Данные и ML вакансии - удалённо

Location: Armenia; Spain; Serbia; Poland; Kyiv City; Kyiv; Odesa; North Macedonia Workplace: remote About Provectus Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.   Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.   Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX, Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for . Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire:   Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant  HR Interview. Soft skills and expectations HM interview. Tech questions; a live engine

Задачи: — анализ банковских и крипто-транзакций для выявления мошенничества и AML-сценариев — разработка и улучшение ML-моделей для fraud detection — graph analysis / Graph ML (GNN, node embeddings, link prediction) — вывод моделей в production Требования: — опыт работы с transactional fraud / AML от 5 лет — strong Python + ML stack (PyTorch / TensorFlow) — опыт с Graph ML / Neo4j / NetworkX / GNN — production ML и ETL pipelines Будет плюсом: — MLOps — ClickHouse / Elasticsearch / Cassandra — опыт с real-time systems и асинхронным Python Условия: — релокация (Узбекистан / Дубай / ЕС) или B2B outside РФ/РБ/Украины — зарплата в валюте — relocation package — международная русскоговорящая команда — сложные ML/AI задачи и сильная technical culture

Требования: - отличное владение русским языком - внимательность, аналитичность - способность работать по инструкции Обязанности: - проверять соответствие описания видео - вносить корректировки и уточнения - следовать инструкциям и метрикам качества Условия: - оплата от 30 000 рублей - гибкий график: 5/2, 6/1, 7/0 - работать можно в любое время - норма — от 6 часов в день - компания компенсирует налоги - удалённая работа - возможность карьерного роста

Location: New York; San Francisco; Canada; United States; Toronto; Montreal Workplace: Remote 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! Why this role? The Data Infrastructure team at Cohere is responsible for the storage and data movement layer underlying every model training run. We're building the unified storage layer that feeds our training workloads. It needs to serve petabytes of training data and model checkpoints fast enough to keep thousands of GPUs busy across several training clusters. In this role, you’d have an opportunity to build this system from the ground up. You’d be a key contributor, working on a problem few teams have had to solve at this scale. In this role, you will: - Design, build, and operate the distributed storage system that feeds model training and evaluation. - Run this system multiple on Kubernetes clusters at petabyte scale. - Work with researchers and training-infra teams on how jobs actually read and write data, and turn that into throughput, latency, and durability requirements - Work through the networking, I/O, and consistency problems of moving large datasets and checkpoints across regions and backends, with GPU idle time and time-to-insight as the measures of success You may be a good fit if you have: - Strong storage fundamentals, including replication, consistency, caching, and data lifecycle management. - Strong coding ability. We work in Python and Go; experience in either is enough, but you should be willing to pick up the other - Experience running stateful systems on Kubernetes, including Persistent Volumes, CSI drivers, and StatefulSets. - Hands-on experience with cloud object storage such as S3 as well as POSIX-style filesystems. It’s a bonus if you have: - Experience with parallel or HPC filesystems such as Weka, VAST, or Lustre. - Familiarity with the data-loading and checkpointing patterns used in large-scale model training. - An interest in how large models are trained and evaluated, including the trajectory and eval data those runs generate, and a desire to understand the workloads the platform is serving. 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: Canada; Europe; United States; United Kingdom Workplace: Remote 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! Why this role? Ship state of the art models to production. Design and implement novel research ideas. Build elegant training/deployment pipelines. Join us at a pivotal moment, shape what we build and wear multiple hats as an intern! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term. As a Machine Learning Intern, you will: - Design, train and improve upon cutting-edge models. - Help us develop new techniques to train and serve models safer, better, and faster. - Train extremely large-scale models on massive datasets. - Explore continual and active learning strategies for streaming data. - Learn from experienced senior machine learning technical staff. - Work closely with product teams to develop solutions. You may be a good fit if you have: - Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR. - Experience using large-scale distributed training strategies. - Familiarity with autoregressive sequence models, such as Transformers. - Strong communication and problem-solving skills. - A demonstrated passion for applied NLP models and products. - Bonus: experience writing kernels for GPUs using CUDA. - Bonus: experience training on TPUs. - Bonus: papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP). 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.

