Lead Machine Learning Engineer

Capital One National Association; Bengaluru; On-site; INR 2,200,000 - 3,500,000; Full time

Job summary

A leading company in financial services is seeking a Lead Machine Learning Engineer to automate model governance processes. The role involves working with advanced data architectures and collaborating with product teams to enhance machine learning solutions, focusing on innovative, scalable applications that drive business impact. Qualified candidates will possess extensive experience in ML development and data engineering, with strong programming skills.

Qualifications

• 6+ years designing and building data solutions.
• 4+ years programming with Python, Go, or Java.
• 2+ years optimizing ML systems.

Responsibilities

• Work with model teams on automated governance.
• Build solutions for scalable governance processes.
• Create software for ML applications in an Agile team.

Skills

Python

Java

Scala

MLOps

Machine Learning

Data Pipelines

Cloud Computing

Education

Bachelor’s Degree

Master’s Degree or PhD in relevant field

Tools

scikit-learn

PyTorch

TensorFlow

Dask

Spark

Job description

Voyager (94001), India, Bangalore, Karnataka

Lead Machine Learning Engineer

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.

We’re looking for a Lead - Machine Learning Engineer to join the Machine Learning Experience (MLX) team! As a Capital One Machine Learning Engineer (MLE), you'll be part of a team focusing on automating governance within the model development lifecycle. You will work with model training and feature and serving metadata at scale, to enable automated model governance decisions. 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.

The MLX team is at the forefront of how Capital One builds and deploys well-managed 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 we’re working to seamlessly infuse ML into the fabric of the company. The ML experience we're creating today is the foundation that enables each of our businesses to deliver next-generation ML-driven products and services for our customers.

What You’ll Do

● Work with model and platform teams to build systems that ingest large amounts of model and feature metadata that will feed into automated governance decisioning

● Partner with product and design teams to build elegant and scalable solutions to speed up governance processes

● 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 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

● Advocate for software and machine learning engineering best practices

Function as a technical lead

Basic Qualifications

● Bachelor’s Degree

● At least 6 years of experience designing and building data intensive solutions using distributed computing

● At least 4 years of experience programming with Python, Go, or Java

● At least 2 years of experience building, scaling, and optimizing ML systems

● At least 2 years of experience with the full ML Development Lifecycle using industry-recognized best practices

Preferred Qualifications

● Master’s Degree or PhD in Computer Science, Electrical Engineering, Mathematics, or a similar field

● Atleast 3 years of experience in building production-ready data pipelines that feed ML models

● Atleast 3 years of on job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

● Atleast 2 years of experience developing performant, resilient, and maintainable code

● Atleast 2 years of experience with data gathering and preparation for ML models, practices, patterns, and automation

● Candidates should have experience with Model Observability - Monitoring and Telematics, MLOps, Python Scripting, Stats and Mathematical Modelling and Data Pipelines.

● Should have developed some POC/ Production Grade Application implementing Use Case specific Fine Tuned LLM.

● Candidates should have Maintained/ Developed 2-3 Large Scale Production grade ML Applications involving a set of various components using different ML/ AI models i.e mix of Calssic ML models as well as Advanced ML Models. Integration with LLM's like LLAMA, BERT or any other transformer based model is a great plus point.

● Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

● Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

● Contributed to open source ML software

● Authored/co-authored a paper on a ML technique, model, or proof of concept

No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

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For technical support or questions about Capital One's recruiting process, please send an email to [e-mail]

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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).