iHire
Senior Machine Learning Engineer (Intelligent Foundations & Experiences)
As a Capital One Machine Learning Engineer (MLE), you will join an Agile team dedicated to productionizing machine learning applications and systems at scale. You will design, build, and maintain ML models and components, perform detailed technical design and development, and ensure high availability and performance of our ML applications. Your work will involve collaborating with Product, Data Science, Ops, and Data Engineering to solve real‑world business problems, and continuously applying the latest innovations and best practices in machine learning engineering.
What You’ll Do In The Role
Design, build, and/or deliver ML models and components that solve real‑world business problems, collaborating with Product and Data Science teams.
Inform ML infrastructure decisions using your understanding of modeling techniques and issues such as model choice, data and feature selection, training, hyperparameter tuning, dimensionality reduction, bias/variance, and validation.
Write and test application code, develop and validate ML models, and automate 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 platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code is well‑managed, models are governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
Use programming languages such as Python, Scala, or Java.
Basic Qualifications
Bachelor’s degree.
At least 4 years of programming experience with Python, Scala, or Java (internship experience does not apply).
At least 3 years of experience designing and building data‑intensive solutions using distributed computing.
At least 2 years of on‑the‑job experience with an industry‑recognized ML framework (scikit‑learn, PyTorch, Dask, Spark, or TensorFlow).
At least 1 year of experience productionizing, monitoring, and maintaining models.
Preferred Qualifications
1+ years of experience building, scaling, and optimizing ML systems.
1+ years of experience with data gathering and preparation for ML models.
2+ years of experience developing performant, resilient, and maintainable code.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
3+ years of experience with distributed file systems or multi‑node database paradigms.
Contributed to open source ML software.
Authored or co‑authored a paper on an ML technique, model, or proof of concept.
3+ years of experience building production‑ready data pipelines that feed ML models.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
Compensation McLean, VA: $158,600 – $181,000 for Senior Machine Learning Engineer New York, NY: $173,000 – $197,400 for Senior Machine Learning Engineer Richmond, VA: $144,200 – $164,600 for Senior Machine Learning Engineer
Benefits and Other Information Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well‑being. This role is eligible for performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI).
Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.
Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws.
Capital One does not sponsor employment authorization or provide immigration‑related support for this position.
This role is expected to accept applications for a minimum of 5 business days. No agencies please.
Applicants requiring accommodations must contact Capital One Recruiting at the provided phone number or email. All personal information will be kept confidential and used only as required for accommodations.
#J-18808-Ljbffr
What You’ll Do In The Role
Design, build, and/or deliver ML models and components that solve real‑world business problems, collaborating with Product and Data Science teams.
Inform ML infrastructure decisions using your understanding of modeling techniques and issues such as model choice, data and feature selection, training, hyperparameter tuning, dimensionality reduction, bias/variance, and validation.
Write and test application code, develop and validate ML models, and automate 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 platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code is well‑managed, models are governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
Use programming languages such as Python, Scala, or Java.
Basic Qualifications
Bachelor’s degree.
At least 4 years of programming experience with Python, Scala, or Java (internship experience does not apply).
At least 3 years of experience designing and building data‑intensive solutions using distributed computing.
At least 2 years of on‑the‑job experience with an industry‑recognized ML framework (scikit‑learn, PyTorch, Dask, Spark, or TensorFlow).
At least 1 year of experience productionizing, monitoring, and maintaining models.
Preferred Qualifications
1+ years of experience building, scaling, and optimizing ML systems.
1+ years of experience with data gathering and preparation for ML models.
2+ years of experience developing performant, resilient, and maintainable code.
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform.
Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
3+ years of experience with distributed file systems or multi‑node database paradigms.
Contributed to open source ML software.
Authored or co‑authored a paper on an ML technique, model, or proof of concept.
3+ years of experience building production‑ready data pipelines that feed ML models.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
Compensation McLean, VA: $158,600 – $181,000 for Senior Machine Learning Engineer New York, NY: $173,000 – $197,400 for Senior Machine Learning Engineer Richmond, VA: $144,200 – $164,600 for Senior Machine Learning Engineer
Benefits and Other Information Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well‑being. This role is eligible for performance‑based incentive compensation, which may include cash bonus(es) and/or long‑term incentives (LTI).
Capital One is an equal‑opportunity employer (EOE, including disability/veteran) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.
Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws.
Capital One does not sponsor employment authorization or provide immigration‑related support for this position.
This role is expected to accept applications for a minimum of 5 business days. No agencies please.
Applicants requiring accommodations must contact Capital One Recruiting at the provided phone number or email. All personal information will be kept confidential and used only as required for accommodations.
#J-18808-Ljbffr