Staff Machine Learning Scientist

Visa; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Visa in Bengaluru is seeking a senior ML engineer with 8+ years of experience in analytics and software development to design, train, and productionize machine learning models. The role emphasizes end-to-end ML lifecycle, feature engineering, and model evaluation.

The candidate will apply Python data science tools (NumPy, Pandas, Matplotlib, Seaborn), work with AWS SageMaker and big data platforms (S3, EMR), and contribute to model explainability and monitoring using SHAP and related frameworks.

Qualifications

• 8+ years of work experience in analytics or ML with a Bachelor’s Degree.
• Proficient in Python data science stack and ML libraries.
• Experience with ML lifecycle management, experimentation frameworks, and model deployment.

Responsibilities

• (Not explicitly stated in HTML)

Skills

Python stack (NumPy, Pandas)

Data Visualization (Matplotlib, Seabor

ML algorithms & feature engineering

AWS SageMaker

Spark / Hadoop / EMR

TensorFlow / PyTorch / Keras

MLOps / CI/CD for ML

Model explainability (SHAP)

EDAs and model evaluation

Big data pipelines

Education

Bachelor's Degree

Master's Degree

Tools

AWS SageMaker

S3 / EC2 / Lambda

TensorFlow

PyTorch

Spark

Hadoop/EMR

Kubernetes

Job description

• Proficient in exploratory data analysis (EDA) using Python’s scientific libraries including NumPy, Pandas, Matplotlib, Seaborn, and scikit‑learn.
• 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

Qualifications

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. 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.