка решений начиная от прототипа, заканчивая выводом в промышленную эксплуатацию • Определение ML SysDes решения с учетом разрешенного технологического стека • Участие в валидации и автомониторинге моделей, проведение A/B тестирования Требования: • Высшее образование в сфере компьютерных наук, физ-мата, прикладной математики и информатики. Приветствуются дипломы ведущих технических и научных ВУЗов (МФТИ, МГУ, Сколтех, ВШЭ, ИТМО, МИФИ и др.) • Знание мат. статистики, классического ML, NLP, опыт в постановке и интерпретации экспериментов • Опыт e2e-разработки ML/AI-пайплайнов (в т.ч. RAG-пайплайнов) и проектировании архитектуры AI решений • Умение переводить бизнес-постановку задачи в ML-постановку • Высокий уровень владения Python и SQL • Знание фреймворков, библиотек, алгоритмов машинного обучения: XGBoost, CatBoost, PyTorch, TensorFlow, Transformers • Знание принципов построения RAG, VisionRAG и AgenticRAG систем • Знание архитектур нейронных сетей: RNN, LSTM, трансформеры (BERT, BART, T5) • Знание агентных архитектур (ReAct, Multi-agent и др.) • Знание фреймворков для работы с LLM (LangChain, LangGraph и др.) • Знание веб-фреймворков (FastAPI, Flask), контейнеризации (Docker) • Понимание жизненного цикла моделей (CRISP-DM) Условия: • Гибкий гибрид (обсуждаем индивидуально) • Современный IT-офис вблизи Москва-Сити с фитнес-залом • Ипотека с выгодой для сотрудника и льготные условия кредитования • Бесплатная подписка СберПрайм+ • Скидки на продукты компаний-партнеров • ДМС с первого дня и льготное страхование для близких • Корпоративная пенсионная программа • Обучение за счет компании: онлайн курсы в онлайн-школе Сбера и неограниченный доступ к библиотеке, обучение в Корпоративном университете, тренинги, митапы и возможность получить новую квалификацию • Крупнейшее DS&AI Community — более 600 DS банка, регулярный обмен знаниями, опытом и лучшими практиками, интерактивные лекции и мастер-классы от ведущих ВУЗов и экспертов технологических компаний, дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира

Azumo is looking for a highly motivated Python Engineer to develop and enhance high performing and scalable software infrastructures in AI, NLP and data intensive software environments. This position will give you the opportunity to collaborate with a growing team and bright engineering minds in AI computing. You will enjoy the role if you love designing and developing scalable, high performant backend infrastructure using Python, React + Django / Flask / Eve / FastAPI open-source frameworks and connecting applications to modern cloud-based technologies. Responsibilities: — Design, develop and test server features and robust APIs — Integrate existing applications with third party systems — Evaluate multiple approaches and technologies to solving a problem Requirements: — BS or Master’s degree in Computer Science, related degree, or equivalent experience — 5+ years experience with backend development, Python Django / Flask / Eve / FastAPI — Deep expertise with Linux and hosted cloud environments (Heroku, AWS, App Engine or other) — Practical experience with open source technologies, including SQL and NoSQL DBs — Experience integrating solutions with 3rd party APIs (RESTful, OAuth, JSON) — Self-driven and motivated, with a strong work ethic and a passion for problem solving Preferred Qualifications: — Love for coding and willingness to be agile — Hacker spirit within a collaborative team Benefits: — The Python Engineer will be based remotely — Compensation commensurate with experience and candidate potential — 10 PTO — Training Udemy free — English Lessons — Mentored career development — U.S. Holidays — Profit Sharing — $US Remuneration

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The AI Security team within Reddit’s Security Platform Engineering organization builds security into Reddit’s products, engineering systems, AI platforms, and operational infrastructure so the secure path is the easiest path for both people and agents. A core part of this work is developing practical, high-quality machine learning systems that detect and prevent risks such as prompt injection, jailbreaks, sensitive data exposure, and unsafe or unauthorized AI behavior. Building on Reddit’s centralized LLM Guardrails Platform, which provides a shared security and safety boundary across major products, we are expanding ML-powered protections as Reddit’s AI systems and threat landscape evolve. We are looking for a founding Staff Machine Learning Engineer to lead the development, training, and optimization of models for AI security at Reddit. This is a strategic and hands-on individual contributor role, combining deep ownership of model architecture, training data, and experimentation with technical leadership across teams. You will help Reddit deliver stronger AI protections while preserving a high-quality product experience. How You’ll Have Impact Select, adapt, fine-tune, evaluate, and deploy pretrained models and lightweight classifiers for Reddit-specific security problems. Build reproducible training and evaluation pipelines on Reddit’s ML platform, partnering with platform engineers to improve inference performance, resource efficiency, and operational reliability. Set the technical vision and multi-quarter modeling roadmap, partnering with cross-functional teams to gather requirements, define model architectures, and iterate on model development. Conduct model evaluations and performance analysis to improve accuracy and adversarial robustness, and define launch criteria that balance false positives, latency, throughput, reliability, and cost. Own training-data quality and the production model lifecycle, using monitoring, incident findings, and red-team feedback to guide dataset improvements, retraining, and safe rollout or rollback. Establish best practices for responsible ML development and deployment, including reproducible experiments, testing, model and data lineage, and privacy-aware data use. Stay current with research in NLP, large language models, and relevant multimodal techniques, translating promising advances into measurable model improvements. Mentor engineers