What You’ll Do - Translate cutting-edge research into production-ready machine learning systems - Design, build, and deploy end-to-end ML models and pipelines - Develop and optimize models for image and video processing - Own the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deployment - Build low-latency, real-time inference systems and scalable ML infrastructure - Rapidly prototype using open-source models and adapt them for product needs - Conduct experiments, analyze results, and iterate to improve performance - Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale - Stay current with advancements in machine learning and apply them to continuously improve products What We’re Looking For Required Qualifications - MS/PhD in Computer Science, Electrical Engineering, or related field - Strong research experience with familiarity in top conferences (e.g., CVPR, ICCV, NeurIPS) - 5+ years of experience in Python and proficiency in Java, C++, or Scala - Strong understanding of multi-threading and memory management - Solid knowledge of ML architectures: CNNs, RNNs (LSTM/GRU), and Transformers - Experience with PyTorch or TensorFlow - Experience building end-to-end ML deployment and inference systems, especially for low-latency, real-time applications - Experience handling large-scale data using tools like Spark - Experience deploying ML models in cloud environments (AWS preferred) - Experience with experiment tracking systems and ML workflows Nice to Have - Experience in low level optimisation, cuda etc. - Experience productionizing and scaling ML models in real-world systems - Contributions to open-source projects - Experience with MLOps tools or distributed training systems - Familiarity with relational databases (Postgres/MySQL) What we offer (compensation & benefits) - Competitive salary and equity - Private health coverage - Pension contribution (UK, Canada, US) - Fully-distributed, async-first culture - Hardware setup of your choice - Stipends for phone, internet, and meals In our team, we approach our work with the dedication similar to Olympic athletes. Anticipate occasional late nights and weekends dedicated to our mission. We understand this level of commitment may not suit everyone, and we openly communicate this expectation. If you're motivated by deeply technical problems, a seemingly never-ending uphill battle and the opportunity to build (and own) a generational technology company, we can give you what you're looking for. All business roles at Moonvalley are hybrid positions by default, with some fully remote depending on the job scope. We meet a few times every year, usually in London, UK or North America (LA, Toronto) as a company. If you're excited about the opportunity to work on cutting-edge AI technology and help shape the future of media and entertainment, we encourage you to apply. We look forward to hearing from you! The statements contained in this job description reflect general details as necessary to describe the principal functions of this job, the level of knowledge and skill typically required and the scope of responsibility. It should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned, including work in other functional areas to cover absences, to equalize peak work periods, or to otherwise balance organizational work Moonvalley AI is proud to be an equal opportunity employer. We are committed to providing accommodations. If you require accommodation, we will work with you to meet your needs. Please be assured we'll treat any information you share with us with the utmost care, only use your information for recruitment purposes and will never sell it to other companies for marketing purposes. Please review our privacy policy and job applicant privacy policy located here for further information.

Senior Deep Learning Engineer locations UK, Remote Poland, Remote Switzerland, Remote Germany, Remote Netherlands, Remote time type Full time job requisition id JR2013341 We are looking for a Senior Deep Learning Engineer to help bring Cosmos World Foundation Models from research into efficient, production-grade systems. You’ll focus on optimizing and deploying models for high-performance inference on diverse GPU platforms. This role sits at the intersection of deep learning, systems, and GPU optimization - working closely with research scientists, software engineers, and hardware experts. NVIDIA Cosmos is a platform purpose-built for physical AI, featuring powerful generative models. Developers use Cosmos to accelerate physical AI development for autonomous vehicles (AVs), robots, and video analytics AI agents by simulating and reasoning about the physical world. What you'll be doing: - Improve inference speed for Cosmos WFMs on GPU platforms. - Effectively carry out the production deployment of Cosmos WFMs. - Profile and analyze deep learning workloads to identify and remove bottlenecks. What we need to see: - 5+ years of experience. - MSc or PhD in CS, EE, or CSEE or equivalent experience. - Strong background in Deep Learning. - Strong programming skills in Python and PyTorch. - Experience with inference optimization techniques (such as quantization) and inference optimization frameworks, one of: TensorRT, TensorRT-LLM, vLLM, SGLang. Ways to stand out from the crowd: - Familiarity with deploying Deep Learning models in production settings (e.g., Docker, Triton Inference Server). - CUDA programming experience. - Familiarity with diffusion models. - Proven experience in analyzing, modeling, and tuning the performance of GPU workloads, both inference and training. #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 221,250 PLN - 383,500 PLN for Level 3, and 292,500 PLN - 507,000 PLN for Level 4.

