Senior ML Engineer / Data Science Platform Engineer

Experience:7+ Year

Role: Senior ML Engineer / Data Science Platform Engineer

Duration: 6 Months contract

Location: 100% Remote

Shift:

• Core Hours: 9:30-11:30 PM
• Core Hours: 3:30 - 5:30 AM
• Remaining working hours are flexible/floating, based on project and team requirements

Position Summary

We are seeking a Senior ML Engineer / Data Science Platform Engineer to design, build, and manage end-to-end data science and machine learning pipelines. The role will focus on productionizing ML models, developing automated ML workflows, building experimentation platforms, and enhancing existing models through feature engineering and hyperparameter tuning.

The ideal candidate will have strong Python, AWS SageMaker, Databricks, ML engineering, data science, and system design experience, with the ability to take ML solutions from experimentation through production and generate reliable predictions for end users.

Key Responsibilities

• Design, develop, and manage end-to-end data science and machine learning pipelines from data preparation and experimentation through model deployment and prediction.
• Build and maintain automated ML pipelines and workflows for training, validation, deployment, monitoring, and retraining.
• Develop and enhance the organization's ML platform using AWS SageMaker as the current machine learning platform.
• Leverage Databricks for data processing, experimentation, model development, and scalable ML workflows.
• Develop production-grade Python code for machine learning applications, data processing, automation, and pipeline orchestration.
• Work with inherited/existing ML models to understand requirements, identify improvement opportunities, and enhance model performance.
• Apply feature engineering, model optimization, and hyperparameter tuning to improve model accuracy and business outcomes.
• Demonstrate strong understanding of machine learning algorithms, statistical concepts, model evaluation, and end-to-end ML lifecycle.
• Design and develop scalable experimentation platforms that enable data scientists and ML engineers to efficiently test models, features, and experiments.
• Contribute to system architecture and design for ML platforms, experimentation frameworks, and production data science systems.
• Build solutions that generate and serve ML predictions for end users while ensuring scalability, reliability, and maintainability.
• Collaborate with data scientists, software engineers, product teams, and business stakeholders to translate requirements into production-ready ML solutions.
• Develop reusable frameworks and components that streamline model development and deployment.
• Implement appropriate practices for model validation, versioning, deployment, monitoring, and lifecycle management.
• Own and enhance the Bill Data Plugin, a product that can be installed by employees to enable SQL-based data querying and analysis.
• Enhance the plugin's capabilities to support business use cases such as identifying customers who have complained about or mentioned competitors.
• Ensure ML and data products are reliable, scalable, secure, and easy for internal users to consume.

Required Skills

• 7+ years of experience in Machine Learning Engineering, Data Science, ML Platform Engineering, or a closely related field.
• Strong programming experience in Python.
• Hands-on experience with AWS SageMaker and production ML platforms.
• Strong experience with Databricks and modern data/ML workflows.
• Proven experience building and managing end-to-end ML pipelines.
• Strong understanding of machine learning algorithms and model development lifecycle.
• Experience with feature engineering and hyperparameter tuning.
• Experience taking ML models from experimentation to production deployment.
• Strong system design and architecture skills, particularly for ML/data platforms.
• Experience building automated ML workflows and experimentation platforms.
• Ability to work with and enhance existing/inherited machine learning models.
• Strong understanding of model evaluation, experimentation, and generating predictions for end users.
• Experience working with SQL and data platforms.

Share resume to:

Vishal Kumar

[email protected]/[email protected]