Machine Learning Engineer - Python

Key Responsibilities :

- Develop, train, and deploy machine learning models, focusing on performance, scalability, and maintainability.

- Build and manage end-to-end ML pipelines, including data ingestion, transformation, training, evaluation, and deployment.

- Work with big data processing pipelines to handle large-scale datasets for training and inference.

- Generate and prepare datasets in formats such as TFRecords, LMDB, or similar formats.

- Perform model evaluation, benchmark various versions on different datasets, and generate comprehensive reports.

- Conduct data analysis and visualization to identify trends, outliers, and areas for improvement.

- Debug issues related to data processing, model training, and Python scripts.

- Utilize development tools like Git/Gerrit, static/dynamic analysis tools, code coverage, and performance profiling tools.

Must-Have Skills :

- Proficient in Python programming language.

- Experience with TensorFlow or Keras frameworks.

- Hands-on experience in developing and maintaining ML pipelines.

- Strong debugging skillsespecially around Python errors, data ingestion, and compilation issues.

- Good understanding of data formats used in ML model training.

- Exposure to model benchmarking and performance comparison.

Good-to-Have Skills :

- Experience in the Vision Domain (e.g., image classification, object detection).

- Exposure to synthetic data generation for training machine learning models.

- Experience building scripts for data analysis, annotation, or automated filtering of image or text data.

- Familiarity with data versioning practices and tools.

- Experience with tools for data annotation, AI data visualization, and labeling.

- Capability to identify failure classes or problematic data patterns and report actionable insights.