- As a Capital One Machine Learning Engineer, youll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale
- You ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms
- Working within an Agile setting, you ll serve as a technical lead, helping guide machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications
- Youll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering
- You ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology
- What you ll do in the role: Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams
- Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
- Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art, next generation big data and machine learning applications
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
- Construct optimized data pipelines to feed MLmodels
- Use programming languages like Python, Scala, or Java
- Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code




- Advocate for software and machine learning engineering best practices
- Function as the engineering tech lead for large-scale initiatives
- Recruit and mentor junior engineering talent
- Basic Qualifications Bachelor s degree
- At least 8 years of experience designing and building data-intensive solutions using distributed computing
- At least 4 years of experience programming with Python, Scala, or Java
- At least 3 years of experience building, scaling, and optimizing ML systems
- At least 2 years of experience with the full ML development lifecycle using modern technology in a business critical setting
- At least 2 years of experience leading teams developing ML solutions
- Preferred Qualifications Masters or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
- At least 4 years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
- At least 3 years of experience developing performant, resilient, and maintainable code
- At least 3 years of experience with data gathering and preparation for ML models
- At least 3 years of people management experience
- ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
- At least 3 years of experience building production-ready data pipelines that feed ML models
- Ability to communicate complex technical concepts clearly to a variety of audiences
- At this time, Capital One will not sponsor a new applicant for employment authorization for this position

Skills: Docker, Spring Boot, Kubernetes, Restful Apis, Java

Experience: 8.00-13.00 Years

📌 Lead Software Engineer (Bengaluru)
🏢 Capital One
📍 Bengaluru