Machine Learning Engineer at Destinus Group | Zürich

Duration: Minimum 6 months; ideally 9–12 months, depending on the candidate’s experience.At Scandit, we empower individuals with cutting-edge technology. Whether it’s accelerating delivery routes for drivers, ensuring patients receive the correct medications, or streamlining retail operations, our solutions transform workflows and yield actionable insights across diverse sectors. Join us as we innovate, expand, and elevate Scandit to new heights.About the InternshipThis research-oriented internship is designed to propel advancements in machine learning techniques for intricate visual understanding tasks. You will engage in projects that focus on deep learning frameworks for image-to-sequence modeling, including Transformers and attention mechanisms, to tackle complex and highly structured computer vision challenges. Your contributions will play a crucial role in our long-term research initiatives targeting enhanced performance, robustness, and generalization in large-scale visual applications.Your ResponsibilitiesCollaborating closely with seasoned ML researchers and engineers, you will be at the forefront of groundbreaking research that intersects computer vision and sequence modeling. Your key responsibilities will include:Designing and testing innovative ML architectures for structured visual data.Assessing various modeling paradigms, including encoder-decoder frameworks and hybrid Transformer models.Exploring methods to enhance robustness, generalization, and multi-view reasoning capabilities.Conducting systematic experiments, ablation studies, and error analyses to substantiate your research hypotheses.This internship offers a unique opportunity for original model development, extensive experimentation, and impactful scholarly work. You will help drive technological innovation with potential real-world implications for millions of users, making this position ideal for master’s students, PhD candidates, or those aspiring for research careers in academia or industry.Your ProfileYou are a Master's or PhD student in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline, with a strong emphasis on research. You possess a solid understanding of machine learning theory, neural networks, and computer vision.Key Skills:Expertise in Python and deep learning frameworks such as PyTorch.Hands-on experience in designing, training, and evaluating neural networks, including CNNs and Transformer architectures.Exceptional analytical and problem-solving skills, with the ability to tackle complex challenges.

At Scandit, we empower individuals with cutting-edge technology that transforms everyday tasks into efficient workflows. Our innovative solutions enhance operational efficiency across various sectors, enabling quicker deliveries, accurate medication matching, and streamlined retail operations. Join us in our mission to elevate Scandit to new heights through continuous growth and innovation. About the Internship We are seeking enthusiastic students who are passionate about computer vision and machine learning to become part of our Zürich team for a duration of four to six months. As an intern, you will contribute to product development by improving and extending algorithms and their automated testing infrastructure. This internship presents an exceptional opportunity to apply your academic knowledge while gaining valuable hands-on experience in a collaborative international environment. What You Will Do Depending on your background and interests, you may work on a variety of exciting projects, including: Refining barcode scanning algorithms to perform effectively in challenging conditions such as deformed surfaces, glare, or reflections. Enhancing our real-time visual tracking and pose estimation systems by integrating advanced sensor measurements and state-of-the-art machine learning algorithms. Improving our object and context detection capabilities through the development and integration of cutting-edge machine learning techniques. Advancing our real-time visualization systems to facilitate the analysis and development of our computer vision algorithms. Streamlining our image annotation tools by implementing intelligent algorithms to reduce manual efforts. Creating features for image classification, matching, and reconstruction to enhance our algorithms for monitoring shelf and product conditions in supermarkets. Our Tech Stack Computer vision algorithms: C++17, CMake Machine learning training and tools, cloud processing: Python, Pytorch Acceleration: SIMD, Vulkan, CoreML

