Вакансии

Location: Montreal, Canada 📍 Location: Montreal, Quebec, Canada (On-site preferred; exceptional remote candidates will be considered) 📄 Employment Type: Contract-to-Permanent (Preferred) / Contract 🏢 Work Arrangement: Remote Opportunity 🚀 Start Date: Immediate 💰 Compensation: TBD -- based on skills and experience Important Screening Requirements Candidates must possess both of the following non-negotiable qualifications: Model-Based Systems Engineering (MBSE) experience, including SysML , Cameo Systems Modeler , functional decomposition, and requirements traceability. Launch and Early Orbit Phase (LEOP) operations experience, including spacecraft commissioning and/or routine satellite operations. Please note: Candidates who do not have both MBSE and LEOP experience will not be considered. Exceptional candidates may be considered for a fully remote arrangement. Remote candidates must demonstrate significantly stronger MBSE expertise and satellite operations experience than on-site candidates. About the Role We are seeking an experienced Model-Based Systems Engineer (MBSE) to support the development of advanced satellite systems through modern digital engineering practices. In this role, you will develop and maintain system architectures, create model-based engineering artifacts, and ensure end-to-end requirements traceability while supporting spacecraft commissioning and operations during the Launch and Early Orbit Phase (LEOP) . The ideal candidate has a strong background in satellite systems engineering, MBSE methodologies, and mission operations, with the ability to collaborate across multidisciplinary engineering teams. Key Responsibilities Develop and maintain system architectures using Model-Based Systems Engineering (MBSE) methodologies. Create and manage SysML models using Cameo Systems Modeler . Perform functional decomposition and maintain end-to-end requirements traceability. Support digital engineering initiatives throughout the system development lifecycle. Develop and maintain Concept of Operations (CONOPS) documentation and system behavior models. Support spacecraft commissioning and Launch and Early Orbit Phase (LEOP) activities. Collaborate with systems, software, hardware, integration, and operations teams to ensure mission readiness. Participate in architecture reviews, engineering trade studies, and technical design reviews. Support systems integration, verification, validation, and operational readiness activities. Prepare engineering documentation and communicate technical recommendations to stakeholders. Required Qualifications Demonstrated experience with Model-Based Systems Engineering (MBSE) . Hands-on experience with: SysML Cameo Systems Modeler Functional decomposition Requirements traceability Experience supporting Launch and Early Orbit Phase (LEOP) operations. Experience with spacecraft commissioning and/or routine satellite operations. Strong understanding of systems engineering principles and digital engineering methodologies. Excellent analytical, problem-solving, communication, and collaboration skills. Ability to work effectively in multidisciplinary engineering teams. Preferred Qualifications Experience developing Concept of Operations (CONOPS) documentation. Experience supporting LEO/MEO satellite systems or spacecraft development programs. Familiarity with digital engineering frameworks and MBSE best practices. Experience with satellite mission planning, systems integration, and spacecraft operations. Experience leading systems engineering trade studies and architecture reviews. What We're Looking For We're looking for an exceptional Model-Based Systems Engineer who combines deep MBSE expertise with real-world satellite operations experience . The ideal candidate has successfully applied SysML and Cameo Systems Modeler to develop robust system architectures while supporting spacecraft commissioning and LEOP activities. You are a collaborative systems thinker who can translate complex mission requirements into well-structured system models and deliver practical engineering solutions across the satellite lifecycle. Montreal-based, on-site candidates remain the preferred choice. However, truly exceptional candidates with outstanding MBSE and satellite operations experience may be considered for a fully remote arrangement. Candidates with both MBSE and LEOP experience will be given the highest priority, as these are mandatory qualifications for the role.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are looking for a strong Deep Learning Engineer to join our Autonomy team and develop the learning-based algorithms that power dynamic locomotion and whole-body control on our humanoid robots. You will develop robust, reusable motion capabilities that enable the robot to move dynamically, maintain balance, interact with its environment, and combine locomotion with manipulation. This includes building the underlying learning-based motion primitives that can be composed into increasingly complex whole-body behaviors. You will work closely with robotics, controls, simulation, and machine learning engineers to turn learned behaviors into reliable capabilities running as part of the robot's real-time control stack.   