GEN AI and Machine Learning Engineer Primus Global Technologies

3.0 - 5.0 years

0 - 3 Lacs

Hyderabad, Chennai, Bengaluru

Hybrid

Role & responsibilities Preferred candidate profile Skills (must have) Bachelor's or masters degree in Computer Science, Data Science, Engineering, or a related field. Experience on Agentic AI/Framework and Platform. Strong programming skills in languages such as Python, SQL/NoSQL Experience in working with OpenAI Models. Experience in TensorFlow, PyTorch, PySpark. Good experience in Azure Exposure to Gen AI, Vector DB/Embeddings, LLM, RAG, Grounding with external APIs Skills (good to have) Experience with MLOps, MLFlow, Kubeflow, CI/CD Pipeline etc. Experience in Flask/Django is a bonus Knowledge of math, probability, and statistics. Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms. 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.

Posted 2 months ago

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AI ML Python Developer Einfochips

3.0 - 4.0 years

3 - 4 Lacs

Ahmedabad, Gujarat, India

On-site

Technical Skills Experience: Programming Languages: Proficiency in Python for AI/ML model development.. Machine Learning Deep Learning: Hands-on experience with TensorFlow and PyTorch for model training and deployment. Data Science Analytics: Strong knowledge of scikit-learn, NumPy, and pandas for data processing and manipulation. Natural Language Processing (NLP): Expertise in text preprocessing, tokenization, embeddings, and NLP techniques. Large Language Models (LLMs): Experience with transformer models like GPT, BERT, T5, and LLaMA, including fine-tuning and prompt engineering. Retrieval-AugmentedGeneration (RAG): Knowledge of RAG pipelines and experience with vector databases such as FAISS, Pinecone, or Chroma. Multi-Agent Systems: Familiarity with multi-agent frameworks like LangChain, LangGraph, or CrewAI. Data Handling Databases: Strong skills in data preprocessing, feature engineering, and working with SQL/NoSQL databases. API Development: Experience in building and deploying APIs using FastAPI, Flask, or Django. Version Control Collaboration: Strong understanding of Git/GitHub for version control and team collaboration. Hugging Face: Experience with Hugging Face for model training, deployment, and inference.

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