Senior ML Engineer — Pricing & Demand Forecasting (Onsite Fremont)

Weee! Inc; United States; On-site; USD 123,000 - 151,000; Full time

Job summary

Weee! Inc. in Fremont, CA, seeks a Senior Machine Learning Engineer to build pricing and promotional models and own end-to-end ML solutions.

You will design, train, deploy, and monitor models using diverse data sources, collaborating with pricing, product, and data teams to improve revenue and efficiency. The role requires a bachelor’s degree in Information Science or a related field and 2 years of experience in ML roles, with hands-on work in deep learning, time-series forecasting, multimodal

Qualifications

• Bachelor's degree in Information Science or related field with 24 months of relevant experience.
• Experience in deep learning model design and architecture.
• Experience with time-series forecasting and decision modeling.
• Production ML with cloud deployment and ML infrastructure.

Responsibilities

• Develop and implement advanced machine learning models to enhance pricing strategies and promotional effectiveness.
• Build end-to-end ML solutions from data exploration to deployment and monitoring.
• Collaborate with cross-functional teams to apply ML innovations for pricing and promotion optimization.
• Drive insights using ML and statistical models to unlock business opportunities.

Skills

Deep Learning

ML for Production

Time-Series Forecasting

Multimodal Modeling

Representation Learning

Generative AI/LLM

ML Infrastructure & Cloud

Education

Bachelor's degree in Information Science or related field

Job description

Weee! Inc. in Fremont, CA, seeks a Senior Machine Learning Engineer to build pricing and promotional models and own end-to-end ML solutions.

You will design, train, deploy, and monitor models using diverse data sources, collaborating with pricing, product, and data teams to improve revenue and efficiency. The role requires a bachelor’s degree in Information Science or a related field and 2 years of experience in ML roles, with hands-on work in deep learning, time-series forecasting, multimodal