Вакансии

Location: Brazil; Argentina; Colombia; Chile; Peru; Uruguay About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.

Location: United Kingdom; Germany; Poland; South Africa; United Arab Emirates; Egypt About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems. SENIORITY: Experienced / Research-Level Engineer EDUCATION: Master's degree or PhD in a relevant quantitative discipline LANGUAGE: Strong written and verbal English LOCATION: Remote — Worldwide Key Responsibilities Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. Design and execute tests to verify implementation correctness and compliance with objective performance requirements. Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. Document technical approaches, implementation decisions, test results, and performance findings clearly. Deliver high-quality, reproducible task submissions within project deadlines. Requirements Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. Strong professional or research experience in machine learning and practical ML engineering. Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. Hands-on experience using coding agents within a Python development workflow. Understanding of machine learning model development, training and inference workflows, and evaluation methods. Ability to build reproducible implementations and verify correctness through systematic testing. Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. Strong written communication skills and the ability to explain technical findings. Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Team Description: The Ads Retrieval ML team builds the machine learning systems that identify relevant advertising candidates for Reddit users. Retrieval sits at the heart of the ads delivery funnel: before downstream ranking and auction decisions, our models determine which campaigns and ads are eligible to compete. We work on large-scale retrieval across multiple objectives, placements, and geographies. Our work combines representation learning, candidate generation, nearest-neighbor search, behavioral and contextual signals, and rigorous offline and online experimentation. Role Description: We are looking for a Staff Machine Learning Engineer to provide technical leadership for the Retrieval and Targeting ML team. You will lead the design and evolution of retrieval models and modeling practices that improve relevance, advertiser outcomes, and user experience at Reddit scale. This is an applied ML role centered on retrieval modeling and end-to-end product impact. You will be expected to stay close to the technical details—from data and objective design through model development, evaluation, experimentation, and launch—while setting direction for other engineers. Responsibilities: Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders. Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit’s advertising surfaces. Apply modern approaches such as two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and other deep learning techniques when they create meaningful product value. Improve the retrieval stack across key modeling decisions, including objectives, labels, sampling strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth. Work with approximate nearest-neighbor and vector retrieval systems, reasoning about recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs. Establish strong evaluation practices that connect retrieval metrics—such as recall, precision, candidate coverage, calibration, and downstream lift—to ads and user outcomes. Lead offline analysis and online experiments, interpret ambiguous results, and translate findings into the next modeling iteration. Partner with downstream ranking, ads platform, auction, measurement, and product teams to ensure retrieval models integrate effectively into the full ads funnel. Write design documents, review code and model changes, and raise the quality bar for modeling, testing, observability, and production ownership. Mentor ML engineers and help grow the team’s expertise in retrieval, recommendation, and representation learning. Required Qualifications: 7+ years of industry experience, including substantial experience building and shipping applied ML products. Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems. Strong understanding of retrieval modeling concepts, including DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval. Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks. Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration. Strong command of experimental design and model evaluation, including how offline retrieval metrics relate to downstream business and user metrics. Experience working with large-scale behavioral, contextual, or content datasets and complex feature pipelines. Strong software engineering fundamentals and the ability to write clear, reliable, maintainable production code. Technical leadership experience: setting direction, leading complex projects, influencing partner teams, and mentoring other engineers. Excellent written and verbal communication, with the ability to explain complex modeling choices to technical and non-technical audiences. Preferred Qualifications: Experience with ads retrieval, ads ranking, ad targeting, ad serving, recommendation, search relevance, or marketplace optimization Experience modeling user, content, campaign, or ad interactions with sequential, graph, or multimodal signals Experience connecting retrieval improvements to downstream ranking, auction, conversion, revenue, or user-experience outcomes Experience in ads marketplaces at peer companies Publications, patents, or industry contributions in applied ML or ranking systems Experience with sequential modeling (e.g., RNNs, Transformers) Benefits: 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago) Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-AJ1 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $230,000 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Remote - Ontario, Canada (DNU) Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Staff Machine Learning Engineer on Twilio’s AI/ML Platform team. About the job We are actively recruiting for this role to fill an existing vacancy. This position is needed to build the foundational AI/ML capabilities and common platform tooling that power intelligent engagement experiences across Twilio. You will influence the design and evolution of our company-wide ML/AI Ops foundation, ensuring every AI capability incorporates rigorous offline and online evals to maintain exceptionally high quality. You will drive improvements to managing LLM workloads across the company, while ensuring easy and compliant access to data for AI/ML exploration and product development. This role requires a builder mindset to bridge theoretical research, production-grade experimentation, and scalable, enterprise-quality software. Responsibilities In this role, you’ll: Conduct deep-dive research into and implement state-of-the-art LLM inference and orchestration. Identify opportunities to leverage small language via fine-tuning/distillation. Build ML systems that hold up at Twilio scale. Set standards and tooling for building evals across a range of AI/ML capabilities. Rapidly acquire new technical skills and knowledge in a fast-paced, high-delivery environment. Proactively leverage and integrate the latest AI development stacks to bypass boilerplate engineering and focus on core differentiation. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: 8+ years applied ML/AI experience with a track record of owning technically ambitious systems end to end rather than contributing to someone else's design. Comfort operating in a 0-to-1 setting with ambiguous requirements and a strong bias for action. Proficiency in Python programming language. Experience building cloud-based services on AWS, GCP, or Azure, with high-volume data, streaming or real-time inference paths, and a range of data stores. Strong fundamentals of statistical machine learning algorithms, transformer models, LLMs. Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics for non-deterministic AI features at scale. Strong communication skills and highly effective collaborator who works well with teammates. Familiarity with AI-assisted development tools (e.g., Claude, Codex, GitHub Copilot, Cursor, etc.). Desired: Prior experience building evals for autonomous agents and large language models. Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context/consistency. Prior experience working in a globally distributed team. Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research. Location This role will be remote and based in Ontario, British Columbia or Alberta, Canada. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off. The estimated pay ranges for this role are as follows: $160,320 - $200,400 Target Bonus Percentage 12.5% The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Задачи: — Разработка кросс-ассетных стратегий: поиск альфа-сигналов, построение и валидация математических и ML-моделей для прогнозирования движений рынка на различных горизонтах (от HFT до среднесрочных стратегий).

