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:

At DICK’S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve. If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today! OVERVIEW: About GameChanger: We believe in the life changing impact youth sports have on and off the field. Sports encourage leadership, teamwork, responsibility, and confidence – important life lessons that have the power to propel our youth toward meaningful futures. We recognize that without coaches, parents, and volunteers, organized youth sports could not exist. By building the first and best place to experience the youth sports moments important to our community, we are helping families elevate the next generation through youth sports. So if you love sports and their community building potential, or building cool products is your sport, GameChanger is the team for you. We are a remote first, dynamic tech company based in New York City, and we are solving some of the biggest challenges in youth sports today. The Position: The Computer Vision Platform team at GameChanger builds and operates the real-time inference infrastructure that delivers CV-powered experiences to millions of users every weekend. You'll partner directly with researchers to shape their models and code for production, steer them toward existing platform capabilities, and collaborate with MLOps engineers to evolve infrastructure where gaps exist. You'll also influence the technical direction of the platform itself, identifying which capabilities to build next based on patterns you see across research efforts. You'll report directly to the Engineering Manager, CV Platform. What You'll Do: - Work directly with CV researchers to understand their goals, review their code, and engineer it for reliability and performance at scale. - Profile and optimize performance-sensitive code across both training and real-time inference. - Identify patterns across research efforts and propose standardized, composable abstractions. - Collaborate with MLOps and backend engineers to translate recurring research pain points into platform investments through design documents and architecture proposals. - Guide researchers toward production-oriented engineering practices regarding testability, modularity, and performance profiling. Who You Are: - 6+ years of software engineering experience, with 4+ years working on ML systems. - Experience working on production ML systems. Our team uses Python and PyTorch, Docker for containerization, and deploys on AWS. - Experience with data-intensive distributed systems, including optimizing I/O, GPU utilization, and parallel processing. - Experience working directly with researchers or research teams to take their prototypes and deliver production systems that are performant, reliable, and maintainable. - Experience building internal libraries, tools, or platforms that other engineers depend on. Perks: - Work remotely throughout the US* or from our well-furnished, modern office in Manhattan, NY. - Unlimited vacation policy. - Paid volunteer opportunities. - Technology stipend - $4,000 every 2 years after your start to make sure you have the latest and greatest technology. - WFH stipend - $500 annually to make your WFH situation comfortable. - Monthly physical, mental, wellness & learning stipend offered through Holisticly. - Monthly lifestyle stipend offered through Fringe. - Full health benefits - medical, dental, vision, prescription, FSA, HRA, HSA, and coverage for family/dependents. - Retirement savings - Traditional and Roth 401K plans are offered through Vanguard, with an immediate company match. - Life insurance - basic life, supplemental life, and dependent life. - Disability leave - short-term disability and long-term disability. - Company paid parental leave - up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents. - Family building benefits offered through Progyny. - DICK'S Sporting Goods and their family of brands teammate discount. The target salary range for this position is between $180,000 and $200,000. This is part of a total compensation package that includes incentive, equity, and benefits for eligible roles. Individual pay may vary from the target range and is determined by several factors including experience, internal pay equity, and other relevant business considerations. We constantly review all teammate pay to ensure a great compensation package that is fair and equal across the board. * DICK'S Sporting Goods has company-wide practices to monitor and protect the company from significant compliance and monetary implications as it pertains to employer state tax liabilities. Due to said guidelines put in place, we are unable to hire in AK, DE, HI, IA, LA, MS, MT, OK, and SC. We are an equal opportunity employer and value diversity in our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Our Interview Process & AI We recognize that AI has become a common part of everyday life and professional work, and its use continues to evolve rapidly. Our perspective on AI in the hiring process will evolve as well. At this time, we ask that candidates please refrain from using AI tools during interviews and assessments, as we want to see your authentic self. We will clearly indicate if and when AI use is acceptable in the process. If you have any questions or need accommodations, we're here to help. Thanks for helping us keep the process fair and secure for everyone! IMPORTANT NOTICE: All official recruitment communications from GameChanger will come from an email address ending in @gc.com or no-reply@ashby.hq.com. If you receive communication from any other domain, please be cautious, as it is likely fraudulent. QUALIFICATIONS: - Bachelor's Degree or Master’s Degree in Computer Science, or equivalent work experience - 3-6 years of experience in software engineering - TypeScript - React JS / Kotlin / Swift - Postgres - AWS VIRTUAL REQUIREMENTS: At DICK’S, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools (like ChatGPT or others) during interviews or assessments. To ensure a smooth and secure experience, please note the following: - Cameras must be on during all virtual interviews. - AI tools are not permitted to be used by the candidate during any part of the interview process. - Offers are contingent upon a satisfactory background check which may include ID verification. If you have any questions or need accommodations, we’re here to help. Thanks for helping us keep the process fair and secure for everyone!