- Experience & Education: Typically 10-plus years of experience with a broad and deep portfolio of applied ML and data science work; or a PhD with 6-plus years of relevant experience. A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
- Technical Mastery: Expert-level proficiency in Python and advanced scientific computing, with a track record of building large-scale, production-grade ML systems. Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy
- AI/ML Expertise: Recognized depth in machine learning and statistical methodology. Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs) and experience with multimodal data processing (e.g., combining text, image, and 3D data). Strong background in probability, statistics, and optimization techniques relevant to generative modeling
- Strategic & Operational Skills: Demonstrated ability to drive 18-24 month technical initiatives that deliver lasting organizational and business impact. Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker), and familiar with software engineering principles, including version control, reproducibility, and continuous integration
- Communication: Exceptional influence and communication skills, with a track record of aligning executives and cross-functional partners around ambitious scientific directions
- Domain Expertise (Plus): Experience in the manufacturing, supply chain, or similar industries is a plus
The estimated base salary range for new hires into this role is $200,000- $230,000 annually + bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.