Python ML Engineer

Company: Research Fox Consulting Pvt Ltd

Website: Visit Website

Business Type: Startup

Company Type: Product & Service

Business Model: B2B

Funding Stage: Series C

Industry: Consulting

Salary Range: ₹ 10-30 Lacs PA

Job Description

About the Role We are seeking a Python ML Engineer to join our dynamic AI/ML Engineering team at Korn Ferry Digital. This role centers on ML engineering, API engineering, deployment, and release within a machine learning SaaS product delivery team. You will be involved in developing and maintaining APIs that serve ML models and data services, focusing on performance, scalability, and reliability. If you’re passionate about bridging the gap between data science and production-grade software engineering, and believe you have the hands-on technical and engineering skills for this, please apply to this role.

Key Responsibilities

• API Development & Maintenance o Design, build, and maintain RESTful APIs using Python for ML applications.
• Integration of machine learning capabilities such as vectorization, ML inference, embedding computation, etc into services
• Working with multi-paradigm product architectures such as REST, gRPC, GraphQL, message based architectures Implement best practices for endpoint creation, versioning, pagination, and error handling.
  
  

Deployment & Release

• Containerize applications using Docker to ensure consistent deployments across environments.
• Manage configurations and ensure deployability and maintainability across environments
• Work with AWS or Azure services to deploy, manage, and scale cloud-based solutions
  
  

Performance & Scalability

• Monitor API performance metrics (throughput, latency) and optimize for better user experiences.
• Use best practices in MLOps for data and model monitoring and evaluations of traditional ML models and GenAI based applications
• Implement load balancing, caching, and other strategies to handle high-tra ic scenarios.
  
  

Collaboration & Teamwork

• o Work with data scientists to integrate ML models into production-grade applications.
• o Partner with cross-functional teams to ensure seamless end-to-end system delivery.
  
  

Documentation & Testing

• Write clear, concise technical documentation and maintain code repositories.
• Develop and run unit tests, integration tests, and performance tests for robust releases.