Данные и ML вакансии - гибрид

Задачи: — Проектировать и развивать архитектуру корпоративного Data Warehouse — Строить ELT-пайплайны с использованием Python — Поддерживать Master Data Management (MDM) и качество данных — Разрабатывать дашборды и отчёты в Power BI — Управлять рабочим пространством Power BI и доступом — Взаимодействовать с командами аналитики, продукта и технологий Требования: — Опыт 3+ года в BI, Data Analyst или BI Developer — Уверенное владение SQL (PostgreSQL, BigQuery) — Опыт проектирования DWH и моделирования данных — Знание Python (pandas, SQLAlchemy, Airflow или аналогичные инструменты) — Опыт работы с Power BI (отчёты, дашборды, администрирование) — Глубокое понимание BI-систем и рабочих процессов Плюсы: — Опыт в e-commerce, игровой индустрии или цифровых продуктах — Знание Power Query, Power Pivot — Опыт с Looker Studio, QlikView — Опыт автоматизации отчётности Условия: — Работа в быстрорастущей fintech-компании — Высокая степень ответственности и реальное влияние на продукт — Международная команда и современный офис — Зарплата 5000-8000 евро net — Поддержка релокации (перелёт, проживание, виза) — Гибридный формат работы в Лимассоле

Location: Metro Manila; Armenia; Kazakhstan; Georgia Workplace: Hybrid Salmon is a technology-driven financial company building a banking and lending platform across Southeast Asia, starting in the Philippines. We combine global fintech expertise with deep local market knowledge to make financial services simple, accessible, and useful for millions of people across the region. 7M+ app downloads. 2M+ monthly active users. 7,000+ partner stores. US$310M+ raised from leading global investors. Manila-based, globally distributed, and hybrid-first — our team spans 45+ countries. If you want to solve complex problems at scale and impact how millions of people access and manage money, come build with us. Southeast Asia's fintech moment starts here. About the role: You'll own ML models across credit scoring, collection, and antifraud, turning data into systems that directly shape how Salmon lends and collects at scale. What you'll do: - You'll build and ship ML models across credit scoring, collection, antifraud, and sales — high-stakes, high-visibility work from day one. - You'll work directly with Collection, Product, and other cross-functional teams to find where a better model moves the business. - You'll take models from idea to production, then keep monitoring and improving them as real data comes in. What you'll own: - Own the end-to-end lifecycle of ML models — EDA, feature generation, hypothesis testing, production deployment, and monitoring. - Partner with Collection and Product to identify where a new or improved model would have the most leverage. - Evaluate model performance against business impact, and iterate based on what you find. - Explore and integrate new data sources, internal and external, to surface additional predictive signals. - Build models that are scalable, observable, and maintainable in production systems. What makes you a strong fit: - 2+ years of experience as a Machine Learning Engineer or Data Scientist, ideally in fintech or fast-paced product environments. - Solid foundation in classical ML techniques, fluent in Pandas, Scikit-learn, NumPy, SciPy, Matplotlib, Seaborn, Statsmodels, and gradient boosting libraries (XGBoost, LightGBM, CatBoost). - Strong Python and SQL, with experience using version control. - A strong sense of ownership and accountability. - Experience with graph neural networks or transformer models would be a plus. What we offer: Ownership and flexibility - Hybrid-first work environment - Company-provided tools and equipment - Office in Bonifacio Global City, Manila — a modern, walkable district at the centre of the Philippines' growing tech scene Health and time off - Medical insurance support for you and your family through co-funding or reimbursement, depending on your location and subject to policy limits - Access to an internal mental health support specialist - 22 vacation days, Philippine public holidays, and 15 sick days - 105 days of paid maternity leave and up to 14 days of paid paternity leave for employees relocating to Manila Relocation and family support - Relocation support for you, your family — including flights, two weeks of accommodation, visas, paperwork, and