High-Powered Machine Learning Engineer

4 days ago

Bikaner, Rajasthan, India beBeeDataScience Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title: Senior AI/ML Data Scientist

We are seeking a seasoned Senior AI/ML Data Scientist to spearhead our team's data-driven initiatives.

About the Role:

  • This is a senior-level position that demands 5-6 years of hands-on experience in AI/ML and data science.
  • The ideal candidate will have a strong background in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face).
  • They will also have practical experience with LLMs, embeddings, vector databases, and RAG pipelines.
  • Proven expertise in recommendation systems, personalization, and predictive modeling is essential.
  • Familiarity with APIs & microservices (FastAPI, Django REST, Flask) and cloud ML deployments (Azure/AWS/GCP) is a plus.

Responsibilities:

  • Design, develop, and deploy end-to-end AI/ML solutions that drive business value.
  • Lead projects involving LLMs, NLP, recommendation engines, and predictive models that meet high-quality standards.
  • Build, optimize, and maintain data pipelines and APIs for ML services that ensure scalability and reliability.
  • Deploy and scale ML models on cloud platforms with containerization and CI/CD.
  • Collaborate with cross-functional teams to deliver production-ready AI systems that exceed stakeholder expectations.
  • Ensure model performance, scalability, monitoring, and explainability.
  • Mentor junior team members and contribute to best practices in MLOps that promote knowledge sharing and growth.

Requirements:

  • Bachelor's/Master's in Computer Science, Data Science, or related field.
  • Strong expertise in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face).
  • Practical experience with LLMs, embeddings, vector databases, and RAG pipelines.
  • Proven background in recommendation systems, personalization, and predictive modeling.
  • Proficiency in SQL/NoSQL databases and data pipeline development.
  • Familiarity with APIs & microservices (FastAPI, Django REST, Flask).
  • Experience with cloud ML deployments (Azure/AWS/GCP).
  • Good knowledge of Docker, Kubernetes, Git, CI/CD for production ML.

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