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  • Emplois similaires à : Founding Lead Machine Learning Engineer
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Machine Learning Engineer (AI Foundations)Capital One National Association • New York, New York, United States
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Machine Learning Engineer (AI Foundations)

Capital One National Association
  • US
    New York, New York, United States
  • US
    New York, New York, United States
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À propos

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.
Capital One is accelerating the adoption of state of the art AI research to create simpler, safer banking experiences for over 100 million customers. The AI Foundations team spearheads this mission by developing advanced LLMs and autonomous agentic systems capable of complex reasoning and real world problem solving. Their comprehensive research framework prioritizes foundational model architecture, operational efficiency, and responsible AI practices to ensure all systems are trustworthy and scalable.
What You’ll Do: 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 2 years of experience designing and building data‑intensive solutions using distributed computing (Internship experience does not apply)
At least 2 years of experience programming with Python, Scala, or Java
At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit‑learn, PyTorch, Dask, Spark, or TensorFlow)
Preferred Qualifications:
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
1+ years of experience working with large code bases in a team environment
1+ years of experience with distributed file systems or multi‑node database paradigms
Contributed to open source ML software
1+ years of experience building production‑ready data pipelines that feed ML models
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion
At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).
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.
McLean, VA: $135,600 – $154,800 for Machine Learning Engineer
New York, NY: $148,000 – $168,900 for 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 Capital One Careers website. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.
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 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.
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  • New York, New York, United States

Compétences linguistiques

  • English
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