О КОМПАНИИ «Арт-Финтех» — международный поставщик банковского ПО с 20-летней историей. Мы разрабатываем инновационные решения для финансового сектора. Сейчас мы ищем специалиста для развития виртуальных ассистентов и автоматизации клиентского сервиса первой линии. ОСНОВНЫЕ ЗАДАЧИ — Проектирование и внедрение ветвящихся сценариев для чат-ботов и голосовых ассистентов. — Создание блок-схем и UML-диаграмм диалоговых моделей. — Написание скриптов на JavaScript для обработки данных внутри диалога и интеграционных сценариев. — Работа с NLU-классификаторами: сбор, нормализация и предобработка обучающих выборок. — Оптимизация сценариев на основе метрик CSI/VOC/NPS и проведение A/B-тестов. — Поиск и устранение багов в текущих сценариях обслуживания. — Генерация гипотез по улучшению качества ответов ИИ-ассистентов. ТРЕБОВАНИЯ К КАНДИДАТУ — Гражданство и нахождение на территории РФ. — Высшее техническое или лингвистическое образование. — Опыт разработки чат-ботов или голосовых помощников от 1 года. — Базовое владение JavaScript или Python (опыт работы с API и интеграциями). — Опыт работы с No-Code/Low-Code платформами и понимание принципов работы NLU (intent, entity, context). — Практические навыки проектирования диалогов для автоматизации поддержки. — Системное мышление и понимание продуктовых метрик клиентского сервиса. УСЛОВИЯ — Полностью удаленный формат работы. — Стабильность в группе компаний с многолетней историей на рынке. — Работа над сложными интеграционными проектами в сфере FinTech. — Возможность применения современных LLM и инструментов ИИ.

Location: Japan Workplace: remote Contract type: Freelance Language: Japanese (Japan) Estimated volume: 8 - 10 hours Start date: The project runs on a weekly basis.    We are looking for qualified raters to support a project focused on evaluating personalized search and location recommendations. This role involves rating the relevance and usefulness of suggested places based on personalized results and defined project guidelines.   𝗜𝗳 𝘆𝗼𝘂’𝗿𝗲 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝘄𝗵𝗼: ✅Notices when recommendations actually make sense 🧠Thinks critically about usefulness, intent, and context 🖥️Cares about accuracy in digital experiences   This project is built for you.   What you will do: Review search queries with results personalized based on your activity history Evaluate suggested places (e.g., restaurants or locations) related to places you’ve previously visited Rate whether the suggested places are relevant and useful Follow project guidelines and complete tasks accurately Requirements: To be located and have the right to work in Japan. An existing, actively used Gmail account with prior usage history on Google Maps. Participation is limited to maximum three project rounds. Please note that the task request will be dynamic and we will be providing you with a heads-up as soon as possible once there is a project round available for you. Please note: This project requires opt-in, consent-based access to limited elements of your activity history. A consent form will be provided for you to review and sign before participation. Please note that the consent form and its terms may be subject to change as project requirements evolve. A desktop or laptop computer is required to complete the application and onboarding process. Mobile devices are not supported.