WHAT YOU'LL DO - Design and train learning-based locomotion and whole-body control policies for dynamic robotic behaviors. - Develop motion primitives using different learning based generative models. - Apply reinforcement learning, imitation learning, and other learning-based approaches to motion generation and control. - Build scalable simulation, data generation, and training pipelines using platforms such as Isaac Lab and MuJoCo. - Develop methods for robustness, adaptation, and sim-to-real transfer, including domain randomization and learning from real-world robot data. - Deploy, evaluate, debug, and fine-tune learned policies on physical humanoid robots. - Optimize policy inference and training systems for the performance and latency requirements of real-time control. - Integrate learned policies into the broader robot control and autonomy stack.   WHAT WE'RE LOOKING FOR - BS, MS, or PhD in Robotics, Machine Learning, Computer Science, or a related technical field. - 3+ years of experience developing machine learning systems in industry or research. - Strong understanding of deep learning and modern policy architectures, including training, inference, experimentation, and debugging. - Hands-on experience with RL and at least one additional area such as imitation learning, generative models, sequence models, or large-scale representation learning. - Strong Python and PyTorch experience. - Experience with physics-based simulation environments such as Isaac Lab, Isaac Sim, MuJoCo, or similar platforms. - Ability to reason about learning algorithms in the context of dynamics, control, and physical systems. Nice to have: - Experience applying reinforcement learning or imitation learning to legged robots, humanoids, or other complex physical systems. - Experience with whole-body control, locomotion, motion imitation, or loco-manipulation. - Experience deploying learned policies on real robotic systems and debugging the sim-to-real gap. - Familiarity with motion capture, trajectory optimization, model-based control, or learning from demonstrations. - Experience training policies at scale across large numbers of simulated environments. - Publications at NeurIPS, ICML, ICLR, CoRL, RSS, CVPR, or equivalent contributions to impactful open-source robotics or machine learning projects.   WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: United States; Canada Workplace: OnSite 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 Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities - Build and maintain data pipelines for SFT, preference, and RL post-training data. - Own dataset quality, versioning, and reproducibility. - Turn research data recipes into production-grade, reusable components. - Scale model inference for data generation and model-based grading. - Design data formats and schemas that keep post-training datasets consistent and efficient to train on. - Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications - Strong software engineering skills. - Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. - Track record of running distributed data processing and model inference at scale. - Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour. - Excellent communication skills. This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere   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: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable technology collects rich physiological data, providing members with actionable insights into their recovery, training, and sleep. We are seeking a Senior Sensor Algorithm Engineer to develop and deploy algorithms for physiological sensors including optical sensor and inertial measurement unit (IMU) data into accurate, reliable, and real-time insights on WHOOP devices. This hands-on role centers on digital and statistical signal processing, sensor fusion, and model-based state estimation, with a particular focus on accelerometer and gyroscope data. You will own algorithm development from sensor characterization, mathematical modeling, and Python prototyping through efficient C/C++ implementation, firmware integration, and production validation. Working closely with Firmware, Hardware, Data Science, and Product, you will deliver robust on-device algorithms that perform reliably across diverse members and real-world conditions while meeting the constraints of wearable hardware. RESPONSIBILITIES - Design and develop real-time signal processing and sensor fusion algorithms that combine Sensor measurements inputs to characterize motion and deliver reliable member-facing insights. - Develop and tune model-based estimators for orientation and motion, including sensor bias estimation, uncertainty propagation, and drift mitigation under changing movement and sensing conditions. - Build robust IMU processing pipelines, including filtering, calibration, time synchronization, resampling, coordinate transformations, and compensation for sensor noise and systematic errors. - Analyze large-scale, noisy wearable datasets to identify failure modes and improve robustness across motion patterns, device orientation, fit, and individual movement characteristics. - Translate algorithm prototypes into production-ready C/C++ implementations, balancing accuracy with power, memory, compute, numerical stability, and latency. - Partner with Firmware and Hardware teams on sensor configuration, sampling strategies, and on-device integration; investigate differences between prototype behavior and performance on target