Развитие и поддержка ML-инфраструктуры (Linux, Docker, Kubernetes, Python, GitLab CI, Git, Kubeflow, Prometheus, Grafana Airflow S3 / MinIO HelmPyTorch / TensorFlow Fine-tuning — LoRA, QLoRA, PEFT Дистилляция RAG,Hugging Face Quantization, ONNX, TensorRT). Интеграция LLM и других моделей в продакшн-окружение.

Знание Python и основ машинного и глубокого обучения (ML/DL). Понимание NLP и LLM, принципов дообучения моделей (Fine-tuning), построения RAG-систем и семантического поиска.

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Location: Москва Мы — команда, которая занимается обучением LLM, VLM и CV моделей. Создаем нативные омнимодальные архитектуры, новые способы кодирования и совместного обучения в доменах изображений, аудио, видео и т.д. Наши основные направления: обучение LLM и VLM с нуля, разработка новых архитектур, Computer Vision research, создание opensource инструментов, сбор и подготовка данных, деплой моделей для MVP. Работаем на кластере с GPU уровня H100. **Ищем** Edge AI / ML Deployment инженера, который проведёт модель через весь путь от RnD-прототипа до prod-ready решения: оптимизация инференса, квантование и запуск на Edge-девайсах, масштабирование на кластерах. Обязанности * подготовка RnD-технологий к prod-ready решению; * оптимизация моделей и кода инференса для масштабирования на кластерах; * подготовка и запуск моделей на Edge-девайсах (Nvidia Jetson, Rockchip, Amlogic Khadas). Требования * опыт работы с Nvidia Jetson (Orin, Xavier, Nano); * уверенный C++ (для инференса) + Python (для скриптов и подготовки); * умение делать квантование моделей из PyTorch-весов (FP32, FP16, FP8, FP4), квантование (INT8, INT4), QAT и калибровка моделей; * Linux, CMake, опыт кросс-компиляции под ARM. **Будет плюсом:** * опыт работы с NPU от Rockchip (RK3588, RK3568, RV1126) / Amlogic (A311D, C308X, Khadas); * знание API Nvidia CUDA Условия * комфортный современный офис рядом с м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, годовая премия от 3х окладов * большой спортзал и зоны отдыха * система обучения для профессионального и карьерного развития * расширенный полис ДМС с первого дня работы и страхование для семьи * программа ипотеки для сотрудников со скидкой -1/3 от текущей ставки * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — Останавливать абьюз до того, как потрачен compute (6M+ генераций в день, каждая мошенническая генерация расходует реальные GPU) — Строить систему, которая выдерживает адаптацию противника (фермы из сотен аккаунтов, перепродажа доступа, автоматизированный сбор промобонусов) — Разбирать кейсы руками и собирать сигналы из сырых событий, платежей и поведения пользователей — Самостоятельно доводить от первой гипотезы до работающего скоринга, мониторинга и обновления модели Требования: — 3+ года в DS/ML — Опыт работы с Python и SQL — Опыт внедрения моделей в production — Опыт работы с бустингами, дисбалансом классов и графами связей — Умение оценивать модель через предотвращённые потери и стоимость ложных блокировок Условия: — full-time (6 дней в неделю) — Полная поддержка с релокацией (финансовая + операционная) — Конкурентная зарплата в USD + опционы