and lead technical discussions and reviews, shaping the team’s long-term ML capabilities and AI security direction. Who You Might Be 8+ years of experience developing machine learning models, with substantial hands-on model training experience, demonstrated production impact, and a record of leading complex initiatives across teams. Strong background in Python programming, software engineering, and deep learning frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face Transformers. Deep understanding of neural network architectures and optimization, with proficiency in data preprocessing, tokenization, embeddings, language modeling, and model calibration. Expertise in scalable data pipelines and distributed training frameworks such as Ray Train or PyTorch Distributed, with a strong understanding of hardware and system tradeoffs. Demonstrated rigor in experimental design and model evaluation, including representative holdouts, ablation studies, adversarial tests, and error analysis to diagnose training issues, bias, and generalization gaps. Excellent written and verbal communication, with the ability to explain model behavior, security risk, uncertainty, and tradeoffs to technical and non-technical partners. Preferred Qualifications Experience applying ML to security, trust and safety, fraud, privacy, or related adversarial domains. Experience with adversarial training, model distillation, active learning, or synthetic-data generation to improve model quality, robustness, and training efficiency. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Santa Clara, CA Workplace: onsite Role Overview We are looking for a Senior Software Engineer to own the systems that power a large-scale data collection operation, including the collection platform, operator tooling, data pipeline, and fleet infrastructure. This is an engineering role. Day-to-day teleoperation is performed by a dedicated operator team that you direct — you build what they run on, and you own what comes out of it. Project Details Location: 100% Onsite (Santa Clara, CA, US) Employment: Full-time W-2, Monday–Friday, 9:00 AM–5:00 PM Start Date: ASAP Contract Duration: 12-month contract with possibility of extension Rate: $105/hour What You’ll Do Design, build, and maintain the software behind our data collection stations — teleoperation stack, multi-camera recording, and session tooling. Deploy and upgrade that stack across the fleet without stopping collection; keep workstations, containers, and networking healthy. Own the data pipeline end to end: automated validation, conversion into our dataset format, upload, metadata, and versioning. Build the QA tooling that catches dropped frames, stream desync, bad calibration, and mislabeled episodes before data reaches training. Direct a team of teleoperators — define task protocols and SOPs, onboard them on new tasks and embodiments, review session quality, and unblock them daily. Own fleet reliability: calibration and firmware pipelines, sensor and end-effector integration, root-cause analysis of recurring faults, and vendor escalation. Bring up new stations and new embodiments; report throughput, yield, and data health to the research team. What we need to see MS in CS, Robotics, EE/ME, or a related field (or BS with equivalent hands-on experience). 3+ years building software for real robot systems — not simulation only. A system you designed and shipped that other people depended on daily, and that you kept running. Strong Python and Linux; Docker, git, CI, and SSH-based fleet administration. Robot middleware and real-time multi-sensor recording — ROS 2 or equivalent vendor SDKs. Experience supporting a data collection or teleoperation operation: you have built the tools operators depend on and owned throughput and quality numbers. Comfortable around robot hardware — arms or humanoids, dexterous hands, RGB-D cameras, and the calibration that keeps them honest. Able to lead operators without formal authority: you write clear SOPs, train people, and communicate status without being asked. Ways to stand out from the crowd Humanoid or bimanual platforms (Unitree, Fourier, ALOHA/ARX-class rigs) and dexterous hands. XR teleoperation: Quest / PICO / Vision Pro, motion-capture gloves, whole-body retargeting. Imitation-learning data tooling — LeRobot, HDF5/Zarr episode stores, dataset versioning, S3 at TB–PB scale. Built internal dashboards or tooling for a production line or high-throughput lab. Open-source contributions to robotics data or teleoperation tooling. #L1-CC1 Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.   To know more details (Click here)   In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.     As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com   To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Задачи: — Проектировать и разрабатывать multi-agent системы. — Интегрировать LLM с внутренними инструментами и сервисами. — Разрабатывать backend-сервисы и API для agent workflows. — Реализовывать RAG pipelines и tool/function calling. — Создавать CLI-based agent workflows и инструменты автоматизации. — Разрабатывать Computer Vision pipelines: object detection, multi-object tracking, person re-identification. — Разрабатывать multi-camera multi-person tracking для сетей камер. — Работать с видеопотоками в реальном времени и оптимизировать GPU inference. Требования: — Опыт работы с Node.js ecosystem и Express.js. — Уверенное владение Python. — Опыт работы с LLM APIs и prompt engineering. — Опыт работы с RAG, tool calling или agent frameworks. — Знакомство с Docker, Linux и Git. — Опыт работы с PyTorch и OpenCV. — Опыт в object detection и multi-object tracking. — Опыт работы с YOLO, ByteTrack / BoT-SORT или аналогами. — Понимание person re-identification и vector search. — Опыт работы с Milvus / FAISS. — Опыт обработки видео с ffmpeg / GStreamer. — Работа с RTSP и hardware decoding. Будет плюсом: — Опыт в NLP и ML. — Опыт развёртывания open-source LLM. — Опыт оптимизации inference. — Опыт работы с Vision-Language Models. — TensorRT / ONNX Runtime. Условия: — Удалённый формат работы. — Заработная плата: 1.600–3.200 USD net в месяц.

