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Position: Machine Learning Engineer
Experience: 2–5 Years
Location: On-Site
Role OverviewBuild, train, optimize and deploy machine learning models while managing data pipelines and improving model accuracy for business applications.
Core Responsibilities- 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)
Key Skills
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