Location: Colombia; Brazil; Argentina Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. What you will do - Deliver end-to-end data science projects using classical machine learning (e.g., regression, classification, time series forecasting) and deep learning approaches — from data exploration and modeling to deployment and performance tracking. - Collaborate closely with business stakeholders to identify opportunities and translate them into measurable data-driven solutions. - Present complex analytical findings in a clear, actionable way to both technical and non-technical audiences. - Contribute to analytical planning and ensure alignment with overall business objectives. - Support presales activities by preparing data/ML solution concepts, participating in client meetings, and estimating project scope and potential value. - Help shape the Data Science practice by contributing to its strategic development and supporting recruitment initiatives. What you bring - Proven experience as a Data Scientist delivering end-to-end projects — from exploratory data analysis to model deployment, performance evaluation, and experimentation (e.g., A/B testing). - Strong expertise in working with tabular and time-series data, including EDA, feature engineering, predictive modeling, and model evaluation. - Proficiency in Python and common data-science libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch). - Experience leading or mentoring analytics teams and coordinating with business stakeholders. - Excellent communication skills, able to translate between technical and business perspectives effectively. - Solid understanding of business processes and data structures. - Confidence in client-facing settings: gathering requirements, shaping analytical roadmaps, and delivering measurable business value. - Fluency in English for meetings with international clients. Nice to have - Hands-on experience with deep learning, computer vision, or generative AI projects. - Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tools. - Experience with data visualization or BI tools for communicating insights. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Canada; San Francisco; Europe; London; United States; United Kingdom; Toronto; Montreal Workplace: Remote 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! Why this role? To have the opportunity to collaborate with Cohere researchers and tools on designing and implementing novel research ideas and shipping state-of-the-art models to production. We have openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, to name a few; and we are open to receiving intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup.  Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months. As a Cohere Research Intern, you will: - Conduct cutting-edge machine learning research, building and training large language models.  - Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc. - Disseminate your research results through the production of publications, datasets, and code. - Contribute to research initiatives that have practical applications in Cohere’s product development.  You may be a good fit if you: - Are currently pursuing, or in the process of obtaining, a PhD in Machine Learning, NLP, Artificial Intelligence, or a related discipline. We will also consider exceptional non-PhD candidates. - Are eligible for work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship period.  - Have experience using large-scale distributed training strategies, data annotation and evaluation pipelines, or implementing state of the art ML models. - Are familiar with autoregressive sequence models, such as Transformers. - Have strong communication and problem-solving skills with the ability to convey complex research findings clearly and succinctly.  - Have knowledge, or are knowledgeable, of programming languages such as Python, C, C++, Lua, or related languages. - Have knowledge of related ML frameworks such as JAX, Pytorch and Tensorflow. - Have previous experience in building systems based on machine learning and deep learning techniques.  - Demonstrate passion for applied NLP models and products. Preferred Qualifications: - Demonstrated expertise through publications in top tier venues in fields such as machine learning, NLP, artificial intelligence, computer vision, optimization, computer science, statistics, applied mathematics, or data science.  - Proven ability to tackle analytical problems using quantitative methodologies.  - Proficiency in handling and analysing complex, high-dimensional data from various sources. - Experience in applying theoretical and empirical research to real-world problem-solving. 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: Canada; Calgary; Vancouver; Toronto; Montreal Workplace: Remote 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! Why this role? This role will focus on breaking down engineering tasks such as reporting, component search and handling of material billing/information into individual steps that can be tackled through tool use. Your breakdown will teach the Cohere model the logic needed to complete each task. Please Note: This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 30 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. As a Data Annotation Specialist, you will: - Evaluate the model's ability to respond to engineering procedures and workflows - Task models to complete engineering tasks along with verified information to evaluate the accuracy of the model's responses - Label, proofread, and improve machine-written and human-written engineering-related outputs. - Follow our style guide, and make recommendations on unique situations that fall outside of its scope. You may be a good fit if you have: - 3+ years of industry experience working in engineering fields (civil, mechanical, electrical, chemical) - Technician/engineering specialist training and experience preferredAn education background in engineering (Bachelors, Masters or similar) - Experience on medium-large scale engineering projects involving designing, prototyping and manufacturing components and/or experience in post-graduate research lab - Experience with CAD software, material billing and product lifecycle management (PCMs) can be a plus The Candidate Journey: - Initial Screening: Our Talent Team will review your application. - First Assessment: If selected to move forward, you’ll receive a multiple-choice assessment by email. - Second Assessment: Candidates who achieve a passing score will be contacted by a member of our team to complete a more comprehensive assessment focused on their area of expertise. - Video Screen: If selected to move forward, you’ll have a short video call with a member of our Operations Team. - Final: Selected candidates will receive an Independent Contractor Agreement. As an independent contractor, you maintain control over how you complete your work and may work with multiple clients simultaneously, although we ask you to declare if any of these are with a direct competitor of Cohere and maintain IP confidentiality of the Cohere project. Independent contractors are not eligible for health benefits or other benefits provided to employees. Compensation for services is provided to contractors by contractors invoicing for services provided pursuant to the terms of our agreement with the contractor. It is important to understand that as an independent contractor, continuous work is not guaranteed. The client-contractor relationship is fundamentally project-based, meaning engagements may be temporary, periodic, or intermittent based on our organizational needs and project availability. As an independent contractor, you should anticipate fluctuations in workflow and therefore compensation for services when Cohere does not require as many hours of services in a week. Prospective candidates, please be advised: this role involves working with human generated and model generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material. If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and 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.

