Senior Director - Machine Learning Engineering
Salary not listed • Bangalore, In • Full-time
Posted 3d ago
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
The Intelligent Foundations and Experiences (IFX) team is central to bringing AI vision to life at Capital One. We empower teams across the company with Generative AI models and platforms, enabling powerful, safe, and explainable AI capabilities like agentic workflows and shared services such as guardrails, observability, and evals. We also leverage foundational models, both open-weight and proprietary, and deliver capabilities to optimize the software development lifecycle, enhancing developer productivity and accelerating the time-to-market for machine learning models. We are seeking a Senior Director, Machine Learning Engineering who is passionate about leveraging cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to drive major AI transformations and scale production models across Capital One.
Responsibilities
- Deliver ML models and software components that solve challenging business problems in financial services, collaborating with Product, Architecture, Engineering, and Data Science teams.
- Drive the creation and evolution of ML models and software for state-of-the-art intelligent systems.
- Lead large-scale ML initiatives with a customer-centric approach.
- Leverage cloud-based architectures and technologies for optimized ML model delivery at scale.
- Optimize data pipelines to support ML models.
- Evangelize best practices across engineering and modeling lifecycles.
- Recruit, nurture, and retain top engineering talent.
- Act as a force-multiplier by balancing hands-on technical contribution and innovation with mentoring junior engineers.
- Stay on top of tech trends, experiment with new technologies, participate in tech communities, and mentor engineers.
Requirements
- Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field.
- At least 5 years of people leadership experience.
- At least 10 years of programming experience with Python, Java, Golang, or C++.
- At least 8 years of Machine Learning experience using PyTorch or Tensorflow and libraries like Pandas, NumPy, and Scikit-learn.
- At least 8 years of experience using and operating large-scale distributed systems like Spark and Ray for AI/ML data preparation.
- At least 8 years of experience deploying and operating ML solutions in production, including cloud environments (AWS, GCP, Azure) and Kubernetes.
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field (preferred).
- 7+ years of experience leading software engineering teams (preferred).
- 5+ years of experience architecting and designing resilient, large-scale, production ML systems (preferred).
- 7+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
- 7+ years of experience with ML techniques including Supervised, semi-supervised, unsupervised, and reinforcement learning, and model types like Regression, Classification, and Clustering (preferred).
- Experience with model architectures including RNNs, CNNs, LSTMs, and Transformers (preferred).
- Experience with training concepts like loss function, hyperparameters, and regularization, and evaluating model accuracy (preferred).
- 9+ years of experience designing, implementing, and scaling production-ready data pipelines for ML models (preferred).
- Experience shaping long-term, cross-organizational ML strategy (preferred).
- Ability to communicate complex technical concepts clearly to executive leadership (preferred).
- Recognized ML industry leader through presentations, papers, blogs, or open-source contributions (preferred).
- Experience developing high-performing ML engineers with an inspiring leadership style (preferred).