About GenPeach AIGenPeach AI is a pioneering research lab dedicated to developing vertical multimodal foundation models aimed at creating hyper-realistic human representations in images and videos. Our mission is to empower human creativity through advanced AI tools rather than replace it.We build our models from the ground up, utilizing proprietary datasets at an expansive scale, innovative architectures and training methodologies, extensive GPU resources, and seamless product integration to expedite the delivery of our research to end users.Our team consists of approximately 10 highly skilled professionals, guided by advisors from Google DeepMind and supported by prominent AI-focused investors and advisors from OpenAI, Meta AI, Microsoft AI, Project Prometheus, and Fal. Collectively, our team and advisors have significantly contributed to groundbreaking models such as Meta’s Imagine/MovieGen, OpenAI’s Sora, Google’s Veo, and Gemini.About the TeamYou will become a key member of the research team, focused on advancing image/video generation and multimodal understanding. Collaborating closely with fellow Research Engineers, Scientists, and Founders, you will transform innovative research into scalable training processes, robust evaluations, and production-ready systems.About the RoleWe are seeking an AI Research Engineer to contribute to the end-to-end development and scaling of GenPeach’s foundational models. Your responsibilities will include the implementation of new model concepts and training methodologies, managing critical aspects of the training stack that influence quality and efficiency, and navigating production constraints.This role is hands-on with a high degree of ownership, where you will write research-quality code that is vital for production.In this role, you willDevelop and refine image/video generative model concepts (architecture, loss functions, conditioning, sampling, distillation, post-training adjustments)Oversee training performance comprehensively (distributed training, throughput, memory management, stability, debugging scaling issues)Establish and enhance the experimental workflow (evaluations, ablation studies, reproducibility tools, reporting, decision-making processes)Create and optimize VLMs for image/video captioning (data preparation, training strategies, model variations, evaluation)Conduct high-frequency research: review literature as needed, implement concepts, and validate findings empirically

About GenPeach AIGenPeach AI is an innovative research lab focused on developing cutting-edge multimodal foundation models aimed at hyper-realistic human generation in both image and video formats. Our mission is to cultivate tools that enhance human creativity rather than replace it.We specialize in training models from the ground up, leveraging proprietary datasets at a massive scale, pioneering architectures, and custom training methodologies. We utilize extensive GPU clusters and ensure swift product integration so that our research reaches users quickly.Our technical team, consisting of around 10 experts, is guided by Directors from Google DeepMind and supported by premier AI-focused funds and influential angel investors from OpenAI, Meta AI, Microsoft AI, Project Prometheus, and Fal. Together, our team, advisors, and investors have contributed to significant models such as Meta’s Imagine/MovieGen and foundational model work that supports OpenAI’s Sora, as well as Google’s Veo and Gemini.About the RoleWe are seeking a distinguished AI Research Scientist to spearhead the next evolution of GenPeach AI foundation models. This role is categorized as a Leadership Individual Contributor, where you will influence research direction through practical experimentation, guide technical strategy across the entire stack, and mentor a select group of researchers while collaborating closely with the founding team.This position transcends mere fine-tuning of existing models; it involves constructing new capabilities through innovative architecture work, training systems, and post-training methodologies—culminating in their deployment into a production environment.Key ResponsibilitiesCollaborate in designing and training large-scale diffusion models for advanced image and video generation.Develop and refine training recipes (including pretraining, post-training, control, and preference tuning) to unlock enhanced model functionalities.Conduct rigorous ablation studies: discern effective strategies, understand their mechanisms, and communicate findings clearly to guide roadmap decisions.Evaluate speed/quality/cost trade-offs and make informed technical decisions that significantly impact training efficiency and production quality.Contribute to dataset strategy: focus on curation signals, filtering, evaluations, and feedback loops from product performance.Work in tandem with engineering and product teams to transition research into production (addressing serving constraints, stability, monitoring, and rapid iteration).Guide and elevate the skills of a small team of researchers through code reviews and maintaining research standards.

Role Overview Destinus Group is seeking a Computer Vision Engineer in Zürich to advance the intelligence of autonomous flight systems. This role focuses on improving the precision, reliability, and adaptability of AI-powered aviation products used in real-world scenarios. The work involves refining current algorithms and models as well as developing new approaches to help these systems perform in complex and demanding environments. About Destinus Group Destinus Group develops high-speed, autonomous flight technologies for defense applications. The company builds next-generation unmanned aerial systems designed for speed, accuracy, and efficiency, supporting governments and defense organizations in critical operations worldwide. This position is part of Daedalean AG, Destinus Group’s AI and autonomy hub. The team is responsible for creating safety-critical AI systems that connect advanced research with practical aviation needs. The work combines aerospace engineering with artificial intelligence to build the next generation of autonomous flight systems.