Location: Remote - US About the Job: As a Staff Engineer on LaunchDarkly's Experimentation team, you'll build the platform that helps engineering teams make data-driven decisions with confidence. Our Experimentation product enables customers to run A/B tests, measure the impact of feature changes, and optimize experiences — integrated with a feature management platform that processes trillions of evaluations daily. This role sits at the intersection of data science and platform engineering. You'll design the statistical engine, warehouse-native analysis pipelines, and adaptive experimentation systems (including contextual bandits) that power our customers' most important decisions. We want someone who brings genuine depth in applied statistics and ML — as fluent in statistical validity as in system architecture. You'll also architect warehouse-agnostic features that run analysis directly inside customers' data warehouses (Snowflake, Databricks, Redshift, BigQuery) — modular computation layers that abstract across warehouse environments while maintaining statistical correctness. Deep technical experience, a scientific mindset, and the ability to influence product and technical direction are critical. You'll lead by example: setting the bar for rigor, mentoring teammates, and owning systems end to end, including on-call. Responsibilities: Build the experimentation statistical engine — hypothesis testing, sequential analysis, variance reduction ( CUPED , Winsorization), power analysis. Ensure statistical correctness across all experiment types. Design warehouse-native experimentation that runs analysis inside customer warehouses (Snowflake, Databricks, Redshift, BigQuery). Build modular, warehouse-agnostic abstractions for rapid new backend support. Lead adaptive experimentation — contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. Drive the platform roadmap with product, design, and data science. Shape what we build, not just how. Collaborate cross-functionally with Warehouse Integrations, SDK, Platform, and Data Science teams. Mentor engineers and raise the team's bar for statistical rigor and system design. Own operational excellence — monitoring, observability, incident response, on-call. Robust telemetry and alerting. Qualifications: 10+ years building large-scale experimentation platforms, statistical analysis systems, or data-intensive backend services. Applied-statistics knowledge: hypothesis testing, sequential analysis, variance reduction ( CUPED ), power analysis, experiment design. Comfortable with frequentist vs. Bayesian trade-offs. Experience with adaptive experimentation ML — contextual bandits, Thompson sampling, Bayesian optimization, or RL -based allocation. Track record designing warehouse-agnostic systems across Snowflake, Databricks, Redshift, BigQuery, or similar. Expertise in Go, Python, or similar for backend services and statistical computation. Experience with event-driven architectures, data pipelines, and large-scale data processing. Cloud environments (AWS, GCP) with infrastructure-as-code. Technical leadership: setting direction, breaking down complex problems, influencing across teams. Ability to translate statistical concepts for product and engineering audiences. Pay: Target pay ranges based on Geographic Zones* for Level 5: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $214,800 - $295,350* Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $193,400 - $265,870** Zone 3: All other US locations - $182,600 - $251,0202** 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: Thailand Workplace: remote Transcriber – Audio & Annotation Projects We are looking to onboard Transcribers to support a range of upcoming audio processing projects. This role focuses on converting audio into accurate written text, with opportunities to contribute to annotation tasks depending on project needs. Key Responsibilities Transcribe audio files into clear, well-structured text Work with a variety of audio types, including: Single-speaker recordings Podcasts Multi-speaker conversations Identify speakers where applicable Ensure high accuracy and attention to detail Follow project-specific transcription and formatting guidelines Task Types 1. Transcription Tasks Convert audio content into written text Maintain consistency in formatting and structure Ensure clarity and completeness of transcriptions 2. Annotation Tasks (Project-dependent) Label or tag segments of text or audio Categorize content based on provided guidelines Support data quality and training datasets Requirements Very high proficiency in Arabic Good written English Strong listening and comprehension skills Ability to follow detailed instructions and guidelines Previous transcription or annotation experience is a plus, but not required Availability Minimum 4 hours of availability required during scheduled transcription shifts Project Details Flexible working hours – complete tasks at your own pace within project timelines Tasks are completed via a secure online platform Full guidelines and instructions are provided for each task Ongoing support is available to ensure quality and consistency Multiple similar projects are planned throughout 2026, offering potential for continued work