hardware. - Define performance metrics and rigorous validation plans using reference measurements, controlled experiments, real-world data, and on-device testing to assess accuracy, robustness, and long-duration stability. - Own technical decisions for complex algorithm components, contribute to design and code reviews, mentor teammates, and collaborate across functions to investigate post-deployment issues and drive continuous improvement. QUALIFICATIONS - 5+ years of experience developing and deploying signal processing, sensor fusion, or state-estimation algorithms for real-world sensor applications, including substantial hands-on work with IMU data. - MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics, or a related quantitative field, or equivalent practical experience. - Strong foundation in digital and statistical signal processing, including filtering, spectral analysis, stochastic processes, and sensor noise characterization. - Demonstrated experience with accelerometer and gyroscope processing, IMU calibration, sensor error modeling, bias estimation, and drift management. - Strong experience with Kalman filtering, including extended or error-state formulations, and model-based sensor fusion; practical understanding of nonlinear estimation, uncertainty propagation, and estimator failure modes. - Practical knowledge of 3D motion and orientation representations, including coordinate frames, rotation matrices, quaternions, and rigid-body kinematics. - Proficiency in Python for algorithm development, data analysis, and experimentation, and C/C++ for efficient embedded implementation; demonstrated experience deploying algorithms to resource-constrained hardware. - Ability to independently investigate complex algorithmic problems, design rigorous validation experiments, and communicate technical tradeoffs with firmware, hardware, and cross-functional partners. - Experience with body-worn sensors, human-motion modeling, motion segmentation, or periodicity analysis is highly desirable. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-Verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Location: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE We are looking for a backend-leaning full-stack engineer to help build the next generation of Creative Agents at ElevenLabs. Our ambition is to make agents a primary way people create across ElevenCreative. We are building systems that turn ideas into high-quality audio, image and video, bringing models and creative tools together without requiring users to become prompting experts. The creative agent is already live. You will join a small team shaping its capabilities and architecture, with ownership from backend systems and agent infrastructure through to the customer-facing experience. You will help discover what works, turn experiments into reliable features, and use real customer feedback to guide what we build next. Your responsibilities will include: - Building production agents and expanding their capabilities through prompts, tool use, orchestration, new models and MCP integrations. - Designing and operating reliable backend systems for asynchronous creative generation and long-running tasks, with strong performance, observability, scalability and security. - Developing shared evaluations and live quality monitoring, including model-based assessment of image and video outputs. - Owning features end to end, from identifying user needs and prototyping to shipping across the stack and supporting them in production, alongside product, design and engineering. You will help shape both what the agent can do and how people use it across ElevenCreative. The work combines substantial greenfield development with improving and operating a live product. REQUIREMENTS We care about evidence of exceptional engineering: products you have shipped, difficult problems you have solved, and systems you have owned. We are looking for: - Strong backend engineering skills, experience operating production systems, and sound fundamentals in APIs, cloud infrastructure, storage and asynchronous processing. - Hands-on experience developing agents, with an understanding of prompts, tools, execution logic, evaluations and the challenges of reliable, secure operation. - Evidence of independent, end-to-end ownership and confidence working across the stack, including frontend delivery when needed. - Good product judgement, clear communication and enthusiasm for creative agents. We may also consider exceptional engineers with closely relevant experience. Familiarity with HTTP, WebSockets and asynchronous workers will help you build reliable communication between services and recover from failures. Experience with multimodal generation, creative editors, MCP, or building products in a small, fast-moving team would be particularly valuable. Location: This role is remote and can be executed globally. If you prefer, you can work from our offices in London, New York, San Francisco, and Warsaw.   #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Location: Bangalore, India GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Staff Data Analyst, you'll turn raw data into actionable insights that inform strategic decisions across GitLab's global Support Engineering organization. You'll design dashboards, reports, and data models that help leaders monitor performance, optimize costs, and improve customer outcomes. You'll also promote data innovation by experimenting thoughtfully and working through complex problems. What you'll do Own annual operating plan and capacity planning through data modeling and validation that support workforce and budget decisions. Build and maintain utilization and team-performance scorecards, including automated alerting that surfaces trends in real time. Analyze Support Economics, including cost-per-ticket modeling, self-service savings, and product quality costs. Develop performance indexes and heatmaps that identify product areas and customers using the most support resources. Lead dashboarding for AI adoption and return on investment, measuring the business impact of AI-driven initiatives across Support Engineering. Partner with go-to-market teams on predictive analytics and churn-prevention models that identify at-risk customers. Define and refine unified customer-schema requirements to create consistent data across systems and a single source of truth. Deliver Monthly Business Review telemetry, executive-ready reporting packages, recurring operational reports, and ad hoc analysis. What you'll bring Experience as a business intelligence analyst, analytics engineer, or in a similar data role, ideally in a software as a service or technology company. Experience partnering with Technical Support, Business Operations, Product Engineering, or similar organizations. Fluency in SQL, including complex multi-table joins, grouping and aggregation, common table expressions, and conditional filters. Hands-on experience building dashboards and reports in Zendesk Explore, Tableau, Looker, or similar business intelligence tools. Translate ambiguous business questions into structured analytical frameworks. Present findings clearly to technical and non-technical stakeholders. Plan and prioritize work independently in a remote, cross-functional environment across time zones. You may also bring experience with large language model-based tools, artificial intelligence and machine learning workflows, durable data solutions, analytics frameworks, in-depth data analysis, or presenting to senior leaders and executives. About the team Our Support Engineering organization uses data to understand performance, improve customer outcomes, and improve operational practices. You'll partner across Support Engineering, go-to-market teams, Business Operations, and Product Engineering in an all-remote environment. How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Athens, Greece We currently have a vacancy for a Business Analyst in English, to offer his/her services as an expert who will be based in Greece . The work will be carried out remotely. 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 on site. Tasks: Analysis of the IT functional and non-functional requirements, according to the applicable methodology and toolset to be used; Collaborate with numerous stakeholders to ensure that their concerns, requirements, and contribution are included in the requirements specification document; Provide input on low level detail design issues and patterns; Analyze and define specifications linked to the integration with other applications and/or technological components; Work in collaboration with Enterprise Architect and Solution Architect to design models in a modelling tool based on predefined requirements. Requirements University degree in IT or relevant discipline, combined with minimum 6 years of relevant working experience in IT; Minimum 3 years of experience as a Business Analyst; Minimum 2 years of experience in Scrum or another agile framework; Substantial experience in Business and IT system analysis, and ability to translate business needs into IT requirements; Strong experience in the use of agile tools (JIRA, Confluence) and knowledge of the modelling tools (Sparx EA); Knowledge and experience in Scrum; Good knowledge of relational database systems; Ability to apply architectural principles to functional solutions and use of model-based representations to collect, aggregate or disaggregate complex and conflicting information about the business; Assistance in the testing, the technical documentation, the technical training, the deployment, the evaluation and the reporting; Provide training/coaching on analysis techniques; Excellent command of the English & Greek language. Benefits If you are seeking a career in an exciting and dynamic company, where you will offer your services as part of a team of a major European Institution, operating in an international, multilingual and multicultural environment where you can expect real chances to make a difference, please send us your detailed CV in English, quoting reference: (BA/10/2026). 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 Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). The company employs over 1000 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc or equivalent). We design and develop software applications using state-of-the-art technology. The group generates annual revenues in the range of EURO 40 million, with an EBITDA in the range of 20%. The value of our contract portfolio exceeds EURO 300 million. EUROPEAN DYNAMICS is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, 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 authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy.