Join Us as a Senior Machine Learning Engineer (Computer Vision) At Scandit, we empower individuals with innovative technology that enhances efficiency across various industries. From optimizing delivery operations to ensuring accurate medication delivery, our solutions automate workflows and provide critical insights. Be part of our journey as we innovate and expand, taking Scandit to new heights. Role Overview We are seeking a talented Senior Machine Learning Engineer to join our Label Capture team. In this role, you will work on developing digital twins of intricate labels and identification documents, enhancing our existing product offerings by implementing new features and optimizing current functionalities. You will utilize cutting-edge computer vision and deep learning algorithms to significantly improve information extraction from printed materials, surpassing existing standards. If you are excited by these challenges, we want to hear from you! Key Responsibilities Lead the semantic document parsing initiatives for customer applications. Engage in all stages of quality enhancement, including metrics definition, prototyping, testing, model integration, and data analysis. Keep abreast of the latest developments in document classification, text recognition, and information extraction. Drive innovation by identifying areas for enhancing recognition capabilities. Mentor fellow engineers on code quality and best engineering practices. About You You are a seasoned ML engineer with a passion for designing, deploying, and refining machine learning systems. With over five years of experience, you have successfully delivered advanced computer vision solutions, both in cloud environments and on-device, from initial prototype to production. You understand that software development combines technology with human interaction, allowing you to thrive in both independent and collaborative settings. While you stay informed about emerging trends in CV/ML, you appreciate the value of established technologies and incremental improvements. Your creativity and determination drive you to tackle real-world challenges innovatively, and you excel at taking ownership and navigating obstacles efficiently. You possess a keen eye for detail, balancing precision with pragmatic approaches to achieve our objectives. If this resonates with you, we look forward to your application!

Intrinsic Robotics is at the forefront of redefining industrial robotics as part of Alphabet's innovative vision. We are committed to harnessing advances in AI, perception, and simulation to unlock new possibilities in the field of industrial robotics, with software and data at the heart of our solutions. Our mission is to make industrial robotics smarter, more accessible, and user-friendly for a diverse range of businesses, entrepreneurs, and developers. Our dynamic team consists of engineers, roboticists, designers, and technologists who are passionate about unleashing the creative and economic potential of industrial robotics. Role OverviewAs a Senior Research Scientist within our Applied Research team, you will spearhead applied research initiatives and design groundbreaking algorithms in geometric computer vision and image/video-centric foundation models tailored for scalable deployment in industrial robotics. Your expertise in Deep Learning will aid in defining processes and formulating strategies to reduce hallucination risks, enhance accuracy, and execute algorithms on industrial robotics workcells, thereby assessing the sim-to-real transfer of models. Additionally, you will guide the development of synthetic data and annotations essential for training foundation models, identifying gaps in the sim-to-real transfer process. Collaboration with research partners and interdisciplinary engineering teams will be crucial as we explore new methodologies and architectures to integrate cutting-edge foundation models into real-world industrial applications. Continuous learning and embracing unfamiliar technologies will be integral to your role. Your ImpactYour contributions will be pivotal in democratizing access to advanced AI capabilities within the robotics sector, boosting the reliability of deploying AI models at scale in industrial environments. Your day-to-day responsibilities will include: You will demonstrate insight and innovation, proactively identifying challenges and proposing practical solutions that can be implemented in high-throughput settings.You will act as a liaison between the robotics team and our research partners, collaborating effectively to provide engineering insights into research projects and conceptualize next-generation solutions. You will serve as an advisor to engineering and cross-functional teams, guiding them in translating early-stage AI research into robust engineering capabilities within Flowstate (Intrinsic’s robotics software platform).