logistics - Reimbursement of eligible pet relocation expenses - USD 2,500 per year for flights home - Baby and family stipends for employees relocating to Manila: USD 1,000 per month for each child under two and USD 500 per month for each child aged two to 18 Growth and team experience - Opportunities to learn and share your expertise through internal expert meetups, external conferences, speaking opportunities, and industry publications - Company-sponsored trips to Manila to meet and work with your team in person - Regular team offsites, sports activities, and team events - High-performing teams can earn a dedicated beach house week in Southeast Asia

О ПРОЕКТЕ Команда занимается развитием внутренней AI/ML-платформы, AutoML, разработкой LLM/NLP-решений, мониторингом качества моделей на крупном финтех-проекте. ПРЕДСТОЯЩИЕ ЗАДАЧИ • Разработка и развитие ML/LLM-сценариев для production; • Работа с AutoML, NLP и RAG-пайплайнами; • Оптимизация качества и стабильности ML-решений; • Интеграция с MLOps/DE-инфраструктурой; • Быстрое прототипирование и проектирование AI-решений. ОЖИДАНИЯ ОТ КАНДИДАТА • 3+ лет опыта в DS/ML; • Хороший Python и уверенный ML-стек (Sklearn, CatBoost/LightGBM/XGBoost, Pandas, NumPy), опыт с табличными данными; • Опыт с LLM/NLP (для проекта в данном направлении); • Опыт работы с Spark/Hadoop/Hive; • Понимание production ML-процессов. БУДЕТ ПЛЮСОМ • PyTorch / DL; • Open-source contribution; • Full-stack опыт. УСЛОВИЯ РАБОТЫ • Оформление по ТК или ИП в аккредитованную ИТ-компанию; • Сильная инженерная команда и обмен экспертизой; • Гибридный или удаленный формат работы (РФ!); • ДМС со стоматологией с 1-го дня; • Предоставление техники (на выбор, по запросу).

О ПРОЕКТЕ VADAROD расширяет команду! Мы ищем эксперта, который усилит нашу работу с данными и поможет вывести КХД на новый уровень. Если ты мастерски владеешь DBT и знаешь, как строить отказоустойчивые модели данных — нам по пути! ТВОИ КЛЮЧЕВЫЕ ВЫЗОВЫ — Transformation: Создание эффективного слоя трансформации сырых данных. — Modeling: Проектирование концептуальных, логических и физических моделей данных для КХД. — Architecture: Прямое участие в разработке архитектуры решений. — Quality: Участие в Code Review и внедрение лучших практик разработки. МЫ ЖДЕМ ОТ ТЕБЯ — Tooling: Уверенный опыт работы с DBT, CDC или Databricks. — Coding: Знание Python и умение писать/отлаживать действительно сложные SQL-запросы. — Design: Практические навыки проектирования баз данных и хранилищ (DWH). БУДЕТ ПЛЮСОМ — Опыт в финтех-домене или понимание процессов финансовых организаций. — Работа с Apache Airflow, Debezium или Greenplum.

Задачи: — Улучшать стабильность и качество текущих AutoML алгоритмов, оптимизировать код; — Разрабатывать новые сценарии платформы для аналитиков (поиск аномалий, очистка данных, кластеризация, анализ дрейфа данных/концепта); — Улучшать отчетность и артефакты по полученной модели (отчёт по модели с интерпретацией LLM, графики, таблицы); — Обновлять документацию и технические инструкции по сценариям платформы; — Взаимодействовать по внедрению новых сценариев и фич платформы с MLOps командой; — Проводить анализ потребностей аналитиков, формализовать их в сценарии; — Поддерживать пользователей (аналитиков); — Отвечать за релизный цикл библиотеки; — Проводить ревью PR от других DS. Требования: — Опыт в Data Science от 3 до 5 лет (важна насмотренность к кейсам и разным моделям, опыт промышленной разработки); — Уверенное владение ML- и DL-стеком Python: PyTorch, LightGBM / XGBoost / CatBoost, Scikit-Learn, Pandas, NumPy; — Умение работать с инструментами: Spark, Hadoop, Hive, MLflow, Airflow / Argo Workflows; — Обязателен опыт в табличных данных и классическом ML (градиентный бустинг, логистическая регрессия, кластеризация); — Будет большим плюсом: Контрибьют в ML-библиотеки; Опыт full-stack разработки; — Не подходят кандидаты с чистой карьерой в CV / NLP / LLM без серьёзного бэкграунда в таблицах. Условия: — Работа в аккредитованной IT компании; — Формат работы: удалённый по РФ (или гибрид — на выбор); — Расширенный ДМС (со стоматологией); — Выдача необходимой для работы техники (ноутбук); — Возможность воспользоваться реферальной программой: «Приведи товарища»; — Участие в Бонусной программе; — Помощь с ипотекой и другими пособиями; — Возможность построить карьеру в рамках ведущих компаний России.