Location: Strasbourg, France We currently have a vacancy for a Business Analyst in English, to offer his/her services as an expert who will be based in Strasbourg, France . 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 on site. Tasks: Analysis of the IT functional and non-functional requirements, according to the applicable methodology and toolset to be used; Collaborate with numerous stakeholders to ensure that their concerns, requirements, and contribution are included in the requirements specification document; Provide input on low level detail design issues and patterns; Analyze and define specifications linked to the integration with other applications and/or technological components; Work in collaboration with Enterprise Architect and Solution Architect to design models in a modelling tool based on predefined requirements. Requirements University degree in IT or relevant discipline, combined with minimum 6 years of relevant working experience in IT; Minimum 3 years of experience as a Business Analyst; Minimum 2 years of experience in modelling and UML; Experience in the use of modelling and design tools in Business or IT projects (ARIS, EA, etc.); Experience in applying architectural principles to functional solutions and use of model-based representations to collect, aggregate or disaggregate complex and conflicting information about the business; Experience with assistance in the testing, the technical documentation, the technical training, the deployment, the evaluation and the reporting; Good knowledge of relational database systems; Excellent command of the English language. Benefits If you are seeking a career in an exciting and dynamic company, where you will offer your services as part of a team of a major European Institution, operating in an international, multilingual and multicultural environment where you can expect real chances to make a difference, please send us your detailed CV in English, quoting reference: (L4/10/2026). 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 Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). The company employs over 1000 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc or equivalent). We design and develop software applications using state-of-the-art technology. The group generates annual revenues in the range of EURO 40 million, with an EBITDA in the range of 20%. The value of our contract portfolio exceeds EURO 300 million. EUROPEAN DYNAMICS is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, 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 authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy.

Anthropic Fellows Program is designed to foster AI research and engineering talent by providing funding and mentorship to promising technical talent regardless of previous experience. Fellows primarily use external infrastructure such as open-source models and public APIs to work on empirical projects aligned with Anthropic's research priorities, aiming to produce public outputs like paper submissions. The program runs multiple cohorts yearly with rolling application reviews, expecting a start in January 2027 but flexible start dates can be requested. The program includes 4 months of full-time research, direct mentorship from Anthropic researchers, access to a shared workspace, connection to the AI safety and security research community, a weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD plus benefits varying by country, and funding for compute (~$15k/month) and other research expenses. The interview process involves an initial application and reference check, technical assessments and interviews, and a research discussion. Applicants are encouraged to apply even if they do not meet every qualification, with emphasis on diversity and inclusion. There are two main fellow tracks: ML Systems & Performance Fellows: - Mentors include Alwin Peng and Zygi Straznickas. - Projects may involve building CPU simulators for accelerator workloads, adding backends for accelerators on open source projects, building on-demand infrastructure, and creating complex synthetic data or environment pipelines. - Candidates should have strong software engineering skills, experience with complex ML systems, ability to balance research and engineering rigor, comfort with large-scale distributed systems and high-performance computing, experience with training or evaluating large language models, and skills in analyzing and debugging model training. - Fluency in Python and full-time availability are required. Reinforcement Learning Fellows: - Mentors include Ruhua Jiang, Kaidi Cao, Sunny Duan, David Brandfonbrener, Colt Steele, Dino Distefano, and Will Williams. - Projects may include building model-based tools to understand and improve AI training data, research on generalization, creating RL environments to improve Claude models and safety-related tasks, and research and implementation of RL algorithms. - Candidate criteria are similar to ML Systems Fellows. Logistics: - Participants must have work authorization and be located in the US, UK, or Canada during the program. - Shared workspaces are available in San Francisco; remote participation is allowed in the UK, US, or Canada. - Visa sponsorship is not provided; candidates must have or obtain full-time work authorization independently. - The program duration is 4 months full-time, with possible extensions and flexibility for partial commitments. Additional notes: - No guarantee of full-time offers post-program, though strong performers may receive offers or continue impactful AI safety work elsewhere. - Anthropic's full-time role policies do not apply to the Fellows Program. - The company emphasizes collaborative, large-scale AI research with a focus on safety, interpretability, and steerability. - Candidates must be fluent in Python and able to commit full-time. - The program values diversity and encourages applications from underrepresented groups. - Safety advice is provided regarding recruitment communications. Apply at the provided link.

