ML-инженер вакансии

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: New York; San Francisco ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models toward higher throughput and lower latency, we’d love to hear from you! YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality, high-performance code - You’ve worked with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT) - You’re familiar with NVIDIA GPU architecture and CUDA - You have experience with ML performance engineering (tell us a story about boosting GPU performance: debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc.) NICE-TO-HAVE: - Familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc.)

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.

Задачи: — Конфигурировать и разворачивать инфраструктурные компоненты — Адаптировать/разрабатывать с нуля автоматизированные пайплайны под актуальные бизнес-задачи (AutoML, LLM, computer vision и пр) — Создавать и поддерживать пользовательские инструменты для работы в едином ML-контуре применения и обучения — Масштабировать разрабатываемые системы и инструменты для управления жизненным циклом моделей машинного обучения Требования: — Опыт DevOps от 3х лет (Docker, Helm, Jenkins/GitLab CI, Python) — Опыт ML/MLOps от 1 года (Airflow, JupyterHub, MLflow, Seldon, CUDA) — Опыт администрирования Kubernetes от 2х лет — Опыт работы с Hadoop, Spark, Kafka, ELK Условия: — Работа в аккредитованной IT компании, имеющей собственные продукты — Формат работы: удаленный по РФ — Предоставляем расширенный ДМС (со стоматологией) — Выдаем необходимую для работы технику (ноутбук) — Возможность воспользоваться реферальной программой: “Приведи товарища” — Участие в Бонусной программе — Помогаем в ипотеке и других пособиях — Предоставляем возможность построить карьеру в рамках ведущих компаний России

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 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: Tbilisi; Belgrade; Budapest; Madrid; Riga; Tallinn; Valencia; Vilnius; Yerevan Workplace: remote 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

О ПРОЕКТЕ DigiNavi — это иммерсивная AR-навигация для крупных общественных пространств (ТЦ, аэропорты). Мы превращаем локации в SMART-зоны с помощью Computer Vision и дополненной реальности. Наша команда внедряет подход VibeCoding: вы выступаете архитектором решений, используя AI-агентов (Claude Code, Cursor) как основной инструмент исполнения. ЧЕМ ПРЕДСТОИТ ЗАНИМАТЬСЯ — AI-Driven Development: Разработка и поддержка кода через AI-инструментарий. — R&D & Prototyping: Быстрая проверка гипотез и внедрение алгоритмов (SuperPoint, NetVLAD, Gaussian Splatting). — Architecture: Рефакторинг CV-компонентов в гетерогенной среде (Go / C++ / Python). — Integration: Внедрение ML-моделей в микросервисную архитектуру через gRPC и Kafka. — Optimization: Работа с high-load системами и оптимизация инференса моделей. ЧТО МЫ ЖДЕМ ОТ ВАС — CV & ML Expert: Глубокие знания PyTorch и OpenCV. Опыт создания Computer Vision решений. — VibeCoding Skills: Практический опыт работы с Claude Code, Cursor или аналогами. Понимание SDD и TDD подходов. — Backend: Опыт production-развертывания (FastAPI, Docker) и понимание микросервисов. — Polyglot Mindset: Готовность работать в окружении, где используются Go и C++ (чтение и интеграция). — Документация: Умение создавать техническую документацию и структурировать процессы там, где их нет. БУДЕТ ПЛЮСОМ — Опыт оптимизации инференса для мобильных платформ. — Работа с облачной инфраструктурой GCP. — Понимание специфики разработки в сфере AR/VR.