Location: Limassol; Nicosia Workplace: hybrid The Role:  We are looking for an experienced Data Scientist to join our Data Science department. In this role, you will work hands-on on advanced analytics and machine learning projects, leveraging large datasets to build impactful, production-ready solutions.  Ideal for someone who enjoys solving complex problems, building models end-to-end, and driving data-driven decision-making The main responsibilities of the position include: Design, develop, and review machine learning models and advanced analytics solutions Apply statistical analysis and data mining techniques to extract meaningful insights from large datasets Ensure high standards in data preparation, feature engineering, model evaluation, documentation, and code quality Collaborate with cross-functional teams including data engineers, software engineers, product owners, and business stakeholders Present insights, analysis results, and recommendations to both technical and non-technical audiences Ensure adherence to best practices in data quality, model monitoring, version control, and reproducible analytics Contribute to the development of the department’s data science strategy and identify opportunities where data science can deliver business value Main requirements: University degree in Mathematics, Physics, Computer Science, Engineering, Data Science, or a related quantitative field At least 3 years of experience in data science, machine learning, or advanced analytics Strong programming skills in Python and experience with Pandas, NumPy, and similar data analysis libraries Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly Strong knowledge and exposure to Machine Learning Knowledge of Recommendation Systems will be considered a plus Solid understanding of statistics and data mining techniques Experience working with relational and non-relational databases Strong analytical thinking, problem-solving ability, and attention to detail Excellent communication skills and the ability to work collaboratively in a team environment Benefit from: Attractive remuneration package Private health insurance Corporate pension fund Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Bring It to Life – Role-Specific Take-Home Task Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. We are looking for an engineer with strong experience in machine learning and solid foundations in math and computer science to join our growing Post-Training team at Baseten. THE ROLE Custom models are instrumental to the success of Baseten customers. By inference volume, the overwhelming majority of traffic at Baseten is to and from models that have been post-trained in some way, whether that be through reinforcement learning, supervised finetuning, a recent technique from the literature, or an in-house research technique from Baseten. The Post-Training team is responsible for the success of our customers’ post-trained models, and we employ a wide array of techniques to produce models that are more efficient and higher quality than even the biggest closed source models for the customer’s specific needs. Your role as a research engineer is to build the in-house tooling to support all of this. We care about training a wide spectrum of different model architectures with a variety of techniques efficiently and at scale. At times this involves zooming deep into a particular technical topic, but more often it involves working across the stack as a whole - systems-level concepts like Kubernetes, cgroups, storage systems, and networking topologies, as well as PyTorch distributed tensor computation, and GPU kernels. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH - Dense, on-policy or both? https://www.baseten.co/research/dense-on-policy-or-both/ - Repeated kv cache for long-running agents https://www.baseten.co/research/repeated-kv-cache-for-long-running-agents/ - Distillation without the dark – replicating black-box on-policy distillation on Baseten https://www.baseten.co/research/distillation-without-the-dark/ We don’t have a rigid set of skills, but here’s some of what we’re looking for: - A deep understanding of modern ML techniques and tools for training transformers - Advanced experience in a tensor/array computation library like PyTorch, TensorFlow, Jax, or similar - A detailed understanding of transformer training parallelism strategies like data parallelism, sharded data parallelism, tensor parallelism, pipeline parallelism, context parallelism - The experience and knowledge to profile and improve the performance of a distributed GPU program in PyTorch or a similar library - The ability to perform roofline analysis on a transformer training setup - A willingness to dive into messy problems, work with researchers, derive specifications by asking important questions, and execute - Familiarity with HPC and distributed computing platforms like Slurm, Ray, Kubernetes, and Dask - Familiarity with cluster networking technology like Infiniband, RoCE, GPUDirect - Solid fundamentals in operating systems concepts like processes, files, kernel drivers, containerization, and networking protocols - A sense of creativity and willingness to ask difficult questions about our approach, assumptions, and tooling choices BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: London; New York; Edinburgh; Paris; Toronto; Montreal 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 Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross-functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams. This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management. It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole. Please Note: The existing team work in offices in London, Edinburgh, Paris, Toronto, and New York, but we also embrace