Руководить командой ML-инженеров; Участвовать в найме и развитии команды;

Location: Тольятти Мы ищем редактора (AI-тренера), который станет наставником для GigaChat. Если ты любишь работать с текстами, видишь красоту в деталях и мечтаешь влиять на технологии будущего — это твой шанс. Обязанности ### Что предстоит делать: * создавать и редактировать тексты на самые разные темы * анализировать ответы GigaChat, находить ошибки и улучшать логику его мышления * разрабатывать сценарии диалогов и тестовые задания * искать оригинальные источники, проверять факты и доводить текст до совершенства * тестировать новые версии модели и давать фидбэк разработчикам. Требования ### Мы ищем тебя, если ты: * получил высшее лингвистическое, журналистское или переводоведческое образование * имеешь опыт работы с текстами - копирайтер, технический писатель или любые подобные должности * обожаешь детали: твоя сверхспособность — находить нюансы даже в идеальных предложениях * легко ориентируешься в больших объёмах информации и быстро погружаешься в новые темы. ### Будет круто, если у тебя есть: * опыт работы с LLM (ChatGPT, GigaChat, DeepSeek и пр.) * навыки написания промтов * понимание технической терминологии (JSON, Markdown). Условия ### Что мы предлагаем: * работа в удалённом формате из городов без районного коэффициента * ежегодный пересмотр зарплаты и годовая премия * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнероввознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Команда DataPlatform-Tools реализует платформенные инструменты для сервисов, AI-агентов и потребителей в домене HR-аналитики всего Банка. Мы обеспечиваем self-service для инженеров, аналитиков данных, DS, ML-инженеров: готовые DAG пайплайны, тесты качества данных (DQ), lineage, BI-визуализации. Разработка интеллектуальных ассистентов и чат-ботов для автоматизации процессов подбора персонала и карьерного развития сотрудников. Наш фокус — доступность данных не только для сотрудников, но и для AI-агентов! Для этого мы применяем подходы топовых компаний в мире и формируем собственную практику на огромном массиве данных Обязанности * развитие текущих LLM-агентов и решений на их основе * проектирование и разработка новых LLM-агентов и интеллектуальных ассистентов * работа с RAG-системами и векторными базами данных * оценка и повышение качества ML-моделей * участие в создании чат-ботов для автоматизации HR-процессов Требования * опыт работы с LLM и фреймворками для разработки агентов (LangChain, LangGraph и др.) * уверенные знания Python и SQL * опыт работы с NLP-задачами * опыт создания чат-ботов и интеллектуальных ассистентов * понимание принципов RAG (Retrieval-Augmented Generation) * опыт работы с векторными базами данных * навыки оценки качества ML-моделей Условия * комфортный современный офис рядом с м.Кутузовская * возможность выбрать удобный график – офис/гибрид * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте (для Junior позиций) * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * льготная ипотека для каждого сотрудника * бесплатная подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера. * корпоративная пенсионная программа * отсутствие строгого дресс-кода.