Location: Germany Workplace: remote Transcriber – Audio & Annotation Projects We are looking to onboard Transcribers to support a range of upcoming audio processing projects. This role focuses on converting audio into accurate written text, with opportunities to contribute to annotation tasks depending on project needs. Key Responsibilities Transcribe audio files into clear, well-structured text Work with a variety of audio types, including: Single-speaker recordings Podcasts Multi-speaker conversations Identify speakers where applicable Ensure high accuracy and attention to detail Follow project-specific transcription and formatting guidelines Task Types 1. Transcription Tasks Convert audio content into written text Maintain consistency in formatting and structure Ensure clarity and completeness of transcriptions 2. Annotation Tasks (Project-dependent) Label or tag segments of text or audio Categorize content based on provided guidelines Support data quality and training datasets Requirements Very high proficiency in Arabic Good written English Strong listening and comprehension skills Ability to follow detailed instructions and guidelines Previous transcription or annotation experience is a plus, but not required Availability Minimum 4 hours of availability required during scheduled transcription shifts Project Details Flexible working hours – complete tasks at your own pace within project timelines Tasks are completed via a secure online platform Full guidelines and instructions are provided for each task Ongoing support is available to ensure quality and consistency Multiple similar projects are planned throughout 2026, offering potential for continued work

Location: United States; Canada (BC & ON only) Workplace: Remote Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. Without ever sacrificing craft or quality helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We’re looking for a Senior Staff Machine Learning Scientist to help us solve challenging problems to address emerging customer needs and behaviors. The ideal candidate can move fast but with high quality, and views the early stages of product development as a creative canvas and opportunity for high impact. ABOUT THE ROLE: - Location: Remote-first (United States; BC & ON, Canada) - Full-time - Permanent - Exempt - Our cash compensation amount for this role ranges depending on the cost of labor of the geographic area. The ranges shared below may change if you are hired in another geographic location.  - United States  (all figures cited below in USD and pertain to workers in the United States) - Zone A: 232,000 - 290,000 - Zone B: 217,600 - 272,000 - Zone C: 204,800 - 256,000 - Canada  (All figures cited below in CAD and pertain to workers in ON & BC, Canada) - 253,000 - 316,000 Please visit our Careers page https://webflow.com/careers#pay-zones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. - Application Information: - Application deadline: applications accepted on an ongoing basis until position is closed and filled - This posting is for a new position - Reporting to the Director, Engineering  As a Senior Staff Machine Learning Scientist, you’ll:  - Lead and drive ambitious research initiatives that advance the state of the art in computer vision, multimodal understanding, and visual generation. - Develop novel models, algorithms, and training methodologies for challenging vision problems such as image understanding, video understanding, visual search, scene representation, segmentation, detection, generation, and multimodal reasoning. - Translate cutting-edge research into practical model improvements that can shape product direction and unlock new user experiences. - Design, implement, train, and optimize large-scale vision and multimodal foundation models across diverse datasets and tasks. - Partner closely with applied scientists, ML engineers, and product teams to move research from exploration to production-ready systems. - Set technical direction for high-impact research areas, identifying promising bets and influencing longer-term strategy for vision and multimodal AI. - Mentor other scientists and engineers, raise the quality bar for research, and help build a strong scientific culture across the team. - Stay at the