Location: Greece; Global Workplace: remote As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com   To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.     Main Purpose of the Role   We are looking for translators with experience in English to Greek linguist for patent (native-level fluency of languages specified)  with immediate availability for a patent translation project in the fields of Mechanics, Computer Science and Chemistry.   Project Details:   Job Title: English to Greek Linguist for patent Start Date: ASAP Location: Remote Content Specialties: "Computer Science","Electricity","Chemistry"   Task Type: Translation; Quality Control  CAT Tool: XTM/JIRA  Employment Type: Freelance Main Duties Translate and review patent-related content from English into Greek , with original meaning conveyed in a manner that is readable and understandable to target audience. The Style adequacy is a key aspect for our client; Follow instructions, for example Translation process, CAT tool usage, etc. Communicate effectively and response promptly in English. REQUIRED SKILLS Native fluency in Greek Degree in linguistics, translation or equivalent experience Minimum 2 years’ experience in the translation and/or editing of patent documents. Proficiency use of CAT tools, especially with XTM, JIRA Attention to detail Good availability and quick response times Selected candidates will be invited to complete an the translation test. Approved linguists will be then included in our pool of external partners and professional details will be made available to our global Production teams.   We look forward to hearing from you!   Welocalize Talent Management Team

Location: United Kingdom (Hybrid); United Kingdom (Remote); Spain; Netherlands Workplace: Hybrid Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn https://www.linkedin.com/company/cleo-ai/ for new features and the occasional roast 🔥 MEET THE TEAM 👥 Here at Cleo, we have ~45 ML engineers ✨ They are the builders behind the AI that powers our product. They design experiments, create models that personalise financial insights, deploy fraud detection systems and scale our conversational AI, making sure that what we build genuinely helps people feel better about their money. From shaping product features and building the models that personalise our users' money journeys, to tackling fraud, scaling our systems and giving leaders the insights they need, our data team is at the heart of it all. ABOUT THE ROLE ✍️ We're hiring an ML Engineering Manager to join the existing data science function at Cleo - a collaborative team of ML engineers, analysts, and data engineers - to build and deploy production models that go directly into the product. You'll lead the ML workstream behind our Financial Assistant feature, shaping how Cleo uses LLMs to have more engaging, accurate, and personalised conversations about money. This is a people management role: you'll manage the ML engineers across your squads, own the headcount plan, and be responsible for hiring and team development in your area. - Understand the core problems faced by the Financial Assistant team and coordinate the ML function's contribution to solving them - Find opportunities for model and product improvements in Cleo's extensive customer behaviour datasets - Manage the ML engineers in your squads - coaching and developing them to deliver on the roadmap - Build out the headcount plan and own hiring and team development within your area to support growth WHAT WE'RE LOOKING FOR 🕵️ - Extensive experience building and deploying machine learning models to production - Experience managing and developing high-performing teams of data scientists and ML engineers - A habit of keeping abreast of the latest research and experimenting productively with new technologies, including LLMs and LLM agent design - Experience owning an ML roadmap, driving new ideas through to business impact - Ability to write production-quality Python code, with a willingness to stay somewhat hands-on - Nice to have: domain knowledge of NLP, including evaluating LLM systems and fine-tuning LLMs or other transformer models - Nice to have: a strong ability to communicate findings to non-technical stakeholders concisely and engagingly - Nice to have: experience with containers and container orchestration - Kubernetes, Docker, and/or Mesos - Nice to have: experience using vector databases such as OpenSearch WHAT WE OFFER We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub https://meetcleo.notion.site/Cleo-Candidate-Hub-3b95c63b874580e9a068fdc6c8929ebf 👈 WHAT MATTERS Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Задачи: — Разработка и внедрение автономных ИИ-агентов и генеративных моделей (LLM, мультимодальные системы) для ускорения проектирования, разработки и развертывания ERP-систем, а также создания интеллектуальных интерфейсов автоматизации — от генерации кода до обработки естественно-языковых запросов пользователей. — Создание ИИ-сервисов и автономных агентов для автоматизации бизнес-процессов. — Обучение и тонкая настройка LLM (Large Language Models) и других ML-моделей под задачи компании. — Анализ данных, разработка алгоритмов для прогнозирования, оптимизации и принятия решений. — Интеграция ИИ-решений в существующие продукты компании. — Участие в научно-исследовательских проектах, публикация результатов (при желании). Требования: — Опыт в работы в IT от 5-ти лет. — Опыт работы в области Machine Learning, Deep Learning или Data Science от 3-ех лет. — Знание Python и ряда библиотек для ML/DL таких как TensorFlow, Pandas, PyTorch, scikit-learn и др. — Опыт работы с NLP, LLM (GPT, Llama, Mistral и т. д.), RAG, автономными агентами. — Понимание принципов работы ERP-систем (желательно). — Умение работать с большими данными (SQL, NoSQL). — Знание методов обучения с подкреплением (RL) — будет плюсом. — Английский язык (уровень для чтения технической документации). Условия: — Официальное оформление и стабильный доход по ТК РФ. — Все льготы и преимущества работы в аккредитованной ИТ-компании. — Программа ДМС с первых дней. — Работа в офисе с гибким началом рабочего дня. — Московский офис в шаговой доступности от м. Динамо, оборудованный всем необходимым для комфортной работы и отдыха.

