Thoughtworks Technology Podcast Building at the intersection of machine learning and software engineering
May 2, 2024
Discover the challenges of bringing machine learning models into production and how new teams are bridging the gap between data science and software engineering. Learn about effective teamwork, rigorous testing, and collaboration between data scientists and product owners. Dive into the importance of trust, communication, and experimentation in building effective ML teams, and explore adapting ML techniques in the Gen R2 AI era. Enhance ML product development in modern digital organizations and focus on problem-solving and value delivery in machine learning products.
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Real-Life Inspiration
- The book's fictional scenarios are based on real experiences from the authors' projects.
- These scenarios are often combined or slightly altered, but the challenges they depict are genuine.
Dana's Story
- The book follows a fictional character, Dana, a data scientist/ML engineer, through common challenges.
- One anecdote describes a failed deployment on the day of a celebratory lunch, highlighting the pressures teams face.
Effective Teams, Effective Products
- Effective machine learning products require effective teams.
- Team effectiveness involves building the right thing, building it right, and building it right for the people involved.