forefront of research in computer vision, multimodal learning, generative modeling, and foundation models, and apply emerging techniques to real-world problems. ABOUT YOU: Requirements: - BA/BS degree or equivalent experience You’ll thrive as a Senior Staff Machine Learning Scientist if you: - Deep theoretical and practical expertise in computer vision, with strong foundations in areas such as representation learning, visual recognition, image or video generation, multimodal learning, and large-scale model training. - Advanced degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field; PhD strongly preferred. - 8+ years of relevant industry and/or research experience, or equivalent impact, including a track record of driving major research initiatives in computer vision or multimodal machine learning. - Strong experience with state-of-the-art vision and multimodal model architectures, including transformers, diffusion models, contrastive learning approaches, and foundation models. - Proven ability to formulate research problems clearly, design rigorous experiments, and translate findings into meaningful model or product advances. - Strong coding and prototyping skills in Python, with the ability to write clean, scalable, and well-documented research code. - Proficiency in modern deep learning frameworks such as PyTorch and TensorFlow. - Demonstrated technical leadership, including mentoring scientists or engineers and influencing research direction across a team or organization. - Strong communication skills, with the ability to present complex research clearly to both technical and cross-functional audiences. - Stay curious and open to growth — demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact.   OUR CORE BEHAVIORS - Build lasting customer trust. We build trust by taking action that puts customer trust first. - Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act. - Reinvent ourselves. We don't just improve what exists, we imagine what's possible. - Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.   BENEFITS - Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company. - Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums. - Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions. - Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired. - Wellness for the whole you. Access to mental health resources, therapy and coaching. - Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally. - Monthly stipends that flex with your life. Localized support for work and wellness expenses — from Wi-Fi to workouts. - Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.   Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.   BE YOU, WITH US At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.   STAY CONNECTED Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.   PLEASE NOTE: We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered. To join Webflow, you'll need a valid right to work authorization depending on the country of employment. If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes. Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.

Задачи: — Участие в разработке и деплое ML/LLM решений. — Применение Prompt Engineering и методов Fine-tuning/PEFT. — Построение RAG пайплайнов и работа с векторными базами данных. — Оптимизация производительности LLM и оценка их качества. — Разработка с использованием мультимодальных моделей. Требования: — Уверенное владение Python. — Опыт деплоя ML/LLM решений с использованием Docker, Kubernetes, облачных платформ AWS, GCP, Azure. — Опыт работы с Prompt Engineering (few-shot, chain-of-thought, ReAct). — Знание Fine-tuning / PEFT (LoRA, QLoRA, adapters). — Опыт построения RAG пайплайнов (chunking → embedding → retrieval → генерация). — Умение работать с векторными базами данных (Qdrant, Pinecone, Milvus, FAISS). — Опыт RLHF или работы с синтетическими данными (предпочтения, генерация и фильтрация). — Знание фреймворков LangChain, LlamaIndex, Hugging Face. — Опыт оценки LLM (BLEU, ROUGE, MMLU, кастомные эвалы). — Опыт оптимизации инференса (vLLM, TensorRT, ONNX). — Опыт работы с мультимодальными моделями (LLaVA, GPT-4V, Qwen-VL). — Грейд Middle/Middle+. Условия: — Полная занятость. — Удалённый формат работы. — Интересные проекты в области ИИ.

