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Director, Machine Learning Engineer at Hobbsnews

Hobbsnews No longer available

Job Description

Director, Machine Learning Engineer

As a Capital One Machine Learning Engineer, you will provide technical leadership to Agile teams dedicated to productionizing machine learning applications and systems at scale. You will participate in detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms.

What you'll do in the role:
  • Deliver machine learning models and software components that solve challenging business problems in the financial services industry, working in collaboration with product, architecture, engineering, and data science teams.
  • Drive the creation and evolution of machine learning models and software that enable state of the art intelligent systems.
  • Lead large scale machine learning initiatives with the customer in mind.
  • Leverage cloud based architectures and technologies to deliver optimized machine learning models at scale.
  • Optimize data pipelines to feed machine learning models.
  • Use programming languages like Python, Scala, or Java.
  • Evangelize best practices in all aspects of the engineering and modeling lifecycles.
  • Recruit, nurture, and retain top engineering talent.
Basic Qualifications:
  • Bachelor's degree.
  • At least 10 years of experience designing and building data intensive solutions using distributed computing.
  • At least 6 years of experience programming with Python, Scala, or Java.
  • At least 5 years of people management experience.
  • At least 3 years of experience with the full machine learning development lifecycle using modern technology in a business critical setting.
Preferred Qualifications:
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
  • 3+ years of experience building production ready data pipelines that feed machine learning models.
  • 8+ years of experience within a large data intensive multi line business environment.
  • 5+ years of experience leading software engineering teams.
  • Expertise designing, implementing, and scaling complex production ready data pipelines for machine learning models.
  • Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure or platforms.
  • Ability to communicate complex technical concepts clearly to a variety of audiences.
  • Highly developed interpersonal, presentation, and communications skills.
  • Machine learning industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
  • Ability to attract and develop high performing software engineers with an inspiring leadership style.

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

Capital One is an equal opportunity employer (EOE, including disability/vet).

Typical senior pay: $181k for Computer and Information Research Scientists nationally

National salary averages
Expected senior-level
$181k
Entry
Mid
Senior
Expected
$81k Market range (10th-90th percentile) $232k

Senior roles pay 76% more than entry—experience is well rewarded.

Balanced market

High demand and responsive wages. Negotiate confidently on all fronts.

Hiring leverage
Lean candidate
Wage leverage
Moderate
Mobility
Low mobility

Who this leverage applies to

Stronger for: All experience levels, Credentialed candidates
Weaker for: Self-taught practitioners

Where to negotiate

Base salary
Sign-on bonus
Title / level
Remote flexibility
Scope & responsibility
Start date / PTO

Likely Possible Unlikely

Watch out for

Limited mobility: Few adjacent roles—switching employers is harder.

Does this path compound?

Job Growth →
High churn
Growth, flat pay
🚀 Compound
Growth + pay upside
⚠️ Plateau
Limited growth
Specialize
Experts earn more
Pay Upside →
Growth + pay upside

Both the field and your earnings can grow significantly.

+20%
10yr growth
Advanced degrees are common in this field.
Typical: Master's degree

Good time to build expertise—demand will chase supply.

Labor data: BLS 2024