Location: United States Workplace: Remote At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Machine Learning Engineer, Ranking & Retrieval ClickUp is seeking an experienced Machine Learning Engineer to join our Search team. You'll own the ML systems that power search relevance for millions of users and ground our AI in the right context. Your Impact at ClickUp You'll own the full ML lifecycle for ranking and retrieval, from training through deployment and production serving. Our search indexes large-scale, user-generated content across a multi-tenant platform where permissions-aware retrieval is critical. You'll build the systems that decide what surfaces first. Core Responsibilities - Train, deploy, and serve ranking models in production, owning the full ML lifecycle - Build ranker features, training pipelines, and offline evaluation frameworks - Design and scale hybrid retrieval combining lexical and vector search (including HNSW with disk offloading) - Run embedding inference at billions-of-documents scale - Improve query understanding through intent modeling and query expansion - Build permissions-aware retrieval that respects multi-tenant boundaries - Create measurement frameworks to evaluate and improve search quality - Collaborate with Search Infrastructure, AI, and backend teams to integrate ranking improvements across the platform Technical Requirements - Bachelor's degree in Computer Science, Machine Learning, or related field - 5+ years of ML engineering experience focused on ranking, retrieval, or information retrieval - Proven full ML lifecycle ownership: training, deploying, and serving models in production - Hands-on ranker model training: feature engineering, pipelines, offline evaluation - Experience building hybrid (lexical + vector) retrieval systems - Experience running embedding inference at large scale - Strong query understanding fundamentals: intent modeling, query expansion Preferred Qualifications - Permission-aware retrieval and multi-tenancy experience - Indexing large-scale user-generated content (not small or static datasets) - Hands-on experience with OpenSearch or Elasticsearch - Sharding, index management, and real-time ingestion at scale - Background in NLP, semantic search, or agentic retrieval - Experience with TypeScript in backend systems   Join Our Mission At ClickUp, we're committed to building the future of productivity software. As our Search Engineer, you'll play a crucial role in shaping the core functionality of our platform and driving our AI initiatives forward. Join us in our mission to make the world more productive! #LI-REMOTE Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. https://clickup.com/careers-terms/candidate-privacy-notice If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice https://t333.s.clickup-attachments-stg.com/t333/d9a53ce2-6d2c-48cd-84b1-ed4e525f9613/Philippine%20Data%20Privacy%20Notice_2024.pdf?view=open for further details. Visa Sponsorship Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions. Fraud Alert ClickUp Talent Acquisition will only initiate contact via an @clickup.com http://clickup.com email or through our official careers portal on clickup.com http://clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com. AI Processing Notice ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.