Location: United States; North Carolina; Illinois; California; Arizona; Florida; Frankfurt; Georgia; Idaho; Indiana; Iowa; Kansas; Louisiana; Maine; Massachusetts Workplace: remote Transcriber – Audio & Annotation Projects  Location - all of the US We are looking to onboard Transcribers to support a range of upcoming audio processing projects. This role focuses on converting audio into accurate written text, with opportunities to contribute to annotation tasks depending on project needs. Key Responsibilities Transcribe audio files into clear, well-structured text Work with a variety of audio types, including: Single-speaker recordings Podcasts Multi-speaker conversations Identify speakers where applicable Ensure high accuracy and attention to detail Follow project-specific transcription and formatting guidelines Task Types 1. Transcription Tasks Convert audio content into written text Maintain consistency in formatting and structure Ensure clarity and completeness of transcriptions 2. Annotation Tasks (Project-dependent) Label or tag segments of text or audio Categorize content based on provided guidelines Support data quality and training datasets Requirements Very high proficiency in American English Good written English Strong listening and comprehension skills Ability to follow detailed instructions and guidelines Previous transcription or annotation experience is a plus, but not required Availability Minimum 4 hours of availability required during scheduled transcription shifts Project Details Flexible working hours – complete tasks at your own pace within project timelines Tasks are completed via a secure online platform Full guidelines and instructions are provided for each task Ongoing support is available to ensure quality and consistency Multiple similar projects are planned throughout 2026, offering potential for continued work

Location: Finland Workplace: remote Transcriber – Audio & Annotation Projects We are looking to onboard Transcribers to support a range of upcoming audio processing projects. This role focuses on converting audio into accurate written text, with opportunities to contribute to annotation tasks depending on project needs. Key Responsibilities Transcribe audio files into clear, well-structured text Work with a variety of audio types, including: Single-speaker recordings Podcasts Multi-speaker conversations Identify speakers where applicable Ensure high accuracy and attention to detail Follow project-specific transcription and formatting guidelines Task Types 1. Transcription Tasks Convert audio content into written text Maintain consistency in formatting and structure Ensure clarity and completeness of transcriptions 2. Annotation Tasks (Project-dependent) Label or tag segments of text or audio Categorize content based on provided guidelines Support data quality and training datasets Requirements Very high proficiency in Finnish Good written English Strong listening and comprehension skills Ability to follow detailed instructions and guidelines Previous transcription or annotation experience is a plus, but not required Availability Minimum 4 hours of availability required during scheduled transcription shifts Project Details Flexible working hours – complete tasks at your own pace within project timelines Tasks are completed via a secure online platform Full guidelines and instructions are provided for each task Ongoing support is available to ensure quality and consistency Multiple similar projects are planned throughout 2026, offering potential for continued work

Location: Portugal Workplace: remote Transcriber – Audio & Annotation Projects We are looking to onboard Transcribers to support a range of upcoming audio processing projects. This role focuses on converting audio into accurate written text, with opportunities to contribute to annotation tasks depending on project needs. Key Responsibilities Transcribe audio files into clear, well-structured text Work with a variety of audio types, including: Single-speaker recordings Podcasts Multi-speaker conversations Identify speakers where applicable Ensure high accuracy and attention to detail Follow project-specific transcription and formatting guidelines Task Types 1. Transcription Tasks Convert audio content into written text Maintain consistency in formatting and structure Ensure clarity and completeness of transcriptions 2. Annotation Tasks (Project-dependent) Label or tag segments of text or audio Categorize content based on provided guidelines Support data quality and training datasets Requirements Very high proficiency in Portuguese Good written English Strong listening and comprehension skills Ability to follow detailed instructions and guidelines Previous transcription or annotation experience is a plus, but not required Availability Minimum 4 hours of availability required during scheduled transcription shifts Project Details Flexible working hours – complete tasks at your own pace within project timelines Tasks are completed via a secure online platform Full guidelines and instructions are provided for each task Ongoing support is available to ensure quality and consistency Multiple similar projects are planned throughout 2026, offering potential for continued work