Location: Hong Kong or Remote Nex is on a mission to help families rediscover the joy of movement. Created by parents for parents, Nex combines technology and play to deliver fun, social, and interactive experiences powered by natural body motion, encouraging kids and adults to move more, play more, and have fun together. Nex Playground, the company’s award-winning active play system, is purpose-built to get families moving year-round, with safety and privacy as core considerations in its intentional design. It is certified kidSAFE+ COPPA compliant and built to support healthy, active play for all ages and abilities. Nex Playground features a growing library of 50+ experiences, including motion and dance games, fitness and educational experiences, and Nex Originals. Content includes collaborations with partners like Hasbro, Sesame Workshop, and NBCUniversal. Nex has been recognized by Fast Company’s Most Innovative Companies, TIME’s Best Inventions, and Parents’ Best Entertainment System for Families, and has earned Red Dot, IDEA, and Core77 international design awards. We encourage you to explore Have Fun and Is Motion Gaming Back? , as they offer a deeper look into our culture, values, and explain how our approach to motion gaming differs from previous generations. Nex employees may be expected to collaborate with colleagues across different time zones. Depending on the role and location, occasional travel may also be required for company events, external meetings, and other business-related activities. Important Notice: ⚠️ To protect yourself from recruitment scams, please note that Nex communicates through official company emails ending in @nex.inc . If you receive a suspicious email or message, please do not respond and report it immediately to us. Location: Hong Kong or Remote Type: Full Time The Role As a ML Researcher at Nex, you will develop new machine learning models and algorithms that push the boundaries of computational perception and interaction on Nex Playground. You will join a small, deeply technical team that combines research and engineering to solve complex problems in sensing, understanding, and multimodal interaction. The ML Research role emphasizes rapid experimentation, exploring new ideas and methods to expand what our platform can sense, understand, and respond to. You will work within the ML Research group, collaborating closely with ML Engineers who build the infrastructure that accelerates your research. This role is ideal for researchers who want to see their work directly impact product capabilities while maintaining a focus on cutting-edge innovation. The Mindset You are driven by curiosity and technical discovery. You see research as a systematic process of exploration and validation, not just theoretical work. You balance scientific rigor with practical impact, knowing that the best research solves real problems. You thrive in a team that values experimentation velocity and measurable technical improvement. What You’ll Do Develop novel ML models and algorithms for computational perception and interaction Design and execute rapid experiments to validate new ideas and methods Explore advancements in computer vision, audio processing, sensor fusion, or related domains Collaborate with ML Engineers to integrate research outcomes into training pipelines and production systems Measure and track experimentation velocity, the number and quality of validated experiments per quarter Contribute to research planning and help define the technical roadmap alongside the Engineering Manager and Tech Lead Document research findings and communicate technical progress to the broader team Must Have 2+ years of hands-on ML research experience in industry, academia, or research labs Demonstrable track record of designing and conducting ML experiments from hypothesis to validation Proficiency in Python for ML research and experimentation Deep expertise with PyTorch or TensorFlow for model development Experience training and evaluating ML models on real datasets Understanding of model evaluation metrics, experimental design, and statistical validation Familiarity with data preprocessing, augmentation, and management for ML workflows Experience presenting research findings to technical audiences Nice To Have Expertise in real-time inference, model optimization, or efficient architectures Experience with self-supervised learning, few-shot learning, or foundation models Background in multimodal learning combining vision, audio, and sensor data Contributions to open-source ML projects or released research code Experience collaborating with engineers to productionize research outcomes Familiarity with ML Engineering practices: training pipelines, experiment tracking, MLOps Background in edge computing, on-device ML, or resource-constrained environments Experience with sensing technologies: cameras, microphones, IMUs, or haptic systems Knowledge of privacy-preserving ML, federated learning, or on-device data processing We Offer Competitive compensation package. Flexible working hours and vacation policy. Product-driven culture that treasures talents and individual growth. Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field Nex is located in San Jose, California, USA and Hong Kong . Learn more about us at https://www.nexplayground.com/about . We encourage applications even if you don’t meet more than 50% of the requirements — we believe that experience comes in many forms! Nex is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, gender identity, and sexual orientation), national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable law. This policy applies to all individuals at every stage of the employment relationship, including all current and prospective employees, and covers all employment decisions including recruitment, hiring, job assignment, promotion, compensation, benefits, training, discipline and termination. We are committed to providing a workplace free from discrimination and harassment and to fostering an inclusive environment for all employees.

