Senior Machine Learning Engineer, O'Reilly Media

• We need someone who deeply understands modern machine learning, excels in Python programming, and has a proven track record leading and delivering successful AI projects from start to finish
• Bachelor's degree in Computer Science, Statistics, Mathematics, or Engineering-related field
• In lieu of a degree, equivalent experience and relevant skills may be considered
• 4+ years of on-the-job experience in developing, implementing, productionizing machine learning applications and systems, with at least 1 year of that in a senior role (or equivalent)
• Proven experience in developing and deploying machine learning models at scale
• Proficiency with popular data science and machine learning libraries, such as Pandas, NumPy, TensorFlow, Keras, Scikit-learn or PyTorch
• Strong programming skills in Python and familiarity with relevant ML libraries and frameworks
• Experience with Natural Language Processing (NLP) techniques
• Familiarity with data processing techniques with any dataflow pipelines
• Familiarity with Retrieval Augmented Generation (RAG)
• Experience with any vector database
• Experience with LLMs and Generative AI
• Expertise in Prompt Engineering
• Experience in AI product evaluation
• Strong problem-solving skills and critical-thinking competencies
• Excellent communication and collaboration skills. Ability to work independently as well as in a team

Desirable

• O'Reilly Media is seeking a passionate Senior Machine Learning Engineer to shape the future of our learning platform!
• Here, you'll design, build, and optimize machine learning models and systems (primarily in Python) to personalize user experiences, make predictions, and track user behavior for millions of learners
• Lead end-to-end development of machine learning models, from data exploration to model deployment
• Collaborate with cross-functional teams, including data scientists and other software engineers
• Consult with product managers and business stakeholders to define new project requirements and design solutions that meet those needs
• Design and implement scalable and efficient data pipelines, such as GCP Dataflow pipelines, to preprocess and transform raw data for machine learning models
• Develop and tune machine learning models using libraries such as TensorFlow, Keras, Scikit-learn or PyTorch
• Monitor and analyze model performance and continuously improve them over time
• Building and maintaining web services that provide personalization services using machine learning models to end users. This can include building API, processing data, as well as building any other systems required to meet our goals
• Leverage AI to drive efficiency and optimize processes within the organization
• Stay up-to-date with the latest research and trends in AI, and find the opportunity to apply them to our business
• Mentor other engineers, fostering their growth and development