Senior Machine Learning Engineer

Summary

fabric is looking for a Machine Learning Engineer with 5+ years of experience in Generative AI models, preferably in e-commerce or retail domain. The role involves designing and implementing ML solutions from scratch, collaborating with cross-functional teams, staying up-to-date with the latest developments in machine learning, and maintaining detailed documentation.

Requirements

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field
• Proven experience (5+ years) in designing and implementing Generative AI models, preferably in the e-commerce or retail domain
• Proficiency in programming languages such as Python and familiarity with ML libraries/frameworks like TensorFlow, PyTorch, scikit-learn, etc
• Solid understanding of statistical modeling and data analysis techniques
• Experience in working with e-commerce-related large data (TB+ preferred) and concepts
• Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment
• Excellent communication skills to explain complex technical concepts to non-technical stakeholders
• Knowledge of cloud platforms like AWS, Azure, or GCP

Responsibilities

• Generative AI Development: Lead the research, design, and implementation of Generative AI models with a focus on product recommendation and personalization
• Algorithm Development: Research, design, and develop machine learning models and algorithms tailored to e-commerce use cases
• Data Processing: Analyze large datasets to extract meaningful insights for training and fine-tuning Generative AI models
• Model Training: Train and fine-tune Deep Learning / Reinforcement Learning / Causal models using state-of-the-art techniques, incorporating both structured and unstructured data sources
• Model Deployment: Extensive experience working with machine learning / deep learning libraries and toolsets (C++/Java//Python preferred). Familiarity with AWS or GCP ML tools ensuring scalability, reliability, and real-time performance
• Continuous Improvement: Monitor model performance, identify areas for improvement, and iterate on existing solutions to enhance accuracy and efficiency
• Collaboration: Collaborate with software engineers, product managers, and stakeholders to integrate machine learning features into the SaaS platform
• Research & Innovation: Stay up-to-date with the latest developments in machine learning and e-commerce. To be able to build quick prototypes for multiple use cases to explore green field opportunities across the ecommerce space
• Documentation: Maintain detailed documentation of ML models, processes, and solutions for future reference

Benefits

• Competitive compensation packages
• PTO and Holiday plans
• Benefits packages which include Medical, Dental, Life, and Vision
• Wellness & Technology Programs
• 401k Program
• Fast-paced, fun and collaborative environment
• A team invested in you both personally and professionally