Essential Functions:

• Proficient in exploratory data analysis (EDA) using Python’s scientific libraries including NumPy, Pandas, Matplotlib, Seaborn, and scikit‑learn.
• Strong development experience in Python.
• Hands‑on experience building, training, testing, validating, and productizing machine learning models for high‑performance use cases.
• Solid understanding of core machine learning concepts, including feature engineering, model evaluation, and optimization.
• Experience implementing MLOps best practices, including model versioning, monitoring, and CI/CD pipelines for ML models.
• Hands‑on experience with AWS SageMaker for building, training, tuning, and deploying ML models.
• Hands‑on experience with to AWS services for machine learning workloads, such as S3, EC2, ECR, EKS, Lambda, CloudWatch.
• Strong understanding of model explainability frameworks such as SHAP, and the ability to interpret and explain model behavior.
• Experience debugging and analyzing false positive and false negative cases, including supporting client or production issues.
• Hands‑on experience and solid understanding of deep learning models, with exposure to frameworks such as TensorFlow, PyTorch, or Keras.
• Strong problem‑solving skills with the ability to move beyond tasks and propose improved or alternative solutions.
• Experience with ML lifecycle management and experimentation frameworks such as MLflow

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Skills

• 8+ yrs. work experience with a Bachelor’s Degree or 6+ years of work experience with a Master's or Advanced Degree in an analytical field such as computer science, statistics, finance, economics or relevant area.
• Proficient in Exploratory Data Analysis (EDA) using Python’s scientific libraries including NumPy, Pandas, Matplotlib, Seaborn, and scikit‑learn.
• Hands‑on experience and solid understanding of deep learning models, with exposure to frameworks such as TensorFlow, PyTorch, or Keras.

Additional Skills (Plus)

• Exposure to model serving and inference engines such as TensorFlow Serving, Triton Inference Server, or similar technologies.
• Experience building and maintaining Spark‑based data and feature pipelines to support ML training and inference workflows.
• Familiarity with big data platforms and storage systems such as Hadoop, EMR, and NoSQL databases.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.