Задачи: — Разработка и масштабирование World Models: проектирование и обучение массивных 3D/видеотокенизаторов и бэкбонов на базе Diffusion Transformers (DiT), Flow Matching и других технологий. — Построение пайплайнов для распределённого обучения тяжёлых foundation-моделей на вычислительном кластере. — Обучение Model-Based RL (MBRL) и политик IL + RL внутри замороженной латентной симуляции World Model. — Интеграция вспомогательных лоссов для perception-задач 3D-детекции, сегментации, трекинга. — Создание надёжного safety-контура поверх выходов модели и подготовка конструкции к реалтайм-инференсу на edge-девайсах робота. Требования: — Экспертное владение JAX и PyTorch. — Навыки масштабного распределённого обучения. — Глубокая математическая и ML-база. — Умение писать, генерировать и проверять быстрый оптимизированный код. Будет плюсом: — Опыт работы с Vision Foundation Models, генеративными видео- и image-моделями, синтезом лидарных облаков. — Опыт в Reinforcement Learning. — Опыт продвинутой квантизации тяжёлых трансформеров или диффузионных моделей для edge-девайсов. — Оптимизация инференса на борту робота. — Бэкграунд в Autonomous Driving, Motion Planning или Robotics. Условия: — Возможность обучения и компенсация 50% стоимости курсов по языку. — Другие бонусы, полный список которых доступен на сайте компании.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are seeking a Senior Systems Engineer – Software & Autonomy to support the definition, architecture, integration, and verification of the software systems that enable our humanoid robotic platform. The role will work across perception, localisation, navigation, artificial intelligence, motion planning, controls, ROS 2 platform software, simulation, deployment, and diagnostics. You will collaborate with software leads and subject matter experts to translate product and operational needs into coherent capabilities, requirements, architectures, interfaces, integration plans, and verification criteria. This is a systems engineering position focused on the robot’s software and autonomy stack. It is not primarily a firmware development or electrical engineering role. WHAT YOU'LL DO - Obtain input from system leaders, product teams, and technical subject matter experts to translate stakeholder needs into clear and verifiable system and software requirements. - Define the software capabilities required to support humanoid robot behaviours, operational use cases, and product objectives. - Decompose system-level capabilities across perception, navigation, AI, planning, controls, core platform, and supporting software services. - Develop and maintain the functional and logical architecture of the robot’s software and autonomy stack. - Define system boundaries, responsibilities, dependencies, and interfaces between software components and technical teams. - Establish interface requirements covering data ownership, message definitions, coordinate frames, units, timing, latency, synchronization, quality indicators, fault handling, and degraded operation. - Support architectural decisions involving, middleware, compute allocation, networking, simulation, software deployment, and distributed execution. - Coordinate integration across perception, navigation, AI, controls, platform software, firmware, electronics, sensors, actuators, and mechanical systems. - Identify cross-team assumptions, dependencies, architectural conflicts, and missing functionality before they become late-stage integration issues. - Define integration stages, entry and exit criteria, required test environments, and readiness expectations. - Lead or support the investigation of complex system-level issues involving multiple software components or interactions between software and hardware. - Define nominal, degraded, recovery, fallback, and safe-state behaviours for software-intensive functions. - Develop system-level verification and validation strategies for autonomous robotic capabilities. - Establish measurable performance and acceptance criteria for perception, localization, navigation, planning, controls, AI, and integrated robot behaviours. - Support scenario-based testing using simulation, software-in-the-loop, hardware-in-the-loop, laboratory testing, and physical robot testing. - Maintain traceability between use cases, requirements, architecture, implementation, tests, and verification evidence. - Work with safety engineers to ensure software behaviours support system safety requirements and hazard mitigations. - Facilitate requirement, architecture, interface, integration, and system-readiness reviews. - Communicate technical risks, capability limitations, integration status, and architectural trade-offs to engineering and program leadership. - Coach engineering teams in practical systems engineering methods appropriate for an iterative robotics development