Senior Manager, Machine Learning Engineer

Senior Manager Machine Learning Engineer

Do you love building and pioneering in the AI and technology space Do you enjoy solving complex business problems in a fast-paced collaborative inclusive and iterative delivery environment At Capital One youll be part of a big group of makers breakers doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks advanced algorithms and emerging technologies to join our team. As a Machine Learning Engineer youll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.

What Youll Do:

• The MLE role overlaps with many disciplines such as Ops Modeling and Data this role youll be expected to perform many ML engineering activities including one or more of the following:

• Design build and/or deliver ML models and components that solve real-world business problems while working in collaboration with the Product and Data Science teams

• Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale

• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues including choice of model data and feature selection model 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 that enables state-of-the-art 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 to ensure successful deployment of ML models and application code

• Ensure all code is well-managed to reduce vulnerabilities models are well-governed from a risk perspective and the ML follows best practices in Responsible and Explainable AI

• Use programming languages like Python Scala or Java

Basic Qualifications:

• Bachelors Degree or higher in Computer Science Machine Learning or a related quantitative field (Statistics Economics Operations Research Analytics Mathematics Engineering)

• At least 6 years of experience programming with Python Java Golang or C

• At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas NumPy Scikit-learn)

• At least 6 years of experience using and operating large scale distributed systems (Spark Ray) to prepare AI/ML data

• At least 4 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

Preferred Qualifications:

• Masters or doctoral degree in computer science electrical engineering mathematics or related field

• 5 years of experience optimizing ML algorithms configurations and infrastructure

• 5 years of experience following software development best practices including source control testing code reviews CI/CD etc.

• 5 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

• 5 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)

• 5 years of experience designing implementing and scaling production-ready data pipelines for training and evaluating ML models

• ML industry impact through conference presentations papers blog posts open source contributions or patents

• Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge MA: $229900 - $262400 for Machine Learning Engineer 5

McLean VA: $229900 - $262400 for Machine Learning Engineer 5

New York NY: $250800 - $286200 for Machine Learning Engineer 5

San Francisco CA: $250800 - $286200 for Machine Learning Engineer 5

San Jose CA: $250800 - $286200 for Machine Learning Engineer 5

Candidates hired to work in other locations will be subject to the pay range associated with that location and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidates offer letter.

This role is also eligible to earn performance based incentive compensation which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive competitive and inclusive set of health financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status exempt or non-exempt status and management level.

This role is expected to accept applications for a minimum of 5 business days.

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 Citys Fair Chance Act; Philadelphias 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- or 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 third-party 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).

Required Experience:

Senior Manager