Location: London, United Kingdom 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 Tavily, part of Nebius, is the web access layer for AI agents. Over two million developers use us, and our customers include Fortune 500 companies running agents in production. We build and run our own index. That means we own the hard problems directly: crawl coverage at scale, freshness, cost per query, and the quality of what comes back. This role owns that infrastructure as a product. When an agent asks a question, the answer has to be relevant, fresh, fast, and affordable. Those four things pull against each other, and someone has to decide which one gives. That is you. You will set what good means for each use case we serve and the bar a change has to clear before it ships, working closely with our evaluation team, who own how we measure it. You will also shape where our index goes next: what it needs to cover, how fresh it needs to be, and what it has to be good at. The most open part of the job is what comes next. Search is being rebuilt for a consumer that is not a person. Agents do not want one result page, they want to break a problem apart, run many retrievals, and decide what to do next. That changes what search infrastructure should look like, and part of your job is to have a view on where ours should go. The hard part is deciding what good enough means. Perfect coverage, perfect freshness, and low cost cannot all be true at once, and the person in this seat is the one who has to make that call for each use case and defend it. In your first year, we expect you to set a clear quality bar for our search products that the team builds against, have a real influence on where our index goes next, and bring us a point of view on where search infrastructure is heading. This is a hands-on senior IC role with real ownership, reporting to the Director of Product. You will work day to day with our search engineering and research teams, with the evaluation team, and with customer success, who bring us quality feedback from real accounts every week. Our search engineers are deeply experienced in large-scale retrieval, and the product team is small, so you will argue your case directly with the people building it. That only works if you have built at this scale yourself. Your responsibilities will include: Set the quality bar and release criteria for search: what good means per use case, and what a change has to clear before it ships. Our evaluation team owns the measurement, and you work closely with them on what to measure and why. Own the depth, latency, and cost tradeoffs across our search products, and make them explicit and defensible. Shape the direction of our index: what it needs to cover, how fresh it needs to be, and what quality bar it has to meet. Build a point of view on where search infrastructure is going as agents, rather than people, become the main consumer, and turn that into a roadmap. Know how we compare to the alternatives customers evaluate, and drive the work that closes the gaps that matter. Work with customer success and directly with customers to understand where our results fall short in real workflows, and turn that into quality priorities. Partner with the data and vertical product owners on what our corpus needs to contain and how results should be shaped per industry. We expect you to have: 5+ years of product management experience, with a meaningful portion spent on high-scale search or ranking systems: web search, feed ranking at a large social platform, or a large ad engine. A background as an engineer, ML engineer, or researcher on a production system in one of those areas. This is a requirement rather than a preference. You will be making tradeoff calls alongside senior search engineers, and you need to have built something at that scale yourself. Direct experience shipping a search or ranking change end to end, including how it was evaluated and what happened after it shipped. A strong data foundation: you can design an experiment, read eval results critically, and tell a real quality improvement from noise. Product judgment to match the technical depth: you can decide what to build and what to leave, and defend it to both engineers and customers. Strong understanding of LLMs, AI agents, and how retrieval fits into agentic workflows. Comfort with ambiguity, moving between strategy and execution without losing the thread. The ability to influence and align cross-functional stakeholders without formal authority. It will be an added bonus if you have: Depth in information retrieval, NLP, or applied machine learning beyond what the role requires. Experience with index tiering, sharding, freshness pipelines, or cost-per-query optimisation at scale. Experience with hybrid retrieval, semantic and lexical search, re-ranking, or human evaluation programs. Experience in API-first or developer-platform businesses running both self-serve and enterprise motions. Experience in a high-growth technology company, especially post-acquisition or startup-within-a-larger-org environments. 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.

Location: Amsterdam, Netherlands 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 Tavily, part of Nebius, is the web access layer for AI agents. Over two million developers use us, and our customers include Fortune 500 companies running agents in production. We build and run our own index. That means we own the hard problems directly: crawl coverage at scale, freshness, cost per query, and the quality of what comes back. This role owns that infrastructure as a product. When an agent asks a question, the answer has to be relevant, fresh, fast, and affordable. Those four things pull against each other, and someone has to decide which one gives. That is you. You will set what good means for each use case we serve and the bar a change has to clear before it ships, working closely with our evaluation team, who own how we measure it. You will also shape where our index goes next: what it needs to cover, how fresh it needs to be, and what it has to be good at. The most open part of the job is what comes next. Search is being rebuilt for a consumer that is not a person. Agents do not want one result page, they want to break a problem apart, run many retrievals, and decide what to do next. That changes what search infrastructure should look like, and part of your job is to have a view on where ours should go. The hard part is deciding what good enough means. Perfect coverage, perfect freshness, and low cost cannot all be true at once, and the person in this seat is the one who has to make that call for each use case and defend it. In your first year, we expect you to set a clear quality bar for our search products that the team builds against, have a real influence on where our index goes next, and bring us a point of view on where search infrastructure is heading. This is a hands-on senior IC role with real ownership, reporting to the Director of Product. You will work day to day with our search engineering and research teams, with the evaluation team, and with customer success, who bring us quality feedback from real accounts every week. Our search engineers are deeply experienced in large-scale retrieval, and the product team is small, so you will argue your case directly with the people building it. That only works if you have built at this scale yourself. Your responsibilities will include: Set the quality bar and release criteria for search: what good means per use case, and what a change has to clear before it ships. Our evaluation team owns the measurement, and you work closely with them on what to measure and why. Own the depth, latency, and cost tradeoffs across our search products, and make them explicit and defensible. Shape the direction of our index: what it needs to cover, how fresh it needs to be, and what quality bar it has to meet. Build a point of view on where search infrastructure is going as agents, rather than people, become the main consumer, and turn that into a roadmap. Know how we compare to the alternatives customers evaluate, and drive the work that closes the gaps that matter. Work with customer success and directly with customers to understand where our results fall short in real workflows, and turn that into quality priorities. Partner with the data and vertical product owners on what our corpus needs to contain and how results should be shaped per industry. We expect you to have: 5+ years of product management experience, with a meaningful portion spent on high-scale search or ranking systems: web search, feed ranking at a large social platform, or a large ad engine. A background as an engineer, ML engineer, or researcher on a production system in one of those areas. This is a requirement rather than a preference. You will be making tradeoff calls alongside senior search engineers, and you need to have built something at that scale yourself. Direct experience shipping a search or ranking change end to end, including how it was evaluated and what happened after it shipped. A strong data foundation: you can design an experiment, read eval results critically, and tell a real quality improvement from noise. Product judgment to match the technical depth: you can decide what to build and what to leave, and defend it to both engineers and customers. Strong understanding of LLMs, AI agents, and how retrieval fits into agentic workflows. Comfort with ambiguity, moving between strategy and execution without losing the thread. The ability to influence and align cross-functional stakeholders without formal authority. It will be an added bonus if you have: Depth in information retrieval, NLP, or applied machine learning beyond what the role requires. Experience with index tiering, sharding, freshness pipelines, or cost-per-query optimisation at scale. Experience with hybrid retrieval, semantic and lexical search, re-ranking, or human evaluation programs. Experience in API-first or developer-platform businesses running both self-serve and enterprise motions. Experience in a high-growth technology company, especially post-acquisition or startup-within-a-larger-org environments. 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.

