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Epsilon Data Management
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Re:Sources India Gurgaon IT

Re:Sources India Gurgaon IT

Epsilon Data Management

3 - 6 years

5 - 8 Lacs

Gurugram

Posted:4 hours ago| Platform:

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Skills Required

Procurement Computer science jQuery Django Machine learning Healthcare HTML Risk management SQL Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Overview Title GEN AI and Machine Learning Engineer Skills (must have) Bachelors or master s degree in Computer Science, Data Science, Engineering, or a related field. Experience on Agentic AI/ Frameworks Strong programming skills in languages such as Python, SQL etc. Build analytical approach based on business requirements, then develop, train, and deploy machine learning models and AI algorithms Exposure to GEN AI models such as OpenAI, Google Gemini, Runway ML etc. Experience in developing and deploying AI/ML and deep learning solutions with libraries and frameworks, such as TensorFlow, PyTorch, Scikit-learn, OpenCV and/or Keras. Knowledge of math, probability, and statistics. Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms. Exposure in developing API using Flask/Django. Good experience in cloud infrastructure such as AWS, Azure or GCP Exposure to Gen AI, Vector DB/Embeddings, LLM (Large language Model) Skills (good to have) Experience with MLOps: MLFlow, Kubeflow, CI/CD Pipeline etc. Good to have experience in Docker, Kubernetes etc Exposure in HTML, CSS, Javascript/JQuery, Node.js, Angular/React Experience in Flask/Django is a bonus Responsibilities Collaborate with software engineers, business stake holders and/or domain experts to translate business requirements into product features, tools, projects, AI/ML, NLP/NLU and deep learning solutions. Develop, implement, and deploy AI/ML solutions. Preprocess and analyze large datasets to identify patterns, trends, and insights. Evaluate, validate, and optimize AI/ML models to ensure their accuracy, efficiency, and generalizability. Deploy applications and AI/ML model into cloud environment such as AWS/Azure/GCP etc. Monitor and maintain the performance of AI/ML models in production environments, identifying opportunities for improvement and updating models as needed. Document AI/ML model development processes, results, and lessons learned to facilitate knowledge sharing and continuous improvement.

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