At Skydio, the premier drone company in the US and a global leader in autonomous flight technology, we are shaping the future of drones and aerial mobility. Our team is composed of experts in artificial intelligence, innovative hardware and software development, operational excellence, and a strong commitment to customer satisfaction. We aim to broaden the accessibility of drone technology to a diverse range of users including utility inspectors, first responders, and military personnel.About the Position:The essence of our autonomy system lies in its ability to learn a semantic and geometric understanding of the world through visual data. We are at the forefront of developing real-time deep learning networks to advance intelligent mobile robotics. If you are passionate about utilizing vast structured video datasets to tackle challenges in Computer Vision (CV), such as object detection, tracking, optical flow estimation, and segmentation, we want to hear from you.As a Deep Learning Model Acceleration Engineer, you will play a pivotal role in constructing and scaling the infrastructure that underpins Skydio’s Deep Learning (DL) and AI initiatives. You will collaborate closely with our autonomy, embedded, and cloud teams to introduce new capabilities and support our deep learning efforts.Your Impact:Develop high-performance solutions for deep learning inference tailored to CV workloads, ensuring high throughput and low latency across various hardware platforms.Profile CV and Vision Language Models (VLMs) to assess performance, pinpoint bottlenecks, and discover optimization opportunities while enhancing the power efficiency of deep learning inference tasks.Design and implement comprehensive MLOps workflows for model deployment, monitoring, and retraining.Apply your advanced Machine Learning expertise to utilize training or runtime frameworks and model efficiency tools aimed at boosting system performance.Devise innovative methods to enhance training efficiency.Implement GPU kernels for custom architectures and optimized inference.Create SDKs enabling customers and external developers to construct autonomous workflows utilizing Machine Learning (ML).Leverage your knowledge and best practices to maintain and elevate Skydio’s engineering standards.Qualifications:Proven hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment.Strong foundational knowledge in deep learning frameworks and computer vision.Ability to work collaboratively in a fast-paced environment and manage multiple projects simultaneously.

Join Esri as a Research and Development Intern in Zurich, where you will have the opportunity to contribute to innovative projects that shape the future of geographic information systems. Work alongside expert teams and gain hands-on experience in cutting-edge technologies. This internship will provide you with invaluable insights into the R&D processes at a leading software company.

At Google DeepMind, we celebrate the richness of diverse experiences, knowledge, and backgrounds, leveraging these unique perspectives to achieve remarkable outcomes. Our commitment to equal employment opportunity extends to all individuals, irrespective of sex, race, religion, belief, ethnicity, nationality, disability, age, citizenship, marital status, sexual orientation, gender identity, pregnancy, or any other legally protected status. Should you require any accommodations due to a disability or other need, please feel free to inform us.SnapshotThe Gemini Safety team plays a crucial role in ensuring the safety and equitable behavior of Google DeepMind's most recent Gemini models. As a Research Scientist, you will apply and innovate data-driven and algorithmic solutions to enhance our latest user-facing models. This role thrives in a fast-paced, collaborative environment characterized by a strong culture of support and dedication.About UsAt Google DeepMind, we believe that artificial intelligence can be one of humanity’s most impactful inventions. Our team consists of scientists, engineers, and machine learning specialists working together to push the boundaries of AI technology for the benefit of the public and to facilitate scientific discovery. We prioritize safety and ethics in all our collaborations addressing critical challenges.The RoleWe seek a dynamic Research Scientist who excels in tackling new research questions and adeptly implementing innovative research concepts.Our team is focused on enhancing the safety and fairness of cutting-edge AI models, contributing foundational technologies that are integral to various product areas including Gemini App, Cloud API, and Search.Key Responsibilities:Post-training and instruction tuning of state-of-the-art large language models (LLMs), concentrating on text-to-text, image/video/audio-to-text modalities, and agentic capabilities.Investigate data, reasoning, and algorithmic solutions to ensure that Gemini Models are safe, maximally beneficial, and accessible to all.Enhance the adversarial robustness of Gemini, particularly in relation to high-stakes abuse risks.Design and uphold rigorous evaluation protocols to identify model behavior gaps and opportunities for safety and fairness improvements.Develop and implement experimental plans to address identified gaps or to create entirely new capabilities.Foster innovation and deepen understanding of safety in AI systems.

About Flexion Robotics:At Flexion Robotics, we are pioneering the intelligence framework that will drive the next generation of humanoid robots. Our overarching mission is to expedite the transformation from delicate prototypes to their practical application in real-world scenarios. Founded by preeminent scientists specializing in robot reinforcement learning, with backgrounds from Nvidia and ETH Zürich, we are supported by top-tier international venture capital firms. In just a few months, we've transitioned from our initial line of code to the deployment of tangible humanoid capabilities alongside our partners.The Role:We are seeking a highly skilled expert in whole-body motion generation and/or vision-conditioned generative models to enhance our team in Zurich. Drawing inspiration from the recent advancements in neural avatars and computer graphics, we strive to implement similar methodologies to generate comprehensive body movements for our humanoid robots. The primary objective of this role is to innovate and implement cutting-edge multimodal generative models for robot trajectory generation.