being remote-friendly! For this role you need to have ~50% working day overlap with UK/EU timezone (e.g. US East is fine) but there are otherwise no restrictions on where you can be located for this role. Key responsibilities: - Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance. - Extremely strong software engineering skills. - Strong expertise in designing and conducting data collection tasks, including working with human annotators. - Experience analyzing datasets with respect to their quality, biases, and suitability for training ML models. - Hands-on experience training large language models (LLMs) on distributed training infrastructures. - Familiarity with evaluating and improving the generalizability and robustness of ML systems. - Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX). - Excellent communication skills to collaborate effectively with cross-functional teams and present findings. - One or more papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP). Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. 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: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Engineer to build and scale Baseten’s internal data platform. This role sits at the intersection of data engineering, analytics, and data science, transforming raw product and business data into reliable datasets that power decision-making. You’ll design the data models, pipelines, and analytics infrastructure that enable teams across Product, Engineering, Finance, Marketing, and Sales to understand usage and performance. This includes working with AI inference, infrastructure, and observability data to generate insights about the product, business operations and platform economics. You’ll partner closely with stakeholders to build robust, scalable pipelines, define company-wide metrics that inform strategy and planning. RESPONSIBILITIES - Design and maintain core data models and semantic layers - Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks - Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools - Define and maintain company-wide metrics across product usage, performance, and customer lifecycle - Enable self-service analytics through agents and tools, with well-structured semantic layers and context - Ensure data reliability and quality through testing, documentation, and governance PREFERRED QUALIFICATIONS - Understanding of inference metrics such as latency, throughput, token usage, and model performance - Experience supporting B2B SaaS and/or consumption-based platforms - Application of forecasting and predictive modeling (e.g., ARIMA, Prophet) to business processes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This role sits at the frontier of our research agenda. You will pursue open problems at the intersection of post-training methodology and performant inference, and then collaborate with research engineering to translate findings into production systems. A meaningful portion of your time will be dedicated to research that deepens our understanding of how models learn, alignment, and architectural efficiency — questions that may not have immediate product application. The remainder will be directed toward research that solves concrete problems for Baseten's platform and customers, who are the fastest growing AI companies in the world like Cursor, Lovable, and Notion. We are looking for someone with sharp research taste and genuine creative instinct for problem selection. Someone who can identify questions that matter, design clean experiments to answer them, and push the state of the art. The environment here is not theoretical, but rather research that can be validated with eager customers who are serving billions of tokens a second. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH - Towards infinite context windows: neural KV cache compaction https://www.baseten.co/research/towards-infinite-context-windows-neural-kv-cache-compaction/ - Dense, on-policy or both? https://www.baseten.co/research/dense-on-policy-or-both/ - Repeated kv cache for long-running agents https://www.baseten.co/research/repeated-kv-cache-for-long-running-agents/ - Distillation without the dark – replicating black-box on-policy distillation on Baseten https://www.baseten.co/research/distillation-without-the-dark/ RESPONSIBILITIES - Define and pursue a research agenda spanning both foundational and applied work, with the applied component connected to Baseten's platform and customer needs. - Design and execute rigorous experiments, frequently at meaningful scale (multi-node, trillion parameter models). - Work with customers to translate domain-specific requirements into research problems, where relevant to your agenda. - Publish at top venues (NeurIPS, ICML, ICLR) and establish Baseten's research presence. - Collaborate with model performance and training infrastructure teams to bridge research findings and inference production systems. - Mentor junior researchers and shape the technical direction of the research organization as it grows. PREFERRED QUALIFICATIONS - Master’s or PhD research depth in machine learning, with first-author publications at top venues - Demonstrated ability to move from theory through implementation to empirical results — not exclusively theoretical or exclusively engineering work - Judgment about problem selection, the ability to distinguish research that advances a metric from research that changes how systems are built - Willingness to operate in a startup environment where the majority of research informs product decisions, with timelines measured in months rather than years - Background spanning multiple research areas (e.g., both interpretability and RL, or both systems and training methodology) - Track record of open-source contributions or community building in ML research OUR VIEW ON TALENT Many of the labs that exist today run a credentialist talent model. Concentrate the most already-legible researchers, and assume the concentration compounds. The best researchers in this field are very often not yet legible. Research engineers who have spent years inside a production stack and developed insights no PhD program teaches; PhDs working on the wrong-shaped problem at the right-shaped lab; operators who have been close to real systems long enough to see things credentialed researchers have never had to see. If you don’t have the traditional qualifications and are doing exceptional work, we’d love to chat. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Warsaw; Amsterdam; Barcelona Workplace: hybrid About us: Planner 5D is a global hub for home design, uniting over 100+ million users in 230 territories around our planet (yes, we have 2 users connecting from Antarctica each month!). Our platform simplifies the home renovation process from concept to execution, and this process has never been more straightforward with our cutting-edge software. You don't need to be a professional designer to enhance your home or workspace. We are dedicated to streamlining the design experience, making the customization of dream homes accessible to everyone. Our cross-platform presence spans Web, iOS, Android, Windows, and MacOS, ensuring seamless synchronization for our users.  Planner 5D is more than just software; it's a vibrant community of enthusiastic and product-oriented professionals. From diverse backgrounds, our team collaborates across time zones, fueled by a shared passion to revolutionize the home design market. We are constantly looking for like-minded talent eager to take ownership and drive innovation within our expanding suite of tools. Join us in shaping the future of home design. We are searching for an AI / Machine Learning Researcher to join our AI team and focus on applied research for real-world product challenges. You will work with raw data, explore new approaches, formulate and test hypotheses, and build prototypes and MVP solutions that can later become production features within the Planner 5D platform. You will: Conduct applied research in AI/ML to solve real-world problems related to home design, 2D/3D data, and visual understanding. Work with raw and unstructured data (images, 3D point clouds, text, video) to identify useful signals and formulate research directions. Generate and test hypotheses through experiments, modeling, and data analysis. Design and implement prototypes and MVP solutions, validating ideas before production implementation. Train, evaluate, and iterate on machine learning and deep learning models. Contribute to the development of AI-driven features, including computer vision systems and AI agents. Collaborate with engineers to translate research prototypes into production-ready solutions. Provide algorithm-level support for deployed models, improving and adapting them as new data or requirements emerge. Requirements 4+ years of experience in AI/ML research or applied machine learning. Strong background in mathematics and computer science, including statistics, optimization, linear algebra, and algorithms. Solid understanding of machine learning and deep learning methods. Experience working with real-world datasets, including data exploration, cleaning, feature extraction, and experimental validation. Proficiency in Python and common scientific/ML libraries (NumPy, SciPy, Pandas, etc.). Experience with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with computer vision or multimodal AI (images, video, 3D data such as point clouds and meshes). Ability to independently formulate research hypotheses, design experiments, and evaluate results. Strong analytical thinking and ability to solve complex problems with limited prior solutions. Nice to have Experience with 3D data processing (point clouds, meshes, spatial data). Experience building or experimenting with AI agents or LLM-based systems. Experience training and fine-tuning neural networks. Interest in geometry, graph theory, or computational geometry. What we offer: - Great work environment that balances freedom and responsibility - Our team is made up of friendly and passionate enthusiasts who are eager to help and share their knowledge - We believe in work-life balance, so you'll receive around 30+ days of paid holidays per year - Company computer equipment by request - Education courses for our team members, and we're willing to allocate funds toward your training expenses - English classes on our corporate platform - Offline company events in Lithuania and online team-building - Unlimited free Planner5D subscriptions

Location: San Francisco; New York; Toronto; Montreal 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! WHY THIS ROLE? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: - 5+ years of engineering experience running production infrastructure at a large scale - Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters - Experience with Kubernetes dev and production coding and support - Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving - Experience in designing, deploying, supporting, and troubleshooting in complex Linux-based computing environments - Experience in compute/storage/network resource and cost management - Excellent collaboration and troubleshooting skills to build mission-critical systems, and ensure smooth operations and efficient teamwork - The grit and adaptability to solve complex technical challenges that evolve day to day - Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), especially how they influence latency and throughput of inference. - Strong understanding or working experience with distributed systems. - Experience in Golang, C++ or other languages designed for high-performance scalable servers). 