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: New York; San Francisco ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We’re looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you’ll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads: LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You’ll help teams reach outcomes most engineers can’t on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We’re looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. WHAT YOU’LL WORK ON: - Work hands-on with companies like Suno, Cognition, and Meta to architect and optimize production AI workloads on Modal - Contribute to open-source projects (members of the team are active contributors to SGLang) and publish technical content that demonstrates Modal’s capabilities across the AI stack - Collaborate with Modal’s product and sales teams, contributing to the platform as both an engineer and a product stakeholder - Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work - Conduct technical demos, experiments, and proofs of concept that make Modal’s performance advantages tangible YOU MAY BE A FIT IF: - You have 2+ years of professional ML engineering experience, ideally with hands-on work in inference optimization, model training, GPU programming, or ML infrastructure - You’re familiar with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains and can go deep on at least one (you don’t need all of them) - You’re a strong communicator who can go deep on technical architecture with an engineering team and clearly articulate tradeoffs to technical leadership - You have a genuine interest in working directly with customers: you find it energizing to understand someone else’s problem and help them solve it - You’re willing to work in person in New York City, San Francisco, or Stockholm NICE-TO-HAVE: - Side projects, open-source contributions, or published work you’re proud of in ML or systems performance

Задачи: — Разрабатывать и внедрять ML-модели в областях Computer Vision и NLP. — Развёртывать и оптимизировать inference-пайплайны на GPU-серверах. — Работать над мультимодальными AI-фичами (текст, изображения, видео, аудио). — Масштабировать производительность моделей под растущую базу пользователей. — Сотрудничать с backend-инженерами над продакшн-API. — Проводить эксперименты и A/B-тесты на основе реальных пользовательских данных. Требования: — 5+ лет практического опыта в ML/AI-разработке. — Отличное знание Python и фреймворков PyTorch / TensorFlow. — Глубокое понимание NLP (LLMs, embeddings, transformers) и CV (image generation, diffusion models, video processing). — Опыт работы с GPU-обучением и inference. — Навыки оптимизации моделей (quantization, distillation, batching, caching). — Опыт продакшн-деплоя ML-сервисов. — Будет плюсом: опыт работы с видео-AI моделями, понимание high-load inference систем, опыт с ML-мониторингом и аналитикой (Weights & Biases, MLflow, Grafana), опыт в сфере conversational AI или чатботов, участие в open-source, Kaggle или публикации в ML-сообществе. Условия: — Работа в международной продуктовой компании. — Гибкий график и удалённый формат. — Возможность влиять на ключевые продуктовые решения.

Задачи: — Доработка алгоритмов CV/ML — Разработка и поддержка бэкенда — Разработка фронтенда (минимально) — Рефакторинг и оптимизация кодовой базы — Участие в полном цикле разработки: обсуждение, реализация, тестирование, запуск в продакшн Требования: — Уровень: Senior (коммерческий опыт от 5 лет) — Python (Core): глубокое знание языка и экосистемы — Computer Vision (CV): практический опыт с OpenCV и другими библиотеками для обработки изображений/видео, понимание технологий, наличие минимального опыта — Machine Learning (ML): опыт работы с фреймворками (TensorFlow, PyTorch или аналогами) для задач классификации, детекции, трекинга — Backend (Node.js): уверенное владение Node.js и фреймворками (Express.js, Nest.js) (желательно, но не критично) — Базы данных: опыт работы с реляционными (PostgreSQL) и/или NoSQL (MongoDB) СУБД — Git: уверенное владение системой контроля версий — Желательно: опыт работы с видеопотоками (RTSP-протокол), Frontend (JavaScript) с Vue, Docker и основы DevOps, понимание принципов работы message brokers (RabbitMQ, Kafka), опыт оптимизации кода и ML-моделей для работы в реальном времени, опыт работы с Kubernetes Условия: — Оформление: ТД / ИП / СЗ — Полная занятость — Работа над проектом по системе AI видеоаналитики — Стек: FastAPI, ONNX Runtime / TensorRT, OpenCV, FFmpeg, MS, Meta, MLflow, Docker, Docker Compose (лучше кубы), YOLO, ResNet, MobileNet, ONNX, MLflow, NMS (Non-Maximum Suppression), JSON, Webhook или очереди, queue, threading/asyncio, REST API, оценка качества (loss, accuracy, confusion matrix и др) — Будет плюсом наличие собственных моделей, пригодных к дообучению под задачи проекта.