As a Senior Lead Computational Designer at On Running AG, you will spearhead innovative design initiatives that push the boundaries of technology and creativity. Collaborating closely with our multidisciplinary teams, you'll be at the forefront of developing cutting-edge solutions that enhance our product offerings and redefine user experiences. Your expertise will guide the design process, from conceptualization to execution, ensuring our designs are not only visually stunning but also functional and user-centric.

Skydio stands at the forefront of autonomous flight technology, redefining the future of drones and aerial mobility. As the leading US drone manufacturer, our team blends unrivaled expertise in artificial intelligence with top-tier hardware and software development, operational excellence, and a commitment to customer satisfaction. We empower a diverse range of drone users, from utility inspectors and first responders to military personnel on the battlefield and beyond.About the Role:At Skydio, our autonomy system relies on advanced semantic and geometric comprehension of the world through visual data. We are pushing the limits of real-time deep learning networks to enhance intelligent mobile robotics. If you are passionate about utilizing vast structured video datasets to tackle challenges in Computer Vision (CV), including object detection, tracking, optical flow estimation, and segmentation, we want to connect with you.As a Deep Learning Infrastructure Engineer, you will play a pivotal role in constructing and scaling the infrastructure that underpins Skydio’s Deep Learning (DL) and AI initiatives. Collaborating closely with our autonomy, embedded, and cloud teams, you will deliver innovative capabilities and support the deep learning team.Your Impact:Develop high-performance solutions for deep learning inference tailored to CV workloads, ensuring high throughput and low latency across various hardware platforms.Analyze the performance of CV and Vision Language Models (VLMs) to pinpoint bottlenecks and opportunities for optimization and enhanced power efficiency.Design and implement comprehensive MLOps workflows for model deployment, monitoring, and retraining processes.Apply your advanced machine learning knowledge to improve system performance through training or runtime frameworks and model efficiency tools.Innovate new methods to enhance training efficiency.Develop GPU kernels for custom architectures and optimized inference.Create SDKs that facilitate customer and external developer engagement in building autonomous workflows utilizing Machine Learning (ML).Utilize your expertise and adherence to best practices to uphold and enhance Skydio’s engineering standards.Qualifications:Hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment.Proficiency in deep learning frameworks and tools.Strong understanding of computer vision principles and practices.Excellent problem-solving skills and attention to detail.

Join our dynamic team at On Running AG as a Specialist in Anaplan Solution Architecture and Model Building. You will play a critical role in designing and implementing robust Anaplan models that drive strategic business decisions and enhance operational efficiency.

WHO WE AREAt Proxima Fusion, we are on a transformative journey to revolutionize sustainable energy. Our pioneering concept, centered around the advanced W7-X stellarator and cutting-edge technology, aims to create commercially viable fusion power plants.Our innovative work in stellarator optimization, enhanced by state-of-the-art computational tools and machine learning, is pushing the boundaries of fusion technology. We are unlocking new, high-performance design parameters through the application of high-temperature superconducting magnets.To seize this monumental opportunity, we are assembling a team of highly dedicated and passionate individuals committed to driving extraordinary advancements and radically transforming technology on a global scale.WHY JOIN PROXIMA FUSIONImpact: Your simulations will play a crucial role in shaping the magnets that support the future of commercial fusion energy.Ownership: As a member of a small, expert team, you will establish modeling standards and significantly influence key design decisions.Frontier Engineering: Engage at the cutting edge of high-field electromagnetics, cryogenics, and sophisticated numerical methods.Collaboration: Join forces with a team that combines profound superconducting expertise with advanced computational capabilities to tackle one of the most formidable engineering challenges of our era.YOUR IMPACTAt Proxima Fusion, we are pioneering the design of the first generation of fusion power plants to deliver clean, carbon-free energy to the world. The core of our reactor is its superconducting coils, which operate at cryogenic temperatures, generate intense magnetic fields, and must maintain stability amid complex electromagnetic and thermal transients.We are seeking a Numerical Modeling Engineer to create high-fidelity simulation tools that predict and mitigate the behavior of our superconducting magnets. Your work will encompass electromagnetic, thermal, and transient multiphysics modeling, including quench dynamics, and will directly inform the design choices for conductors, coils, and protection systems.This position emphasizes the creation of robust numerical frameworks, integrating commercial multiphysics tools with in-house developed models to enable prompt, reliable, physics-driven engineering decisions.