At Counterpart Health, we are transforming healthcare and improving patient care with our innovative primary care tool, Counterpart Assistant. By supporting Primary Care Physicians (PCPs), we are able to deliver improved outcomes to our patients at a lower cost through early diagnosis and longitudinal care management of chronic conditions. We’re looking for a Senior Machine Learning Engineer to help us build a revolutionary new health care business. Clover uses Machine Learning/Natural Language Processing to leverage our data to help keep beneficiaries healthy and out of the hospital by getting them targeted care. By predicting avoidable adverse events, our ML/NLP/LLM infrastructure is central to working on our central mission, and has a direct impact on our beneficiaries. You will help build systems and tools that support the data needs of a diverse organization and contribute to the expansion of the Machine Learning/Natural Language Processing/LLM capabilities of our Data Platform. As a Senior Machine Learning Engineer, you will: - Design, implement and validate high-reliability, distributed platforms for machine learning, natural language processing, and LLMs. - Create, debug, interpret and improve production machine learning and natural language processing models. - Build the tools and validation processes that help Clover translate insights into action at scale. - Use existing commercial and open source tools to create a robust production platform. - Work closely with Clover's Data Science and Engineering teams to ensure that the ML/NLP/LLM Platform is providing real value. - Document, iterate, and provide tutorials to ensure Data Scientists are able to use your tools easily. You will love this job if: - You want to create impact with your work by finding machine learning-driven insights in the data to unlock value and improve health outcomes for real people. - You are comfortable acting autonomously in ambiguous and changing environments. - You value collaboration and feedback. You can communicate technical vision in clear terms— to your teammates and across the technology team more broadly. You are willing and able to help your teammates grow by demonstrating best practices, providing (and receiving) respectful and constructive feedback, and disclosing your unique insights with everyone. - You enjoy working in a fluid environment, defining priorities that adapt to our larger goals. You can bring clarity to ambiguity while remaining open-minded to new information that might change your mind. - You are not hesitant to jump in to help fix things that are broken and you are encouraged to make sustainable systems. You are happy to fill in the gaps to reach a goal where necessary, even if it does not always fit your job description. - You have a genuine interest in what good technology can do to help people and have a positive attitude about tackling hard problems in an important industry. You should get in touch if: - You have 5+ years of experience in Machine Learning Engineering roles in technology enabled companies. Healthcare experience preferred but not required. - You have experience with Python, Python data science libraries (numpy, pandas, sklearn, tensorflow, pytorch, etc.), and deploying Python apps into production environments. - You have experience with Natural Language Processing and/or LLMs. - You have a solid foundation in feature engineering, feature selection, and machine learning techniques. - You have experience interpreting, modifying, and debugging the inputs and outputs of production ML/NLP/LLM models. - You have both built and refactored complex distributed systems, especially ML/NLP/LLM systems. - You have scaled the impact of other engineers and data scientists through mentorship, development of reusable libraries, and documentation. Benefits Overview: - Financial Well-Being: Our commitment to attracting and retaining top talent begins with a competitive base salary and equity opportunities. Additionally, we offer a performance-based bonus program, 401k matching, and regular compensation reviews to recognize and reward exceptional contributions. - Physical Well-Being: We prioritize the health and well-being of our employees and their families by providing comprehensive medical, dental, and vision coverage. Your health matters to us, and we invest in ensuring you have access to quality healthcare. - Mental Well-Being: We understand the importance of mental health in fostering productivity and maintaining work-life balance. To support this, we offer initiatives such as No-Meeting Fridays, monthly company holidays, access to mental health resources, and a generous flexible time-off policy. Additionally, we embrace a remote-first culture that supports collaboration and flexibility, allowing our team members to thrive from