environment. WHAT WE'RE LOOKING FOR - Bachelor’s or Master’s degree in Systems Engineering, Software Engineering, Computer Science, Robotics, Mechatronics, Controls Engineering, or a related field. - Five or more years of experience in systems engineering, robotics software, software architecture, autonomous systems, or a related technical domain. - Experience working with complex software-intensive or cyber-physical systems composed of multiple interacting subsystems. - Strong knowledge of requirements engineering, architecture definition, interface management, integration, verification, validation, and traceability. - Technical experience in several of the following areas: - ROS or ROS 2 - Robotics software - Perception and sensor fusion - Localization, mapping, and navigation - Motion or behaviour planning - Manipulation, locomotion, or whole-body controls - Artificial intelligence or machine learning - Simulation and virtual testing - Distributed or real-time software systems - Ability to understand and evaluate software behaviour without being the primary implementation owner for every component. - Experience defining measurable acceptance criteria for complex system behaviours. - Ability to investigate issues spanning algorithms, software, computing, networking, firmware, sensors, actuators, and physical robot behaviour. - Strong analytical, problem-solving, leadership, and technical communication skills. Experience with humanoid robots, mobile robots, autonomous vehicles, industrial robotics, or similar systems. - Familiarity with ROS 2 topics, services, actions, quality-of-service policies, lifecycle management, TF, rosbag, and distributed execution. - Familiarity with C++, Python, Linux, Git, CI/CD, containers, and modern software development workflows. - Experience with simulation tools such as Isaac Sim, Gazebo, MuJoCo, MATLAB/Simulink, or equivalent platforms. - Experience with SysML, model-based systems engineering, or software architecture modelling. - Familiarity with functional safety, SOTIF, machinery safety, cybersecurity, or safety assurance for autonomous systems. - Understanding of machine-learning performance, uncertainty, dataset coverage, and scenario-based validation. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on GitLab's Nonlinear Productivity team, you'll find and remove friction across the software development lifecycle using reliable AI-powered automation — diagnosing problems like long review cycles, manual release steps, and brittle automation, then building the automation and process changes that resolve them for good. Some examples of the problems this team takes on: Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions. Turning a manual, error-prone release step into an agentic workflow that catches its own mistakes before a human ever has to. What you'll do Identify sources of friction across GitLab's software development lifecycle and scope agentic solutions to address them, turning vague pain points into concrete, buildable proposals. Design and build reliable AI-powered systems that follow step-by-step workflows, use tools and safety checks, and correct errors before taking engineering action — the kind of output you can actually trust with real engineering decisions. Build and maintain evaluation tools that judge agent output on correctness, constraint compliance, and cost, not on whether it merely "seems to work." Work across GitLab's codebase as each problem requires, going wherever the friction actually is rather than staying inside one service or product area. Apply distributed systems judgment to identify generated code that may fail under concurrency, at scale, or across self-managed, dedicated, and multi-tenant deployments, catching failures before they reach customers. Collaborate with the India-based group, sharing roadmaps, findings, and reusable agent tooling Take ownership of a greenfield problem space from day one, helping shape a proven internal fix into a capability GitLab could offer customers externally, with your scope and impact free to grow as the team scales. What you'll bring Hands-on experience building agentic or large language model-based systems — multi-step orchestration, tool use, guardrails, and recovery patterns — and making them reliable in production, not treated as one-off prompts or demonstrations. A track record of working autonomously in unfamiliar codebases, getting oriented quickly, and driving solutions through completion. Strong distributed systems knowledge, including coordination, consistency, idempotency, rate limiting, failure modes, and degradation under load. Proficiency in Go, Rust, or Python, in that order of team priority, and the ability to read and modify code in the other languages. Helpful experience includes shipping autonomous agents that complete real tasks from start to