Senior Director - Machine Learning Engineering

Overview

Lead large-scale machine learning engineering initiatives within the Intelligent Foundations and Experiences (IFX) team, building and scaling ML models and software that solve financial services business problems.

What you'll do

• Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
• Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
• Lead large-scale ML initiatives with the customer in mind
• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
• Optimize data pipelines to feed ML models
• Use programming languages like Python, Scala, or Java
• Evangelize best practices in all aspects of the engineering and modeling lifecycles
• Recruit, nurture and retain top engineering talent
• Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring other members of the engineering community

What you'll need

• Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics or Engineering
• At least 5 years of people leadership experience
• At least 10 years of experience programming with Python, Java, Golang or C++
• At least 8 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries like Pandas, NumPy and Scikit-learn
• At least 8 years of experience using and operating large scale distributed systems such as Spark and Ray to prepare AI or Machine Learning data
• At least 8 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud such as AWS, GCP, or Azure and using Kubernetes to manage large scale containerized Machine Learning software systems

Nice to have

• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
• 7+ years of experience leading software engineering teams
• 5+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training and inference
• 7+ years of experience optimizing ML algorithms, configurations and infrastructure
• 7+ years of experience working with Machine Learning techniques including Supervised, semi-supervised, unsupervised, and reinforcement learning, model types including Regression, Classification, and Clustering, model Architectures including RNNs, CNNs, LSTMs and Transformers, training concepts such as loss function, hyperparameters, and regularization and how to evaluate model accuracy and diagnose and address common issues such as underfitting and overfitting
• 9+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• Experience shaping long term cross-organizational machine learning strategy
• Ability to communicate complex technical concepts clearly to executive leadership
• Recognized leader in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
• Experience developing high-performing ML engineers with an inspiring leadership style

Details

• Location: Bangalore, Karnātaka, India
• Capital One will not sponsor a new applicant for employment authorization for this position