Job description

Key Responsibilities:

Design and develop ML, NLP, and GenAI models to solve real-world business problems.
Build, train, and fine-tune AI models using Python and leading ML frameworks.
Leverage Azure and GCP AI/ML services for scalable and production-ready deployment.
Develop and integrate APIs for real-time model inference and intelligent decision-making.
Handle large-scale datasets to extract insights and drive data-informed strategies.
Work collaboratively with Data Engineers, Software Developers, and Product Teams to integrate AI solutions into existing products and platforms.
Implement and maintain CI/CD pipelines for model development and deployment automation.
Follow Agile methodologies and adhere to software engineering best practices.
Stay current with AI/ML innovations, including LLMs and GenAI advancements, and incorporate them into ongoing projects.
Lead research initiatives and contribute to innovative solution development.
Provide mentorship to junior team members and ensure knowledge sharing.
Continuously monitor and optimize models for performance and scalability in production.

Required Skills & Qualifications:

Proficiency in Python and experience with TensorFlow, PyTorch, or Scikit-learn.
In-depth understanding of NLP techniques, such as transformers, embeddings, and text analytics.
Proven expertise in Generative AI models (e.g., GPT, BERT, LLMs).
Strong experience with Azure AI/ML services (Azure ML, Cognitive Services, Databricks).
Hands-on experience with GCP AI/ML tools such as Vertex AI, BigQuery ML, and TensorFlow on GCP.
Proficient in building and integrating REST APIs for ML model inference.
Familiarity with CI/CD practices tailored for ML environments.
Strong grasp of software engineering principles (version control, modularity, testing).
Experience working in Agile development environments.
Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
Solid background in statistical analysis, data mining, and data visualization.

Preferred Qualifications:

Experience with MLOps and end-to-end model lifecycle automation.
Knowledge of vector databases and Retrieval-Augmented Generation (RAG).
Familiarity with big data processing frameworks such as Apache Spark and Hadoop.
Ability to communicate complex technical concepts to non-technical stakeholders.
Exposure to Graph Neural Networks (GNNs) and recommendation engines.
Understanding of AutoML frameworks and advanced hyperparameter tuning techniques.

Job Type: Contractual / Temporary

Pay: ₹700.00 - ₹900.00 per hour

Schedule:

Experience:

Work Location: In person

Job Type: Contractual / Temporary

Pay: ₹500.00 - ₹700.00 per hour

Benefits:

Schedule:

Supplemental Pay:

Work Location: In person

Data Scientist (3-5 years)

Data Scientist