finish; improving build systems, release processes, review workflows, or other parts of the software development lifecycle; and working with globally distributed teams, large language model workload costs, or production constraints across on-premises, air-gapped, single-tenant, and software-as-a-service deployments. About the team Nonlinear Productivity — shortened internally to "NLP," with no relation to natural language processing — is one of GitLab's newest teams: a strategic incubation group that reports into AI Platform leadership under the direct sponsorship of the CTO. It's split into a US group (this role) and an India-based group working the same charter; the two sync on roadmap and tooling a few times a week but otherwise run day to day on their own. It operates like a startup — no dedicated product manager, no pre-set backlog — and solutions that prove out internally are the team's path to a monetized, customer-facing GitLab offering. It's a good fit for engineers who'd rather go find the next problem than be handed one, and who want a hand in defining a brand-new part of GitLab from its first commit. Remote-Global The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $139,200 — $235,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. OUR MISSION At Humanoid we strive to create the world's leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity. ABOUT THE ROLE As a Research Engineer on the World Models team, you will build action-conditioned generative models that predict how the world evolves around our robots — future video, proprioception, contacts, and outcomes — from past observations and actions. World models serve four purposes in our stack: a pretrained, physics-aware prior for our VLA policies; an engine for rare data collection, cross-platform transfer, and sim-to-real transfer; a testbed for policy evaluation and testing before hardware; and a future-prediction rollout engine that surfaces what our policies intend to do, for safety and planning. This is a hands-on individual contributor role: you will design architectures, run large training jobs, and validate your models against real fleet data from industrial deployments. WHAT YOU'LL DO - Design and train multimodal world models — video, state, action, and language — using diffusion-based and transformer architectures. - Build action-conditioned video prediction and dynamics models that stay physically consistent over long horizons, including contact-rich manipulation, and serve as pretrained priors for VLA policies. - Develop learned-simulator evaluation: score candidate policies offline, predict real-world success rates before deployment, and roll out policy futures to expose intended behaviour for safety review and planning. - Generate synthetic rollouts and counterfactual experience — including rare events, cross-platform transfer, and sim-to-real transfer — to augment policy training, and measure their effect on downstream task performance. - Establish fidelity metrics and calibration protocols that quantify where the world model can be trusted and where it diverges from reality. - Build data pipelines that turn fleet telemetry, teleoperation logs, and internet-scale video into training corpora for world models. - Run scaling and ablation studies on architecture, data mixture, and context length; communicate findings crisply. - Collaborate with pretraining, RL, and manipulation teams to integrate world models into policy training and evaluation loops. WHAT WE'RE LOOKING FOR - A track record of training large generative models — video, world, or multimodal — with shipped models or published artifacts to show for it. - Deep hands-on experience with modern generative architectures: diffusion models, autoregressive transformers, latent-variable models, or video prediction. - Experience with large-scale distributed training: streaming datasets, checkpointing and state management, debugging numerics and training instabilities. - Strong Python + PyTorch/JAX; you can profile kernels, optimize data loaders, and write maintainable research code. - Empirical rigor: you design careful evaluations, run honest baselines, and document experiments clearly. - Excitement about grounding generative models in physical reality rather than pixels alone. NICE TO HAVE - Experience with world models for robotics or autonomous driving (e.g., action-conditioned video models, learned simulators, model-based RL). - Familiarity with robotics simulators (Isaac Sim, MuJoCo) and sim-to-real considerations. - Experience using world models for policy evaluation or synthetic data generation at scale. - Publications at top-tier deep learning conferences (NeurIPS, ICML, ICLR, CoRL, CVPR) or equivalent open-source contributions. - Experience optimizing generative models for fast inference. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.