any location. - Professional Development: Developing internal talent is a priority for Clover. We offer learning programs, mentorship, professional development funding, and regular performance feedback and reviews. Additional Perks: - Employee Stock Purchase Plan (ESPP) offering discounted equity opportunities - Reimbursement for office setup expenses - Monthly cell phone & internet stipend - Remote-first culture, enabling collaboration with global teams - Paid parental leave for all new parents - And much more! About Counterpart Health: In 2018, Clover Health set out to do something unprecedented: build a clinically intuitive, AI-enabled solution that fits within physicians' workflows to help support the earlier diagnosis and management of chronic conditions. Years later, that vision is a reality, with thousands of practitioners using Counterpart Assistant during patient visits to improve disease management, reduce medical expenses, and drive success in value-based care. With an exceptional team of value-based care and technology experts, Counterpart Health is driving value-based care at the speed of software. Counterpart Health is a subsidiary of Clover Health. From Clover’s inception, Diversity & Inclusion have always been key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, perspectives, opinions, and backgrounds, who share a passion for improving people's lives. Diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion and many other parts of one’s identity. All of our employee’s points of view are key to our success, and inclusion is everyone's responsibility. #LI-REMOTE Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. We are an E-Verify company. Final pay is based on several factors including but not limited to internal equity, market data, and the applicant’s education, work experience, certifications, etc. A reasonable estimate of the base salary range for this role is: $150,000—$200,000 USD

Our team at Fraunhofer LBF conducts research into solutions for the design of sustainable materials, structures, and systems, as well as circular economy strategies that meet the highest standards of reliability, efficiency, and resilience. Would you like to be part of this inspiring team? We look forward to receiving your application! Master Thesis Machine Learning for retired Lithium-Ion Cell Sorting (all genders) Darmstadt As electric mobility continues to expand globally, sustainable recycling and second-life utilization of traction batteries are becoming increasingly critical. At Fraunhofer LBF, we are developing an automated disassembly system for electric vehicle batteries. A key component of this process is the rapid and reliable evaluation of individual cell health. The master thesis focuses on the development of a machine learning model for the automatic sorting of used lithium-ion cells based on custom electrochemical impedance spectroscopy (EIS) data. The objective is to build a model that processes EIS measurements and assigns cells to the appropriate sorting category. The sorted cells are subsequently grouped according to their intended secondary use. A dataset for training and testing the model will be provided. In addition, the thesis should investigate how different types of EIS data influence sorting accuracy and model performance. Be part of change - Literature review on machine learning methods for battery cell classification and EIS-based analysis - Familiarization with the provided EIS dataset - Development and training of a machine learning model for cell sorting - Evaluation of model performance on test data - Investigation of the influence of different EIS data types on sorting accuracy - Documentation of the results What you contribute - Electrical Engineering / Mechatronics / Computer Science or related fields - Strong interest in machine learning - Basic knowledge of Python and common machine learning libraries - Basic knowledge of electrochemistry and battery technology or willingness to learn What we offer - Flexible working conditions with up to 99% remote work - Please note: this is an unpaid thesis position - An individually tailored task with plenty of creative freedom - A highly topical and practically relevant research topic with direct relevance to the circular economy - The opportunity to actively participate in an innovative and interdisciplinary project - Insight into current developments in battery cell disassembly and diagnostics We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities. With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next. Do you have questions about the position? Our colleague Savan Dihora is there for you: Phone +49 6151 705-573 Fraunhofer Institute for Structural Durability and System Reliability LBF www.lbf.fraunhofer.de Requisition Number: 84126 Application Deadline: