Machine Learning Engineer 4
$179k - $205k • McLean, VA • Full-time
Posted 2d ago
Job Location
McLean, VA
Also open in New York, NY, Cambridge, MA, Chicago, IL
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Capital One is seeking Machine Learning Engineers passionate about leveraging cutting-edge open-source frameworks, advanced algorithms, and emerging technologies to join their team. In this role, you will have the opportunity to be at the forefront of driving major AI transformations and scaling production models across the company. You will collaborate with product and data science teams to design, build, and deliver ML models and components that solve real-world business problems. This role involves performing various ML engineering activities, including informing ML infrastructure decisions, solving complex problems through code, and automating tests and deployment.
Responsibilities
- Design, build, and deliver ML models and components to solve business problems.
- Inform ML infrastructure decisions based on understanding of ML modeling techniques.
- Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
- Collaborate with cross-functional Agile teams to create and enhance software for big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures and platforms for optimized ML model delivery at scale.
- Construct optimized data pipelines to feed ML models.
- Leverage CI/CD best practices, including test automation and monitoring, for successful deployment of ML models and application code.
- Ensure code is well-managed for reduced vulnerabilities, models are well-governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
Requirements
- Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field.
- At least 4 years of experience programming with Python, Java, Golang, or C++.
- At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn).
- At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data.
- At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure).
- At least 2 years of experience using Kubernetes to manage large scale containerized ML software systems.
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field (preferred).
- 3+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
- 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD (preferred).
- 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, alarms, and incident response plans (preferred).
- 3+ years of experience working with various Machine Learning techniques, model types, model architectures, training concepts, and model evaluation (preferred).
- 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models (preferred).
- 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation (preferred).
- Authored/co-authored a paper on an ML technique, model, or proof of concept (preferred).
Benefits
- Performance based incentive compensation (cash bonus(es) and/or long term incentives)
- Comprehensive, competitive, and inclusive set of health, financial and other benefits that support total well-being.