Distinguished Machine Learning Engineer
Distinguished Machine Learning Engineer
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Distinguished Engineer Machine Learning Engineering
At Capital One India we work in a fast paced and intellectually rigorous environment to solve fundamental business problems at scale. Using advanced analytics data science and machine learning we derive valuable insights about product and process design consumer behavior regulatory and credit risk and more from large volumes of data and use it to build cutting edge patentable products that drive the business forward.
Were looking for a Distinguished Engineer Machine Learning Engineering to join the Machine Learning Experience (MLX) team!
As a Capital One Machine Learning Engineer (MLE) youll be part of a team focusing on observability and model governance automation. You will work with model training and features and serving metadata at scale to enable automated model governance decisions and to build a model observability platform. You will contribute to building a system to do this for Capital One models accelerating the move from fully trained models to deployable model artifacts ready to be used to fuel business decisioning and build an observability platform to monitor the models and platform components.
The MLX team is at the forefront of how Capital One builds and deploys wellmanaged ML models and features. We onboard and educate associates on the ML platforms and products that the whole company uses. We drive new innovation and research and were working to seamlessly infuse ML into the fabric of the company. The ML experience were creating today is the foundation that enables each of our businesses to deliver nextgeneration MLdriven products and services for our customers.
What Youll Do
Work with model and platform teams to build systems that ingest large amounts of model and feature metadata and runtime metrics to build an observability platform and to make governance decisions.
Partner with product and design teams to build elegant and scalable solutions to speed up model governance observability
Collaborate as part of a crossfunctional Agile team to create and enhance software that enables state of the art next generation big data and machine learning applications.
Leverage cloudbased architectures and technologies to deliver optimized ML models at scale
Construct optimized data pipelines to feed machine learning models.
Use programming languages like Python Scala or Java
Leverage continuous integration and continuous deployment best practices including test automation and monitoring to ensure successful deployments of machine learning models and application code.
Basic Qualifications
Masters Degree in Computer Science or a related field
At least 15 years of experience in software engineering or solution architecture
At least 10 years of experience designing and building data intensive solutions using distributed computing
At least 10 years of experience programming with Python Go or Java
At least 8 years of onthejob experience with an industry recognized ML framework such as scikitlearn PyTorch Dask Spark or TensorFlow
At least 5 years of experience productionizing monitoring and maintaining models
Preferred Qualifications
Masters Degree or PhD in Computer Science Electrical Engineering Mathematics or a similar field
5 years of experience building scaling and optimizing ML systems
5 years of experience with data gathering and preparation for ML models
10 years of experience developing performant resilient and maintainable code.
Experience developing and deploying ML solutions in a public cloud such as AWS Azure or Google Cloud Platform
5 years of experience with distributed file systems or multinode database paradigms.
Contributed to open source ML software
Authored/coauthored a paper on a ML technique model or proof of concept
5 years of experience building productionready data pipelines that feed ML models.
Experience designing implementing and scaling complex data pipelines for ML models and evaluating their performance
5 years of experience in ML Ops either using open source tools like ML Flow or commercial tools
2 Experience in developing applications using Generative AI i.e open source or commercial LLMs
If you have visited our website in search of information on employment opportunities or to apply for a position and you require an accommodation please contact Capital One Recruiting ator via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital Ones recruiting process please send an email to
Capital One does not provide endorse nor guarantee and is not liable for thirdparty products services educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Employment Type
Full-Time