Location: Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; London, United Kingdom; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge. Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success. Your responsibilities will include: Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning. Creating the datasets, metrics, and pipelines that drive measurable improvements across the system. Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization. Establishing MLOps practices, including orchestration, observability, and experiment tracking. Collaborating with the engineering team on system design and with JetBrains Research on the research agenda. Defining hiring criteria, growing the ML team, and shaping the ML team culture. We expect you to have: A proven track record as an ML/AI Lead. At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI. A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches. Hands-on experience with: Prompt engineering and LLM pipeline design, including evaluation. Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent. Vector databases and retrieval-augmented generation (RAG) patterns. Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models. Strong Python skills – Kotlin knowledge would be a plus. Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences. Proficiency in English, both written and verbal. Our ideal candidate would have: Experience with ontologies, knowledge graphs, or graph-based reasoning. Experience in early-stage startups – you enjoy the zero-to-one phase. The ability to think strategically about product-led AI, beyond just training models in isolation. A background in code analysis, developer tools, or software engineering research. Experience with multi-agent systems or complex agentic workflows. Actively contributed to relevant open-source projects or publications. What we offer A competitive salary and JetBrains benefits. A generous runway and corporate resources with startup autonomy. #LI-KP1 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.

Задачи: — Разработка и оптимизация моделей для обработки/генерации звука. Требования: — Минимум 3 года работы в разработке и оптимизации моделей для обработки/генерации звука; — Глубокие знания в области DL и ML; — Опыт работы с инструментами и библиотеками TensorFlow, TensorRT, Triton (NVidia), PyTorch, Hugging Face; — Умение работать в команде и проактивная позиция; — Знание архитектуры моделей (Transformers, RNN и др.); — Опыт работы с большими данными и основами обработки данных; — Умение оптимизировать модель и проводить её оценку (A/B тестирование, метрики качества). Желательно: — Опыт работы над задачами speech enhancement, noise cancellation, tts, asr. Условия: — Оформление: Только ИП.

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: Remote Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE We’re looking for Research Engineers to contribute to our ambitious research agenda spanning multimodal foundational models, interactive world modeling, and real-time generation. This role is highly collaborative and will touch many aspects of our broader research efforts, taking a full-stack approach across pretraining, SFT/RL post-training techniques, evaluation, and bringing models to production. WHAT YOU’LL DO - Run experiments to teach world models new behaviors — action following, scene manipulation, camera control, and beyond - Develop and test new data strategies, architectural variants, and training techniques - Design evaluations that measure model capabilities, and use them to drive model improvement - Take features from research prototype to production, collaborating with product and creative teams to address application-specific gaps - Contribute across the entire stack (data pipelines, modeling, production inference) to move projects forward WHAT YOU’LL NEED - 4+ years of experience in machine learning research or engineering - Familiarity with the architecture, training, and inference of large-scale multimodal generative models - Experience building robust data pipelines for pretraining and post-training - Comfort working across the full research stack: data, training, evaluation, and deployment - Proficiency with at least one ML framework (e.g. PyTorch, JAX) and experience with distributed training at scale - Ability to context-switch quickly and drive projects forward in a fast-moving, ambiguous environment - Excitement about building AI that simulates the world Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: Toronto; London; New York; Paris; 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! Role Overview: As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. 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: - Design and build scalable inference pipelines that run on large GPU clusters. - Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance. - Research and implement innovative synthetic data curation methods, leveraging Cohere’s infrastructure to drive advancements in natural language processing. - Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models. Qualifications: - Strong software engineering skills, with proficiency in Python and experience building data pipelines. - Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools. - Experience working with LLMs through work projects, open-source contributions or personal experimentation. - Familiarity with LLM inference frameworks such as vLLM and TensorRT. - Experience working with large-scale datasets, including web data, code data, and multilingual corpora. - A passion for bridging research and engineering to solve complex data-related challenges in AI model training. Bonus: paper 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.