Role Description As an Open-Source Machine Learning Engineer, you'll work to improve the open-source machine learning ecosystem. You'll mainly work on existing open-source libraries such as Transformers, Datasets, Pytorch, and vLLM, and you'll interact with users and contributors across the broad open-source ML ecosystem. We'll brainstorm with you to put you in a position to do the work that interests you and that is impactful. - Help foster one of the most active machine learning communities. - Assist users in contributing to and using the tools you build. - Collaborate with researchers, ML practitioners, and data scientists through GitHub, forums, and Slack. Qualifications - Strong Python skills, with experience writing clean, well-tested, maintainable library code. - Deep hands-on experience with a modern deep-learning framework, especially PyTorch (JAX or TensorFlow a plus). - Practical experience with the Hugging Face open-source stack (Transformers, Datasets, Accelerate) or comparable ML libraries. - A public track record of open-source contributions, for example merged pull requests to ML or data libraries, that we can review on GitHub. - Solid understanding of modern machine learning and deep learning, including transformer architectures. - Experience collaborating with a technical community in the open (GitHub issues and reviews, forums, Slack or Discord). - Fluent written English for asynchronous collaboration across a distributed, global community. Requirements - Experience maintaining an open-source project (nice to have). - Prior contributions to Transformers, Datasets, Accelerate, or similar libraries (nice to have). - Familiarity with distributed training, inference optimization, or GPU/accelerator performance work (nice to have). - Experience training or fine-tuning models at scale (nice to have). Benefits - Flexible working hours and remote options. - Health, dental, and vision benefits for employees and their dependents. - Parental leave and flexible paid time off. - Reimbursement for relevant conferences, training, and education. - Company equity as part of the compensation package. - Support for remote employees to visit office spaces in NYC and Paris. - Workstation outfitting to ensure success.

• Build ML models for real-time disinformation detection • Deploy and monitor models in production environments • Manage data pipelines using streaming and batch processing frameworks • Make architectural decisions on databases, infrastructure, and system design • Collaborate across engineering, ML, and intelligence teams

• Design, train, and deploy ML models for time-series forecasting and related data tasks • Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure) • Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT) • Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions • Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders

Role Description Our client, a growing educational and technology organization, is seeking an experienced AI & Machine Learning Instructor to teach and mentor students on artificial intelligence, machine learning engineering, intelligent systems development, and practical strategies for becoming successful AI & Machine Learning Engineers. This role is ideal for an experienced AI or Machine Learning professional who is passionate about teaching and sharing real-world industry knowledge with aspiring AI engineers, data professionals, and software developers. - Deliver engaging training sessions on artificial intelligence, machine learning, and intelligent systems development. - Teach students how to design, build, train, evaluate, and deploy machine learning models and AI-powered applications. - Guide students on supervised learning, unsupervised learning, deep learning, neural networks, and AI engineering workflows. - Share practical experiences, case studies, and real-world AI and machine learning project insights with students. - Teach students programming concepts using Python and relevant AI/ML frameworks and tools. - Train students on data preprocessing, model optimization, feature engineering, and AI deployment techniques. - Develop instructional materials, coding exercises, presentations, and hands-on AI projects. - Facilitate workshops, live coding demonstrations, and project-based learning sessions. - Mentor students on portfolio development, technical problem-solving, and AI career pathways. - Stay updated on emerging AI technologies, machine learning advancements, Generative AI, and industry best practices. Qualifications - Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or related field required. - Master’s degree or advanced certification in AI, Machine Learning, or Data Science is an advantage. - Minimum of 4–5 years of practical experience in artificial intelligence, machine learning engineering, data science, or related technology fields. - Strong understanding of machine learning algorithms, deep learning, AI engineering workflows, and data-driven systems. - Experience working with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or similar technologies. - Proficiency in Python and familiarity with APIs, cloud AI tools, databases, and deployment technologies. - Excellent communication, presentation, and mentoring skills. - Ability to explain technical concepts clearly and engage students effectively. - Strong analytical, coding, and problem-solving abilities. - Must be legally authorized to work in the USA or Canada. Preferred Qualifications - Experience delivering technical training, workshops, or mentoring programs. - Familiarity with NLP, Generative AI, LLMs, computer vision, or AI automation tools. - Experience building and deploying AI-powered solutions in commercial or production environments. - Certifications in AI, machine learning, cloud technologies, or data science are an advantage. Requirements - Part time. Pay depends on experience.