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: Foster City, CA Workplace: Hybrid Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE Replit spreads through companies differently than it does through individuals. One person builds an app, colleagues start using it, a team forms, an admin rolls Replit out more widely, and eventually Sales gets involved. You'll be the data scientist for Replit's enterprise business, covering both the product and the go-to-market motion: how Replit spreads inside organizations, what keeps teams engaged after rollout, which features and signals drive expansion, and how all of that becomes pipeline, revenue, and a reliable forecast. Experimentation is hard here. There are far fewer accounts than users, people within an organization influence each other, and admins control what their teams see. You'll figure out how to learn quickly and rigorously anyway. You'll work with Enterprise Product, Engineering, Sales, Customer Success, RevOps, and Finance, and your work succeeds when it changes a product, GTM, or investment decision. YOU WILL: - Define how we measure the enterprise business end to end: account-level activation, breadth (share of seats active), depth (apps built, deployed, and shared), collaboration, consumption, and net revenue retention - Understand virality inside organizations: how Replit spreads from a first builder to teams through app sharing, invites, and viewers who become builders; quantify within-account network effects and find the levers that accelerate them - Explain post-engagement churn: why seats and accounts that engaged at rollout go dormant, separate seat-level decay from account-level risk, and turn it into account health models that give the product and Customer Success early warning and a clear next action - Identify the product behaviors and features that precede seat expansion and plan upgrades, and use them to build product-qualified account (PQA) models that route bottoms-up usage to Sales at the right moment - Measure adoption and value for enterprise features — admin and governance controls, security, data connectors, collaboration, and deploying to data platforms — and use it to inform what we build next - Design experiments for enterprise: account- and cluster-level randomization, interference within organizations, small samples and heavy-tailed account sizes, stratified and matched-pair designs, staged rollouts and long-running holdouts, synthetic control, and Bayesian or hierarchical models where data is sparse - Measure the incremental impact of GTM programs — pilots, onboarding, enablement, and sales-assist — with the same rigor as product launches - Own enterprise forecasting for pipeline, bookings, consumption, and expansion, and pressure-test the assumptions behind capacity and quota plans - Analyze pricing and packaging: seats vs. consumption, and how contract structure shapes usage - Build a trusted enterprise data layer that joins product telemetry, CRM, and billing data and models the org, workspace, team, and seat hierarchy, so Product, Sales, and leadership can self-serve — increasingly through AI agents rather than static dashboards - Bring a point of view to the enterprise roadmap and GTM strategy before you're asked REQUIRED SKILLS AND EXPERIENCE - 6+ years in product or GTM data science, with significant experience on B2B, collaboration, or multi-seat products - Hands-on experimentation where the unit of randomization differs from the unit of analysis: cluster randomization, interference, and small-sample designs - Strong retention and survival modeling, cohort analysis, and segmentation at both user and account level - Experience defining adoption, retention, and revenue metrics (activation, NRR, GRR, expansion) and getting the company to agree on them - Built scoring or forecasting models that Sales, Customer Success, or Finance actually used - Expert SQL, including messy CRM, billing, and product data joined at the account level; strong Python; comfortable building your own datasets in dbt - A track record of analysis that changed a product roadmap or GTM decision, and the confidence to push back on an attractive story when the evidence doesn't support it - Heavy, practical use of AI tools to move faster in your own work PREFERRED QUALIFICATIONS - Experience at a company that grew from bottoms-up adoption into enterprise sales (collaboration, productivity, or developer tools) - Consumption- or usage-based revenue models and PLG-to-sales motions (PQLs/PQAs, sales-assist) - Virality, network, or graph analysis of collaboration data - Fluency with Salesforce data and RevOps tooling - Modern data stack: BigQuery, dbt, Hex BONUS POINTS - Experience with enterprise admin, security, or governance product surfaces - Built AI agents for GTM teams (account research, deal reviews, QBR prep) - Early member of an enterprise or GTM data function This is a full-time role based in our Foster City, CA office with an in-office requirement of Monday, Wednesday, and Friday. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Location: Toronto; San Francisco; Canada; Seattle; London; United States; New York 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: Evaluation is critical to making progress in scaling intelligence. As models continue to become superhuman in many real-world use cases, we must continue to develop new evaluation techniques that accurately reflect what models are already capable of, as well as set the agenda for what future models should be capable of. In this role, you are responsible for creating these next-generation evaluation methods and infrastructure to measure LLM progress. Key Responsibilities: - Create ambitious new evaluation benchmarks that push the limits of what our models can accomplish. - Work on highly cross-functional teams to translate model feedback into trustworthy, repeatable evaluations. - Conduct research to advance the state-of-the-art in LLM evaluation methods, including training LLM judges; refining LLM-based data synthesis pipelines; and improving evaluation efficiency. - Build scalable and reusable tools for digging into model performance. Qualifications: - You enjoy rapidly building prototypes that demonstrate the boundaries of what LLMs are capable of, and you have developed resources to measure those capabilities. - You have spent dozens of hours reviewing complex data and LLM outputs to ensure high data quality. - You are obsessive about rigorously measuring AI capabilities, and also about making sure your measurements actually align with the capabilities you care about. - You have strong software engineering skills. Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   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: London; Europe; New York; Paris; 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: Code-generating LLMs and autonomous agents are revolutionizing how software is built and tasks are automated. At Cohere, we’re pushing the boundaries of what’s possible with these technologies for enterprises, and we’re looking for a senior member for the Agent Code team. You’ll be at the forefront of research and engineering, driving the development of cutting-edge code LLMs and agent systems that can interact with the digital world to solve complex tasks with minimal human oversight. This role is hands-on and research-driven. You’ll dive into the latest literature on code LLMs and agents, experiment with frontier models, and collaborate with a team of talented engineers and researchers to build scalable, production-ready solutions. At Cohere, we blend engineering and research seamlessly—everyone contributes to both, depending on their interests and organizational needs. We provide access to world-class compute resources, data, and talent to ensure you can do your best work. Note: We have offices in London, Toronto, New York and San Francisco, but we’re also remote-friendly! This team operates primarily between ET to CET time zones, so we’re seeking candidates in locations that align with these hours for effective collaboration. Key responsibilities: - Stay up-to-date with the latest research in code LLMs, agents, and related fields, implementing novel ideas into our systems. - Design and implement scalable strategies to train code models, and deploy agent frameworks for inference and sampling. You will be collaborating with the pretraining team, create SFT trajectories and work on existing and new RL algorithms - Hillclimb on existing benchmarks and design new ones that reflect the needs of our enterprise users - Lead experiments on our state-of-the-art compute infrastructure, pushing the boundaries of what’s possible with frontier LLMs. Qualifications: - A PhD in Computer Science, Machine Learning, or a related field, with publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP). - Deep expertise in code LLMs and agent systems, with a strong understanding of the latest research and trends. We are looking for people who not only have worked with code models, but have actively contributed to their development - Hands-on experience with frontier LLMs and their applications in code generation or automation. - Strong software engineering skills, with proficiency in Python and PyTorch, TensorFlow, or similar frameworks. - Experience with distributed systems, cloud infrastructure, and scalable architectures. - A proactive, self-motivated mindset, with a passion for solving ambitious, open-ended problems. Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. 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: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile gaming industry. Within the Data team, you’ll join the BI/Prediction Team which is an autonomous squad of around 10 people. The team is composed of top-tier product managers, software & data engineers, data scientists and data analysts. ROLE The objective of this team is to accelerate the growth of the company by serving as the on-demand prediction provider for all Voodoo BUs. This involves addressing critical needs such as predicting campaign LTV for User Acquisition optimization, determining optimal monetization offers for millions of players or constructing confidence intervals for time series data prediction. We want to onboard a passionate senior data scientist with significant experience in a similar environment to allow us to go one step further. This is an opportunity to have a strategic and critical impact on Voodoo’s success. This position is hybrid and requires 3 days per week in the office based in Paris. - Take ownership of our products modeling pipelines - Contribute to high modeling performance through insightful ideas and initiatives. - Build and deploy quickly scalable ML systems. - Engage with colleagues across the company to leverage new ideas and perspectives and demonstrate excellent communication to efficiently cooperate with product managers, teammates and stakeholders. - Deep dive into data to discover relevant insights. - Build a rich understanding of the mobile gaming industry, the company strategy, our products and their fit within the company’s daily operations. - Mentor and guide a team of data scientists, fostering technical excellence and autonomy. - Establish and enforce best practices in ML engineering, experimentation, and reproducibility across projects. - Champion a culture of impact-driven research, ensuring models not only perform well technically but also create tangible business value. - Proactively identify risks in modeling approaches, data quality, scalability, business alignment and design mitigation strategies. PROFILE - Extensive experience building machine learning systems - Extensive experience with Python, SQL and MLOps best practices - Cloud experience needed (ideally AWS but could be another cloud provider) - Airflow and DBT experience is a nice to have - Excellent Communication in English and French mandatory - You enjoy working in a team, learning new things, sharing knowledge - Experience in a tech startup/scaleup is a plus - Strong achievements on Kaggle will be valued BENEFITS - Competitive salary - Comprehensive relocation package (including visa support) - Premium healthcare (SideCare) for you and your family 100% borne by Voodoo - Swile Lunch voucher - Gymlib (100% borne by Voodoo) - Wellness activities in our Paris office - Unlimited vacation policy - Remote days - Child daycare facilities (Les Petits Chaperons rouges)

Location: Athens; Limassol; Thessaloniki; Nicosia; Fully Remote - in other eligible locations Workplace: hybrid The Role: We are looking for a skilled MLOps Engineer to join our team and play a key role in bridging the gap between our Data Science and Infrastructure teams. You will be responsible for supporting the Data Science team in MLOps-related tasks while also helping in DevOps initiatives, including CI/CD pipeline creation, provisioning of cloud resources using tools like Terraform, and Kubernetes orchestration. You will collaborate closely with data scientists and engineers to deploy data pipelines, train machine learning models, and manage their deployment within scalable cloud environments while ensuring high performance, security, and reliability throughout the ML lifecycle. The main responsibilities of the position include: Assist in designing, implementing, and maintaining scalable MLOps pipelines on AWS using services such as SageMaker , EC2 , EKS , S3 , Lambda and other relevant AWS tools Coordinate with our platform team to troubleshoot Kubernetes clusters (EKS) to orchestrate the deployment of machine learning models and other microservices Develop and maintain CI/CD pipelines for model and application deployment, testing, and monitoring Collaborate closely with Data Science, and DevOps team to streamline the model development lifecycle, from experimentation to production deployment Implement security best practices, including network security, data encryption, and role-based access controls within the AWS infrastructure Monitor, troubleshoot, and optimize data and ML pipelines to ensure high availability and performance Set up and manage model monitoring systems for performance drift, ensuring continuous model improvement Main requirements: Bachelor’s degree in Computer Science, Engineering, or related field 2+ years of hands-on experience in MLOps, DevOps, or related fields Knowledge and preferable working experience in AWS services for machine learning, such as SageMaker , EKS , S3 , EC2 , Lambda , and others Exposure to Kubernetes for container orchestration Experience with Docker Exposure to infrastructure-as-code tools such as Terraform or CloudFormation Familiarity with CI/CD tools such as GitLab CI Understanding machine learning model lifecycle Familiarity with monitoring and logging solutions like Prometheus , Grafana , CloudWatch and ELK Stack Understanding of networking concepts and cloud security best practices Proficiency in Python and Bash , and comfortable working in Linux environments Strong problem-solving and communication skills The following will be considered an advantage: Experience working with serverless architectures and event-driven processing on AWS Familiarity with advanced Kubernetes concepts such as Helm Experience with Data Engineering pipelines, ETL processes, or big data platforms Experience with ML frameworks like TensorFlow, PyTorch and Keras Experience with ML platforms like Kubeflow and/or SageMaker Experience with workflow engines like Argo Workflows and/or Airflow Benefit from: Attractive remuneration package plus performance related reward Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.

Location: London; San Francisco; New York; Paris; Toronto; Montreal 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: Advance the state of the art for model post training, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organisational needs. We have all the compute, data, and talent available for you to do your best work. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! Key Responsibilities: - Design and write high-performant and scalable software for training models. - Consistently post-train the models to reach SOTA level performance. - Coordinate with other specialist teams (Agentic, Code…) to produce models that have strong all encompassing performance. - Craft and implement techniques to improve the performance and results of our training cycles both on the SFT and the RL regime. - Research, implement, and experiment with ideas on our supercompute and data infrastructure. - Learn from and work with the best researchers in the field. Qualifications: - Extremely strong software engineering skills. - Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR. - Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray). - Experience using large-scale distributed training strategies. - Hands on experience on training large model at scale. - Hands on experience with the post training phase of model training, with a strong emphasis on performance optimisation. - Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP). This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere. Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. 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.