Data / ML Platform Engineer (Python batch pipelines)

About

Data / ML Platform Engineer (Python batch pipelines): Owns the Python evaluation pipelines that run model benchmarks, load datasets from cloud storage, call LLM APIs, and write structured results to MongoDB (resumable batch jobs).

Role Descriptions

Angular and Dot Net Experience Required. Should have experience working as Full stack developer in Angular Dot Net agile scrum programs experience with great communication and team management skills.

Roles Responsibilities

The Full stack Developer will have the following responsibilities:

• Produce minimal and clean code with more reusability.
• Review and fix code by other developers in the team.
• Following and implementing the latest coding trends, tricks, and best practices along with conveying the message to the other team members.
• Develop and implement low-latency, highly performant server-side components by writing efficient, reusable, and maintainable code.
• Leverage available tools and systems to proactively identify and resolve defects.
• Good knowledge on Dot Net, Angular, Flux.
• Implement effective security protocols and data protection measures.

Qualifications

• Bachelors Degree and 5-7 years of experience as a developer.
• 6 years of experience on web development including both Angular.
• Expert knowledge of responsive design, media queries and mobile CSS frameworks.
• Cloud Development (Azure or Aws).
• Generic Managerial Skills.
• Good communication skills and good in team management.

Assignment Details

• Education: Bachelors Degree
• Start date: 16-Aug-2021
• Duration of assignment: 6 Months
• Work Location: USA
• Rates payable to vendor: $58 per hour

Keywords

Angular, Dot Net

Prescreening Questionnaire

1. Have you worked in Agile/Scrum projects?
2. Has the associate worked as FullStack Developer (Dot Net and Angular) in past four years?

Essential Skills

Data / ML Platform Engineer (Python batch pipelines): Owns the Python evaluation pipelines that run model benchmarks, load datasets from cloud storage, call LLM APIs, and write structured results to MongoDB (resumable batch jobs).