Location: Tel Aviv, Israel 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 Tavily, part of Nebius, is the web access layer for AI agents. Over two million developers use us, and our customers include Fortune 500 companies running agents in production. We build and run our own index. That means we own the hard problems directly: crawl coverage at scale, freshness, cost per query, and the quality of what comes back. This role owns that infrastructure as a product. When an agent asks a question, the answer has to be relevant, fresh, fast, and affordable. Those four things pull against each other, and someone has to decide which one gives. That is you. You will set what good means for each use case we serve and the bar a change has to clear before it ships, working closely with our evaluation team, who own how we measure it. You will also shape where our index goes next: what it needs to cover, how fresh it needs to be, and what it has to be good at. The most open part of the job is what comes next. Search is being rebuilt for a consumer that is not a person. Agents do not want one result page, they want to break a problem apart, run many retrievals, and decide what to do next. That changes what search infrastructure should look like, and part of your job is to have a view on where ours should go. The hard part is deciding what good enough means. Perfect coverage, perfect freshness, and low cost cannot all be true at once, and the person in this seat is the one who has to make that call for each use case and defend it. In your first year, we expect you to set a clear quality bar for our search products that the team builds against, have a real influence on where our index goes next, and bring us a point of view on where search infrastructure is heading. This is a hands-on senior IC role with real ownership, reporting to the Director of Product. You will work day to day with our search engineering and research teams, with the evaluation team, and with customer success, who bring us quality feedback from real accounts every week. Our search engineers are deeply experienced in large-scale retrieval, and the product team is small, so you will argue your case directly with the people building it. That only works if you have built at this scale yourself. Your responsibilities will include: Set the quality bar and release criteria for search: what good means per use case, and what a change has to clear before it ships. Our evaluation team owns the measurement, and you work closely with them on what to measure and why. Own the depth, latency, and cost tradeoffs across our search products, and make them explicit and defensible. Shape the direction of our index: what it needs to cover, how fresh it needs to be, and what quality bar it has to meet. Build a point of view on where search infrastructure is going as agents, rather than people, become the main consumer, and turn that into a roadmap. Know how we compare to the alternatives customers evaluate, and drive the work that closes the gaps that matter. Work with customer success and directly with customers to understand where our results fall short in real workflows, and turn that into quality priorities. Partner with the data and vertical product owners on what our corpus needs to contain and how results should be shaped per industry. We expect you to have: 5+ years of product management experience, with a meaningful portion spent on high-scale search or ranking systems: web search, feed ranking at a large social platform, or a large ad engine. A background as an engineer, ML engineer, or researcher on a production system in one of those areas. This is a requirement rather than a preference. You will be making tradeoff calls alongside senior search engineers, and you need to have built something at that scale yourself. Direct experience shipping a search or ranking change end to end, including how it was evaluated and what happened after it shipped. A strong data foundation: you can design an experiment, read eval results critically, and tell a real quality improvement from noise. Product judgment to match the technical depth: you can decide what to build and what to leave, and defend it to both engineers and customers. Strong understanding of LLMs, AI agents, and how retrieval fits into agentic workflows. Comfort with ambiguity, moving between strategy and execution without losing the thread. The ability to influence and align cross-functional stakeholders without formal authority. It will be an added bonus if you have: Depth in information retrieval, NLP, or applied machine learning beyond what the role requires. Experience with index tiering, sharding, freshness pipelines, or cost-per-query optimisation at scale. Experience with hybrid retrieval, semantic and lexical search, re-ranking, or human evaluation programs. Experience in API-first or developer-platform businesses running both self-serve and enterprise motions. Experience in a high-growth technology company, especially post-acquisition or startup-within-a-larger-org environments. 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.

