• Generate AI images for 4 jewelry collections using Midjourney v6+ and/or Stable Diffusion • Strictly follow our 7 visual pillars: absolute black/gold contrast · warm golden hour lighting · ultra-pronounced bokeh · precise model expressions · black gloves signature · tight fashion editorial framing · glowing skin • Deliver images in portrait ratio 3:4 or 4:5, maximum quality (8K prompt quality) • Self-validate each image against our 15-point checklist before delivery • Perform light post-production adjustments when needed (contrast, warm tones, gold luminosity) • Communicate clearly in English and iterate quickly on feedback

We are looking to hire ambitious entrepreneurs to start and scale their own startups. We are serial entrepreneurs, for example Paul Müller (founder Adjust, €1.2B exit) and Petter Made (founder SumUp, €8B) who are eager to support outlier personalities and serial entrepreneurs to build €1B+ companies. Our offer: - A salary while you build your startup as you will directly be employed by us. Alternatively, you can opt for up to €500k in funding. - 1:1 sparring with unicorn founders on a weekly basis - Community: Access to the top 0.1% of founders, peers and investors - Team building: Hiring top notch talent supported through our network (over 50,000 professionals) - Distribution: Support in reaching product-market-fit and building up a sales force / marketing machine - Funding support for securing a multi-million euro funding round within 12 months (on average, EWOR Fellows raise > €2M after our Grand Pitch) One of our fellows set a record for Europe’s largest pre-seed round by a first-time founder, securing a €12M pre-seed investment. Tasks - You will own, build, and run your startup in fields such as Computer Vision - You will embark on an extensive personal development journey crafted by unicorn founders and follow a fully customised programme enhancing your goal, time, and energy management - You will receive support in hiring through our network to over 50,000 professionals and advice as well as best practices from serial entrepreneurs - You will receive intensive coaching to make your startup ready to raise millions in funding - You will iterate your product with us until having reached product-market-fit and receive support in building up a sales force or creating a marketing engine respectively Requirements - You are based in Europe or the Americas or open to relocate - You are willing to take full responsibility for your own startup and scale it to €100M+ in revenues - You have excellent communication skills in the English language

Who we are: Glydways is reimagining what public transit can be. We believe that mobility is the gateway to opportunity—connecting people to housing, education, employment, commerce, and care. By making transportation more accessible, affordable, and sustainable, we empower communities to thrive and unlock economic and social prosperity. Our mission is to revolutionize transit with a solution that delivers high capacity, exceptional user experiences, unmatched affordability, and minimal environmental impact. The Glydways system is a groundbreaking network of carbon-neutral, interconnected transit pathways powered by standardized autonomous vehicles on dedicated roadways. Operating 24/7 with on-demand access, it offers personalized and efficient mobility—without the burden of heavy upfront infrastructure costs or ongoing taxpayer subsidies. With Glydways, we’re building more than a transportation system; we’re creating a future where everyone, everywhere, has the freedom to move. Meet the team: The Glydways perception team is responsible for designing and implementing a perception system that includes data fusion from state-of-the-art sensors (e.g., LIDAR, RADAR, High definition cameras, Ultra-wide-band radios, etc.) and robust detection, classification, and tracking of any and all obstacles that could present a hazard to the vehicle (Glydcars) in the system. The perception system for Glydways will reason about information from each Glydcar and from regularly spaced sensor pods monitoring the road network. The perception team plays a vital role within the Autonomy Software engineering team. The team’s deliverables include: - Documenting a detailed design for enacting a safe system that can be certified by public transportation authorities. - Implementing said design on mature prototype vehicles in demonstrations to customers, potential customers, and investors. - Expanding the design to include fail-operational capabilities that extend the overall system to safely give our customers a more comfortable experience. - Managing data collection, autonomy testing, and milestone demonstration events that showcase the system’s maturing capabilities, leading to a production system. Team members may work remotely and must be self-motivated. Roles & Responsibilities: - Implement and own perception algorithms spanning detection, classification, sensor fusion, and multi-object tracking using both ML-based and classical methods - Develop end-to-end perception pipelines from raw sensor input (camera, LiDAR, radar) to structured scene understanding outputs consumed by downstream autonomy modules - Develop and maintain simulation, log-replay, visualization, and offline analysis workflows to maximize test coverage and accelerate validation prior to on-vehicle deployment - Build tooling and infrastructure for dataset management, model training, evaluation, and deployment at scale Knowledge, Skills and Abilities: - Expertise with perception algorithms as shown with academic and/or professional experience - Proficient at translating perception algorithms into production quality C++ (C++14 or newer) code - Strong debugging skills across distributed and asynchronous pipelines, using logs and metrics to drive root-cause analysis. - Excellent verbal and written communication skills Glydways provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking highly motivated MSc or PhD interns to work on video generation and multimodal video foundation models. Interns will focus on one or more components of the foundation model lifecycle and are encouraged to propose creative, research-driven ideas that advance the state of the art. - Contribute to the development and improvement of open-source video foundation models. - Analyze limitations and design scalable solutions. - This is a research-focused internship with opportunities to publish at top-tier computer vision and machine learning conferences. - Work with petabyte-scale video datasets and large distributed GPU clusters with thousands of GPUs. Responsibilities - Research and improve open-source video and multimodal video generation foundation models. - Focus on one or more areas such as: - Pre-training - Supervised fine-tuning - Post-training - Inference - Architecture design - Evaluation - Benchmark models against current state-of-the-art, identify bottlenecks, and propose novel improvements. - Work with large-scale video datasets and distributed training systems. - Collaborate with researchers and engineers on projects with clear research and publication potential. Qualifications - MSc or PhD candidate in Computer Science, Machine Learning, Computer Vision, or a related technical field. - Research topic or experience in image generation, video generation, or multimodal learning. - Awareness of open-source video foundation models and their current limitations. - Proficiency with PyTorch and modern deep learning workflows. - Strong analytical thinking, creativity, and collaboration skills. - Prior first-author related publications in CVPR, ICCV, ECCV, NeurIPS, or ICLR. Preferred Qualifications - Demonstrated related work, such as research codebase or benchmarks released on GitHub or similar platforms. - Experience with large-scale or distributed training. - Hands-on experience with diffusion-based, transformer-based, or hybrid video generation models. Important Information for Candidates - Apply only through our official channels. - We do not use third-party platforms or agencies for recruitment unless clearly stated. - Verify the recruiter’s identity through verified LinkedIn profiles. - Be cautious of unusual communication methods; we do not conduct interviews over WhatsApp, Telegram, or SMS. - Double-check email addresses; all communication will come from emails ending in @tether.to or @tether.io. - We will never request payment or financial details. Team AI Research