Senior Machine Learning Engineer

About the Role

We're seeking a Machine Learning Engineer to join our team supporting a strategic client engagement focused on deep learning model development for customer behavior prediction. You'll work alongside client data scientists and engineers to enhance and optimize deep-learning models that drive business decisions at scale.

This role involves hands-on work across the ML lifecycle—from feature engineering to model architecture improvements—within a collaborative, research-informed environment. You'll have the opportunity to implement techniques from cutting-edge academic research while contributing to production systems that directly impact business outcomes.

Key Responsibilities

• Develop and refine features for deep learning models, working with large-scale customer and behavioral datasets
• Implement model architecture changes informed by recent academic research (e.g., papers from NeurIPS and similar venues)
• Collaborate with client teams to understand business context and translate requirements into technical solutions
• Optimize model training pipelines for efficiency and scalability
• Document approaches, findings, and technical decisions for knowledge sharing across teams
• Participate in code reviews and contribute to engineering best practices

Required Skills & Experience

• Strong proficiency with a deep learning framework (e.g. Pytorch, tensorflow)
• Hands-on experience with feature engineering for predictive models
• Solid foundation in machine learning fundamentals (supervised learning, neural network architectures, optimization)
• Ability to read, understand, and implement techniques from ML research papers
• Python proficiency in a data science/ML context
• Comfortable working in ambiguous environments and adapting to unfamiliar tooling

Nice to Have

• Experience with time-series or sequential modeling
• MLOps experience (model deployment, monitoring, pipeline orchestration)
• Familiarity with Google Cloud Platform or large-scale distributed training
• Background in causal inference or attribution modeling
• Experience working in consulting or client-facing technical role