Location: Aarhus, Budapest, Dubai, London, Paris, Zurich Programmes offered: Final-year internship, penultimate-year internship, some permanent opportunities Programme duration: 4–6 months, starting in 2027 Locations: Aarhus, Budapest, Dubai, Geneva, London, Paris, Zurich Who qualifies: Penultimate or final-year students completing a bachelor’s, master’s or PhD degree Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes and markets worldwide. Our approach to investing is scientific: we bring together data, research, technology and trading expertise to develop and run systematic strategies. Research is central to how QRT invests. Over the years, we have built a global research and execution platform spanning geographies, asset classes and trading horizons, from high to low frequency. This gives our researchers access to large and diverse datasets, sophisticated research tools and the infrastructure needed to turn research ideas into live trading strategies. Our internships are designed to give students meaningful experience of that process. You’ll join a systematic team, work on real research or trading problems and learn from experienced researchers and traders. The environment is rigorous and collaborative: ideas are tested against data, assumptions are challenged and good questions matter as much as quick answers. Your future role at QRT Throughout the recruitment process, we’ll consider your skills and interests alongside the problems our teams are working on, with the aim of finding the strongest fit. As a Quantitative Research Intern, you could contribute in one of two complementary areas within one of QRT’s systematic teams, spanning high, mid and low frequencies: Research Your focus will be on developing predictive signals from large and varied datasets. You’ll explore the data for patterns and form hypotheses about what might be driving them. From there, research is iterative: you’ll design tests, question the results, adjust your approach and test again. Working with other researchers, you’ll learn to distinguish promising signals from noise. In doing so, you’ll experience the full research process, from an initial observation to something that can be used in live trading. Trading You’ll contribute to the live deployment of QRT’s research by working directly with our systematic trading platform. You’ll monitor how signals behave in production, track performance, improve execution efficiency and help identify and manage potential risks. Working closely with senior Researchers and Traders you’ll investigate how strategies behave in production and look for ways to make them more robust and scalable. You’ll use quantitative analysis and programming to understand what is happening in live systems and determine where improvements can be made. Across both areas, how you approach a problem matter. We’re looking for interns who are curious, creative and collaborative. You should be comfortable exploring ideas, asking questions and learning as you go. Your present skillset Academic background – Pursuing an advanced degree in a quantitative field such as Data Science, Statistics, Mathematics, Physics or Engineering. Quantitative foundations – Strong analytical skills and an interest in using mathematics, statistics and computation to understand complex problems. Programming – Coding experience in at least one leading programming language, including Python, C++ or C#. Research interests – Knowledge of statistics, machine learning, NLP or AI techniques is useful but not essential. Data – Experience exploring large datasets across multiple time horizons is a plus. Problem solving – Able to work through complex problems rigorously while maintaining strong attention to detail. Independence and collaboration – Comfortable working autonomously while exchanging ideas and working closely with colleagues from different disciplines and backgrounds. Communication – Able to explain your reasoning and communicate technical ideas clearly. Languages – Fluent in English; additional languages are a plus. Interviewing Apply Online – Submit your application online. Applications are reviewed on a rolling basis by our Talent Acquisition team. We read applications carefully, so thoughtful answers that explain your interests and motivations are useful. Technical Assessment – Selected candidates will complete a coding challenge focused on core programming and problem-solving skills . Interviews – Shortlisted candidates will take part in interviews, either on-site or via Microsoft Teams. We’ll explore your quantitative and technical thinking, how you approach unfamiliar problems and how you work with others. We also encourage candidates to take part in one of our Data Challenges . These are an opportunity to work on problems relevant to quantitative research and demonstrate your analytical and technical approach. Strong performance may lead to direct follow-up from our team: Challenge data (ens.fr) QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Italy Workplace: Hybrid ABOUT THE ROLE: We're looking for a Conversation Experience Designer to shape how people experience talking with our AI agents: the words, rhythm, and relational dynamics that make an interaction feel clear, credible, and worth coming back to. This role sits at the intersection of linguistics, communication design, and applied persuasion/rapport techniques. You'll define how our agents build trust, handle hesitation and uncertainty, recover gracefully from misunderstanding, and guide people toward action, all in service of one outcome: people choosing to keep using the agent. KEY RESPONSIBILITIES: - Conversation & Flow Design: Design end-to-end dialogue journeys (onboarding, error recovery, edge cases, escalation/hand-off) from the user's cognitive and emotional experience — where they get confused, anxious, or drop off . - Trust & Rapport Patterns: Apply linguistic and rapport-building techniques (framing and reframing, pacing-and-leading, presupposition, mirroring, tension/objection defusing) to reduce user