Join our innovative team at anybotics AG as an Electrical Engineering Intern. This is a unique opportunity to gain hands-on experience in the field of robotics and automation while contributing to cutting-edge projects. As an intern, you will work closely with experienced engineers and participate in the design, testing, and implementation of electrical systems in our robotic solutions.

Skydio stands at the forefront of drone technology as the leading US drone company and the global pioneer in autonomous flight—an essential aspect of the future of aerial mobility. Our team is comprised of experts in artificial intelligence, cutting-edge hardware and software development, operational excellence, and an unwavering commitment to customer satisfaction. We strive to empower a diverse range of drone users, from utility inspectors to first responders and beyond.About the Role:Our autonomy system relies on learning both semantic and geometric interpretations of the world through visual data. We are challenging the limits of real-time deep networks to enhance the capabilities of intelligent aerial robots, enabling them to autonomously navigate uncharted environments and deliver significant operational benefits. If you are passionate about applying deep learning in real-world scenarios and tackling complex issues in computer vision and autonomy, we would be thrilled to connect with you.In the role of Deep Learning Engineer, you will focus on training and deploying optimized models to tackle difficult challenges such as optical flow estimation, stereo depth estimation, object detection, segmentation and tracking, visual place recognition, localization and mapping, few-shot learning, occupancy networks, automated path planning, and more.Your Impact:Design, implement, and deploy advanced computer vision and multimodal deep learning models for Skydio's autonomy system.Utilize extensive real-world video and sensor data for data mining, curation, labeling, training, and evaluation.Employ large-scale and diverse synthetic data to enhance deep learning algorithms.Utilize state-of-the-art foundation models for knowledge distillation and efficient learning.Optimize models for low-latency performance on embedded hardware.Develop evaluation benchmarks and metrics to assess the performance of autonomous systems.Act as a versatile team member, contributing across various software aspects as needed.Qualifications:M.S. or Ph.D. in Computer Science, Electrical Engineering, or a related field.Proven hands-on experience in designing, training, and deploying deep learning models.Ability to produce high-quality, well-architected code (Python/PyTorch preferred).

The Product Creation Academy at On Running AG offers a two-year rotational program in Zurich for those interested in building a career in footwear engineering. This program centers on developing hands-on skills and gaining direct experience within the sportswear industry. Program Structure Engage in specialized rotations across core areas of footwear engineering Spend time in Vietnam to observe the product realization process firsthand Receive mentorship from experienced leaders throughout the program Key Details Location: Zurich, with a rotation in Vietnam Duration: Two years Start Date: September 1, 2026 Application Process Applications are open for a limited period due to high demand. Early submission is recommended.

Skydio builds autonomous flight technology for drones used in fields like utilities, public safety, and defense. The Zurich team blends artificial intelligence with hardware and software development, delivering smart aerial systems for real-world missions. Skydio drones support a range of professionals, including utility inspectors, first responders, and soldiers in tactical scenarios. Internship focus This Autonomy Engineer Intern position centers on deep learning for computational photography in autonomous drones. Skydio’s autonomy system relies on advanced semantic and geometric understanding, using high-quality visual data. The Zurich team develops real-time deep learning networks that help drones navigate new environments and deliver valuable data for inspection, mapping, ISR, and public safety tasks. Interns will contribute to computational photography models and algorithms, aiming to improve camera performance and support a variety of drone missions. The work spans imaging, computer vision, and autonomy, applying deep learning to practical scenarios. What you will do Design, implement, and deploy deep learning models for computational photography, including super-resolution, multi-frame denoising, low-light imaging, and HDR imaging. Handle large sets of real-world video and sensor data for data mining, curation, labeling, training, and evaluation. Train and deploy optimized models to tackle challenges such as multimodal scene understanding, optical flow and range estimation, object detection, segmentation and tracking, visual localization and mapping, few-shot learning, and automated path planning. Location This internship is based in Zurich, Switzerland.