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Data Scientist: AI/ML Engineer
2-6 years
₹ 4 - 28L/yr (AmbitionBox estimate)
Noida
Data Scientist: AI/ML Engineer
IBM
posted 11d ago
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Job Description
We are seeking an experienced AI Engineer to join the Asset Engineering team. In this role, you will be responsible for building innovative AI-powered solutions that integrate with various systems and applications. You will also be working with the broader team to build, analyse and improve the AI solutions. You will be working primarily in one of our key solutions called the IBM Inspection Suite. The set of products enables clients to use AI to inspect parts and equipment for defects or anomalies using models such as Yolo3 that are trained in formats compatible with mobile devices (iPhones, Androids) such as CoreML and Tensorflow Lite. You will directly collaborate with the CTO of the asset and the technical team who architect, develop, enhance, and govern the asset.
- Machine Learning and GenAI: Strong understanding of machine learning and GenAI concepts. Awareness of ethical implications in GenAI, including bias, fairness, and privacy
- Python and Data Science Libraries: Proficiency in Python and relevant data science libraries (e.g., NumPy, Pandas, scikit-learn). Practice on Graph database and Vector DB
- Computer Vision: Yolo, object detection, classification models. Ideally segmentation and anomaly detection
- Container Development: Solid hands-on experience in microservices development, Relational DB development, K8S and/or Redhat OpenShift, especially with AWS
- Large Language Models: Familiarity with LLMs, including their architectures, capabilities, and limitations. Skill in crafting effective prompts to guide LLMs and obtain desired outputs. Ability to handle and prepare data for analysis, including data cleaning, normalization, and feature engineering
- Experience in converting model formats to CoreML and Tensorflow Lite
- Experience on PostgreSQL and Redis DB (or other service caching mechanism)
- AI agent/agentic workflow concepts
Employment Type: Full Time, Permanent
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Anonymous · Data Science & Analytics
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Good colleagues. Friendly environment . Hybrid model
- Salary - Excellent
Heard too much sack happening for those in bench
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