Location: Mountain View, California, USA About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.   Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.   Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.   What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office. The base salary range for this full-time position is $250,000 - $300,000+ bonus + equity + benefits. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Brussels, Belgium We currently have a vacancy for a Senior LLMOps Engineer fluent in English, to offer his/her services as an expert who will be based in Belgium. The work will be carried out either in the company’s premises or on site at customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team. Your tasks: Design, build, and maintain production-grade ML systems with a strong focus on Large Language Models (LLMs) in a secure hybrid on-prem / cloud infrastructure; Deploy, test, manage and monitor ML models in different containerized environments; Work closely with data scientists and back-end developers to build, test, integrate and deploy ML models; Evolve the LLMOps lifecycle: data preparation, fine-tuning, evaluation, deployment, monitoring, and iteration. Develop evaluation frameworks for LLM quality, robustness, and regression tracking; Analyse performance metrics and troubleshoot issues to ensure high availability and reliability; Design CI/CD pipelines, use orchestration solutions and data versioning tools; Creating automated anomaly detection systems and constant tracking of its performance and optimizing ML pipelines for scalability, efficiency and cost-effectiveness; Provision of security studies, security assessments or other security matters associated with information system projects; Provision of support and guidance to other team members on LLMOps/MLOps practices. Requirements University degree in a relevant field such as Computer Science, Information Technology, or Systems Engineering combined with relevant IT professional experience of at least 10 years; Excellent experience of managing an on-prem and/or cloud LLM / MLOps infrastructure; Experience with data analytics over big datasets, non-structured databases as well as data lakes; Experience with monitoring and logging tools (e.g. ELK stack, Prometheus, Grafana, OpenTelemetry, Cloudwatch); Experience with model testing and model validation in production environments; In depth knowledge of containerisation and orchestration platforms (e.g. Kubernetes, Docker, Podman, EKS, PKS); Good knowledge of MLflow, TensorFlow (TFX) or equivalents; Good knowledge of Airflow; Good knowledge of AWS or EU cloud providers; Good knowledge of Python; Good knowledge of Unix and Bash; Good knowledge agile software development methodologies; Good knowledge of infrastructure as code (Terraform, CloudFormation); Excellent knowledge of messaging services and platforms (e.g. Kafka, Redis, RabbitMQ); Knowledge of NoSQL databases, such as OpenSearch, MongoDB as well as query languages, such as SQL, Hive, Pig, etc. and with information extraction; Excellent command of the English language. Benefits If you are seeking a career in an exciting, dynamic and multicultural international environment with exciting opportunities that will boost your career, please send us your detailed CV in English, quoting reference (158837/11/2026). We offer a competitive remuneration (either on contract basis or remuneration with full benefits package), based on qualifications and experience. All applications will be treated as confidential. You may also consider all our other open vacancies by visiting the career section of our web site ( www.eurodyn.com) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS ( www.eurodyn.com) is a leading European Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1000 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, age, national origin, ethnicity, gender, disability, sexual orientation, gender identity or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published in www.eurodyn.com/privacy. By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorise ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy.

разрабатывать с нуля AI-агентов и микросервисы для AI-продуктов. исследовать и внедрять новейшие технологические решения в ИИ - Claw-like & Ouroboros.

Location: San Francisco, CA; Sunnyvale, CA Workplace: Hybrid ABOUT NIANTIC SPATIAL We are building for the >80% of economic activity that happens beyond the reach of screens. AI has learned from the text, images and video online, but it still lacks an accurate understanding of physical space. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. THE OPPORTUNITY As a staff member of the Map Team, you’ll own and drive significant parts of our Reconstruction and/or Localization technologies. You will be responsible for building the Map representing a living geospatial world model that can be simultaneously used to generate a high-fidelity 3D representations via Gaussian Splatting and Meshing, as well as the centimeter-level accuracy Visual Positioning System (VPS) that allows people and robots to explore the real world. This is an individual contributor role with a strong component of technical leadership where you will mentor other engineers and influence the technical roadmap. WHAT YOU WILL DO - Technical Leadership: Lead the design and implementation of some of our core technologies, namely, Structure from Motion (SfM), Feed Forward and Foundational models, and high-fidelity 3D Reconstruction (e.g. meshing, gaussian splats). - Applied Research: Up to speed state-of-the-art in relevant areas to be able to invent novel solutions in VPS and/or 3D Reconstruction alongside the team. - System Architecture: Design, develop, and maintain scalable production-grade Computer Vision systems that power Niantic Spatial’s VPS, 3D Reconstruction and 3D Mapping pipelines. - Algorithm optimization and production implementation: develop and optimize algorithms, train models, for high-accuracy and high-performance execution on CPU/GPU on the cloud or device as part of a reliable production system. - Quality & Benchmarking: Drive decision-making creating high quality data that allows the accurate spatial grounding of AI queries with structural, semantic and location specific knowledge. - Technical Strategy & Mentorship: Work with engineering leadership to define the technical roadmap and quarterly objectives for the Applied CV Team; provide high-level mentorship and code governance to elevate the team’s technical bar. - Cross-Functional Delivery: Collaborate with Product, Research, and Operations teams to ensure that state-of-the-art Computer Vision solutions translate into delightful user experiences. WHAT WE ARE LOOKING FOR - Years of Experience: 7+ years of professional experience in Computer Vision, Machine Learning, or a related field (or 4+ years with a PhD in a relevant domain). - Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master's or PhD preferred. - Core Technical Skills: Strong proficiency in Python and/or C/C++. - Specialized Expertise: Proven experience in both classical and learned-based 3D Computer Vision and ML. - Full SW lifecycle experience: Demonstrated experience in taking research into production at scale. - Technical Leadership Experience: Previous experience tech leading computer vision projects. COMPENSATION & BENEFITS The expected salary range for this role is $256,500 – $315,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. LOCATION & WORK MODEL This role is based in our San Francisco or Sunnyvale office, with three days per week in office. INCLUSIVE APPLICATION We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed — you may be exactly who we're looking for. EQUAL OPPORTUNITY Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. CANDIDATE PRIVACY I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.