hesitation and increase follow-through. - Prompt Engineering & Tone of Voice: Draft and refine system instructions, guardrails, and context guidelines to shape agent behavior and maintain brand voice. - Prototyping & Testing: Build, simulate, and iterate on agent responses across various user personas and scenarios. - Performance Analysis: Review real transcripts to flag tone mismatches, unclear phrasing, and comprehension failures. QUALIFICATIONS: - Experience in UX Writing, Conversation Design, Conversational UX, or Prompt Design for LLM-driven applications. - Working familiarity with NLP (Neuro-Linguistic Programming) frameworks — rapport techniques, framing/reframing, presupposition, pacing-and-leading — applied pragmatically as tested language patterns, not asserted as clinical fact. - Strong understanding of how Large Language Models operate, including context windows, system prompts, and tool-calling logic. - Ability to transform complex business rules into natural, concise conversational experiences. - Portfolio showing conversation flows, prompt strategies, or interactive agent prototypes. Candidate Privacy Notice https://www.wonderful.ai/careers/candidate_notice

Location: Toronto Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ROLE OVERVIEW: As a Business Development Representative (BDR) at Cohere, you will drive revenue growth by identifying, qualifying, and nurturing high-potential leads for our enterprise AI solutions. You’ll act as the first point of contact for prospects, understanding their business needs and aligning them with Cohere’s products to solve complex challenges like natural language processing, AI integration, and scalable language models. You’ll also have the opportunity to sell cutting-edge IP, that is being newly productised, within your own book of business.   KEY RESPONSIBILITIES: - Proactively research and identify target accounts across region in industries such as finance, technology, manufacturing, healthcare, public sector, etc. using tools like LinkedIn Sales Navigator and CRM platforms to prioritise high-fit prospects. - Conduct 40+ outbound calls and personalised emails daily to engage decision-makers (e.g., CTOs, CIOs, and Business Unit leads), focusing on understanding their pain points and demonstrating how Cohere’s AI solutions can address them. - Qualify leads using the BANT framework (Budget, Authority, Need, Timeline) and document interactions in Salesforce, ensuring a clean and actionable pipeline for the sales team. - Collaborate with marketing to refine messaging and campaigns based on prospect feedback, contributing to a 15%+ improvement in campaign response rates. - Stay updated on industry trends, competitor offerings, and Cohere’s product roadmap to position our solutions effectively and anticipate customer needs. - Run independent sales cycles on smaller opportunities with less overhead, from intro to close. QUALIFICATIONS: - 2+ years of experience in business development, sales, or a related role, with a proven track record of exceeding lead generation targets in a SaaS or tech environment. - Strong communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders and build rapport quickly over phone and email. - Familiarity with CRM tools (e.g., Salesforce, HubSpot) and sales enablement platforms, with the ability to analyse data to optimize outreach strategies. - Experience in AI, machine learning, or enterprise software sales, with a basic understanding of natural language processing (NLP) concepts. - Closing experience is seen as an advantage. - A builder mindset is necessary to succeed here, the challenges will be unique based on the team you’ll be working with, and the role will evolve over time. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Москва, гибрид, RU; Россия О команде Поиск помогает пользователям Авито находить подходящие предложения и связывает покупателей с продавцами. Наша команда отвечает за модель ранжирования, которая влияет на качество выдачи и пользовательский опыт. Мы работаем в полном цикле: от гипотезы до инференса и A/B-теста на десятках миллионов пользователей. Сейчас команда переходит к ранжированию на основе глубокого обучения. Какие задачи вас ждут: развивать архитектуру модели: учитывать пользовательскую историю, контекст выдачи и связь между запросом и объявлением; ускорять контур инференса моделей в продакшен-среде; проектировать и поддерживать пайплайны данных для поиска: контролировать качество, настраивать инкрементальные обновления и фичеинжиниринг; развивать и ускорять пайплайны обучения: настраивать обучение на нескольких GPU и узлах, оптимизировать пропускную способность и стабильность. Мы ждём, что вы: имеете продакшен-опыт в поиске, рекомендациях или ML-ранжировании; работали со Spark и SQL на больших объёмах данных; умеете превращать идеи из статей в работающие эксперименты; имеете опыт в одном или нескольких направлениях: NLP, CV или RL. Будет здорово, если вы: уверенно пишете на одном или нескольких языках программирования: у нас в основном Python и Go; умеете вести ML-задачу в полном цикле: от данных до продакшен-инференса и A/B-экспериментов; хотите развиваться в экспертном направлении. Работа у нас — это: возможность улучшать опыт миллионов пользователей; задачи с высокой нагрузкой и большим объёмом данных; полный цикл работы с ML-задачами: от гипотезы до продакшен-инференса и A/B-тестов; команда с развитой культурой взаимопомощи и обмена опытом; инфраструктура и multi-node-кластер с H100 для обучения и экспериментов; прозрачный карьерный трек и инструменты для роста: семинары, менторство, митапы; возможность работать удалённо или из офисов в четырёх городах России; расширенная забота о здоровье: ДМС, страхование жизни, онкострахование; сервис психологической поддержки, а также финансовые, юридические и ЗОЖ-консультации для вас и ваших близких; корпоративный спорт: групповые тренировки, велбиинг-приложение; спецпредложения от партнёров и скидки на сервисы Авито: бронирование жилья, услуги продвижения, ипотечное страхование; компенсация питания.