Senior ML Engineer, MLX: Scale Production Models

MFS Investments; Cambridge (MA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One in Cambridge, MA is seeking a Machine Learning Engineer 4 to design, deploy, and scale production ML models in a fast-paced, collaborative setting. You will work with Product and Data Science teams to build ML solutions, optimize architectures, and maintain models in production using cloud platforms and modern ML frameworks.

The role requires 4+ years in ML, strong Python/Java, PyTorch or TensorFlow, and experience with distributed systems (Spark/Ray) and Kubernetes for scalable

Qualifications

• Bachelor's degree or higher in CS, ML, or related quantitative field.
• 4+ years Python/Java/Golang/C++ experience.
• 4+ years ML with PyTorch or TensorFlow and Pandas/NumPy/Scikit-learn.
• 4+ years distributed systems experience (Spark, Ray).
• 2+ years deploying ML in production on cloud with Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components with Product/Data Science teams.
• Inform infrastructure decisions; select models, data, and features; train and validate models.
• Write production-grade code; test, deploy, and monitor ML models.
• Collaborate in cross-functional Agile teams to enable big data/ML apps.
• Retrain, maintain, and monitor models in production across cloud platforms.
• Construct data pipelines to feed ML models; ensure CI/CD and governance.

Skills

Python

Java

Golang

C++

Machine Learning

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Cloud Platforms

Model Deployment

Education

Bachelor's degree in CS or related field

Master's or Doctoral preferred

Tools

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One in Cambridge, MA is seeking a Machine Learning Engineer 4 to design, deploy, and scale production ML models in a fast-paced, collaborative setting. You will work with Product and Data Science teams to build ML solutions, optimize architectures, and maintain models in production using cloud platforms and modern ML frameworks.

The role requires 4+ years in ML, strong Python/Java, PyTorch or TensorFlow, and experience with distributed systems (Spark/Ray) and Kubernetes for scalable