Machine Learning Engineer

Position: Machine Learning Engineer

Experience:25 Years

Location:On-Site

Build, train, optimize and deploy machine learning models while managing data pipelines and improving model accuracy for business applications.

• Train ML/DL models using TensorFlow/PyTorch.
• Preprocess datasets and perform model tuning.
• Deploy models using Docker/FastAPI on cloud platforms.
• Monitor production accuracy and retrain based on new inputs.
• Research new AI approaches and improve pipeline efficiency.

Software & Tools: Jira, Trello, ClickUp, Asana, Monday.com

Documentation: Confluence, Notion, Google Workspace, MS Office

Diagramming: Draw.io, Lucidchart, Figma (flows/UI mapping)

CRM (Pre-Sales): HubSpot, Zoho, Salesforce (basic use)

Technical Understanding:

• REST/GraphQL APIs for integration
• SQL basics for data extraction & reports
• Cloud (AWS/Azure/GCP) deployment familiarity
• AI/ML concepts LLMs, predictive models, training workflows
• SDLC & MLOps awareness
• Basic understanding of web stack (HTML/CSS/JS)