Software Engineering Lead, Machine Learning

Responsibilities

• Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems.
• Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems.
• Lead the processing and analysis of large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inform the development of our models.
• Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
• Implement A/B testing and other statistical methods to validate the effectiveness of models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.
• Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption.

Requirements

• Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
• Proven industry experience in building and deploying production-level machine learning models.
• Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models.
• Deep understanding of any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build them for large systems.
• Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch.
• Excellent skills in data processing (SQL, ETL, data warehousing) and experience working with large-scale data systems.
• Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices.
• Familiarity with cloud platforms like GCP or Azure.
• Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects.
• Good understanding of software development principles, data structures, and algorithms.

Compensation (California based)

• Standard base salary: $135,000-$300,000 annually. Compensation determined by location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.