Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
Tailor your resume to this Machine Learning Engineer 4 role.
Rezi rewrites your resume against Capital One's job description. Free.
Tailor your resume to this Machine Learning Engineer 4 role.
Rezi rewrites your resume against Capital One's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Machine Learning Engineer 4 posting at Capital One — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Machine Learning Engineer 4 posting at Capital One — free, in seconds.
About the Role
Machine Learning Engineers at Capital One are pivotal in pioneering AI and technology solutions, solving complex business problems in a fast-paced, collaborative, and inclusive environment. This role offers the opportunity to be at the forefront of driving AI transformations and scaling production models.
Responsibilities
- Design, build, and/or deliver ML models and components that solve real-world business problems, in collaboration with Product and Data Science teams.
- Inform ML infrastructure decisions using understanding of ML modeling techniques and issues, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
- 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 for big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, for successful deployment of ML models and application code.
- Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
Requirements
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
- At least 4 years of experience programming with Python, Java, Golang, or C++.
- At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn).
- At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data.
- At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems.
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field.
- 3+ years of experience optimizing ML algorithms, configurations, and infrastructure.
- 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc.
- 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans.
- 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting).
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
- 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation.
- Authored/co-authored a paper on a ML technique, model, or proof of concept.
Skills
- Python
- Java
- Golang
- C++
- PyTorch
- Tensorflow
- Pandas
- NumPy
- Scikit-learn
- Spark
- Ray
- AWS
- GCP
- Azure
- Kubernetes
- Responsible AI
- Explainable AI
Location
- New York, NY
Work Type
- Full-time
Experience Level
- 4 years of experience programming
- 4 years of Machine Learning experience
- 4 years of experience using and operating large scale distributed systems
- 2 years of experience deploying and operating Machine Learning solutions in production
- 3+ years of experience optimizing ML algorithms
- 3+ years of experience following software development best practices
- 3+ years of experience building resilient software solutions
- 3+ years of experience working with Machine Learning techniques
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines
- 1+ years of experience as a technical lead
Education Level
- Bachelor's Degree in Computer Science, Machine Learning or a related quantitative field
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field
Salary/Compensations
- $215,200 - $245,600
Benefits
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
About the Company
- Capital One is a group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs.
- Capital One Financial is made up of several different entities. Positions posted in Canada are for Capital One Canada, in the United Kingdom for Capital One Europe and in the Philippines for Capital One Philippines Service Corp. (COPSSC).
Equal Opportunity
- 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.
- 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 at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.