AI/ML Architect, Technical Team Lead
General Dynamics Information Technology
AWSCloudJavaPythonPyTorchScalaScikit-LearnTensorflowVBA
Senior Machine Learning Engineer
Capital One
full-time
Posted on:
Origin: • 🇺🇸 United States
Visit company websiteSalary
💰 $144,200 - $181,000 per year
Job Level
Senior
Tech Stack
AWSAzureCloudGoogle Cloud PlatformJavaNode.jsOpen SourcePythonPyTorchScalaScikit-LearnSparkTensorflow
About the role
- Design, build, and/or deliver ML models and components that solve real-world business problems in collaboration with Product and Data Science teams.
- Inform ML infrastructure decisions using understanding of modeling techniques (choice of model, data/feature selection, training, hyperparameter tuning, dimensionality, bias/variance, 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 for 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.
- Use 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 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.
Requirements
- Bachelor’s degree
- At least 4 years of experience programming 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 frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
- At least 1 year of experience productionizing, monitoring, and maintaining models
- Preferred: 1+ years of experience building, scaling, and optimizing ML systems
- Preferred: 1+ years of experience with data gathering and preparation for ML models
- Preferred: 2+ years of experience developing performant, resilient, and maintainable code
- Preferred: Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
- Preferred: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
- Preferred: 3+ years of experience with distributed file systems or multi-node database paradigms
- Preferred: Contributed to open source ML software
- Preferred: Authored/co-authored a paper on a ML technique, model, or proof of concept
- Preferred: 3+ years of experience building production-ready data pipelines that feed ML models
- Preferred: Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
- 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, or another type of work authorization).
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