Placements Alley
Capital One
Distinguished Machine Learning Engineer
Port Chester, NY,
10573
Part Time, Full Time
$63,602 per year
Posted 7 days ago
Apply Now
Actively Hiring
Center 1 (19052), United States of America, McLean, Virginia
Distinguished Machine Learning Engineer
As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams 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 serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring 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. You'll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.
In this role, you will be supporting the Bank Tech organization. You will lead development and implementation that will enable business initiatives, working with other leaders and teams across the enterprise to enable these solutions. .
What you'll do in the role:
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.
New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer
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.
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 . 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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- 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 One's 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).
Distinguished Machine Learning Engineer
As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams 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 serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring 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. You'll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.
In this role, you will be supporting the Bank Tech organization. You will lead development and implementation that will enable business initiatives, working with other leaders and teams across the enterprise to enable these solutions. .
What you'll do in the role:
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems.
- Lead large-scale ML initiatives with the customer in mind.
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
- Optimize data pipelines to feed ML models.
- Use programming languages like Python, Scala, C/C++.
- Leverage compute technologies such as Dask and RAPIDS
- Evangelize best practices in all aspects of the engineering and modeling lifecycles.
- Help recruit, nurture, and retain top engineering talent.
- 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 in C, C++, Python, or Scala.
- At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.
- At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing
- At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.
- 8+ years of experience within a large/data-intensive multi-line business environment.
- Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.
- Ability to communicate complex technical concepts clearly to a variety of audiences.
- ML industry impact through conference presentations, papers, blog posts, or open source contributions.
- Ability to attract and develop high-performing software engineers with an inspiring leadership style.
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.
New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer
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.
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 . 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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- 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 One's 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).
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FAQ's
Find the answers for the most frequently asked questions below
Are you looking for job openings with Capital One near Port Chester, NY, US? You'll find plenty of opportunities in nearby cities, including Farmingdale, NY, Cornwall, NY, Sloatsburg, NY, Islip, NY, Long Beach, NY, Lynbrook, NY, Mamaroneck, NY, Spring Valley, NY, Warwick, NY, Westbury, NY, Amityville, NY, Briarcliff Manor, NY, Harrison, NY, Northport, NY, Sea Cliff, NY, Williston Park, NY, Glen Cove, NY, Larchmont, NY, Irvington, NY, Putnam Valley, NY. These locations offer remote jobs, part-time jobs, and full-time positions with Capital One. Check out current job listings in these cities to discover more employment opportunities and local jobs hiring now in your area.
If you're searching for companies hiring now in Port Chester, NY, US, several top employers are offering a variety of job opportunities. These include Angi, U.S. Department of Defense, Allied Universal, CACI and more. Whether you're looking for entry-level positions, work-from-home jobs, or immediate hire roles, you'll find plenty of local job listings in Port Chester, NY, US.
While a degree can be beneficial, it's not strictly necessary to become a Learning Engineer. Relevant experience, strong programming skills, and a solid understanding of machine learning principles are more important. Certifications and online courses can also demonstrate competency in the field. However, a degree can still provide additional advantages in the job market.
Yes, a software engineer can transition to a machine learning engineer role by acquiring knowledge in areas such as statistics, data structures, algorithms, and machine learning principles. This often involves learning programming languages like Python and frameworks like TensorFlow or PyTorch.
A learning engineer designs, develops, and implements machine learning models and systems to improve and optimize various processes, often in the context of education or training, but can also be applied to other fields such as data analysis or artificial intelligence.
Engineering students typically learn subjects such as mathematics, physics, and computer science, as well as specialized engineering topics like mechanics, materials science, and engineering design, depending on their chosen field of study (e.g., electrical, mechanical, civil, computer, etc.). The goal is to equip them with the knowledge and skills necessary to design, build, and test engineering systems.
While a master's degree can be beneficial for a Machine Learning Engineer role, it is not strictly necessary. Many Machine Learning Engineers have a background in computer science, mathematics, statistics, or a related field. Practical experience with machine learning algorithms, programming skills, and a strong understanding of data structures and algorithms are often more important than a master's degree. However, a master's degree can provide additional knowledge and specialization in the field.
While a software engineer and a mechanical engineer are distinct professions, it is possible for a software engineer to transition to a mechanical engineering role. This would require additional education in mechanical engineering principles, as well as practical experience in mechanical design and engineering. However, the specifics of such a transition would depend on the individual's aptitude, interest, and the specific requirements of the mechanical engineering field.
Yes, a mechanical engineer can transition to a machine learning engineer. The transition requires learning programming, data structures, algorithms, and machine learning principles. However, understanding the mechanical aspects of systems can provide a unique advantage in applying machine learning to mechanical systems.
As a learning engineer, one learns about instructional design, educational technology, learning analytics, and adult learning principles to create, implement, and evaluate effective learning experiences in various educational or corporate training contexts.
Learning engineers typically study a combination of subjects in school, including:
1. Mathematics (Calculus, Linear Algebra, Statistics)
2. Computer Science (Programming, Data Structures, Algorithms)
3. Electrical Engineering (Circuits, Systems, Signals & Systems)
4. Machine Learning (Neural Networks, Reinforcement Learning, Deep Learning)
5. Software Engineering (Software Development, Design Patterns, Agile Methodologies)
6. Artificial Intelligence (AI Principles, Robotics, Natural Language Processing)
7. Data Science (Data Mining, Data Visualization, Machine Learning Algorithms)
8. Human-Computer Interaction (UX Design, Usability, Accessibility)
These subjects provide a strong foundation for a learning engineer to develop, implement, and evaluate machine learning models and systems.
A learning engineer is a professional who designs, develops, and implements educational technology solutions to enhance learning experiences and improve educational outcomes. They often work in educational institutions or learning technology companies, using their skills in instructional design, technology, and data analysis to create effective learning environments.