Senior Manager, Machine Learning Engineering

Hobbsnews; McLean (VA); On-site; USD 229,900 - 262,400; Full time

Benefits offered by this job

Comprehensive health benefits

Financial benefits

Inclusive benefits supporting total well-being

Job summary

Hobbsnews is seeking a Senior Manager, Machine Learning Engineering in McLean, VA. This role involves leading an Agile team dedicated to developing and optimizing machine learning applications at scale. You will be responsible for designing ML infrastructure, coding, and ensuring high-performance outcomes while driving innovation.

The ideal candidate will have substantial experience in ML systems, programming, and team leadership. A comprehensive benefits package is also offered.

Qualifications

• 8+ years experience designing data-intensive solutions.
• 4+ years experience programming with Python, Scala, or Java.
• 3+ years experience building ML systems.
• Experience leading teams in developing ML solutions.

Responsibilities

• Design and deliver ML models and components for business problems.
• Participate in ML architecture design and model training.
• Collaborate with cross-functional teams on software enhancements.
• Maintain and monitor models in production.

Skills

ML Model Design

Python

Data Pipelines

Problem Solving

Team Leadership

Education

Bachelor's Degree

Master's or Doctoral Degree

Tools

scikit-learn

PyTorch

TensorFlow

Spark

AWS

Azure

Job description

Senior Manager, Machine Learning Engineering

As a Capital One Machine Learning Engineer (MLE), you'll 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. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you’ll do in the role

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll 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.
• 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

• Bachelor’s Degree
• At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• 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 leading teams developing ML solutions
• At least 4 years of people management experience

Preferred Qualifications

• Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 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
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

Sponsorship

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

Salary Information

McLean, VA: $229,900 - $262,400 for Sr. Mgr, Machine Learning Engineering
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 candidate’s offer letter.

Benefits

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

EEO Statement

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 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.