The Data Scientist is a senior, technical leadership role requiring 812 years of experience, focused on advanced Machine Learning and Generative AI solutions.

Located in Bangalore, Pune, or Trivandrum, the incumbent will be responsible for the end-to-end design, development, and deployment of cutting-edge models, including LLMs, GANs, and VAEs.

This position demands a Collaborative and team-oriented mindset and the ability to lead the team and architect complex solutions.

Job Summary :

We are seeking a highly experienced Data Scientist (812 years) with deep expertise in statistical analysis, predictive modeling, and state-of-the-art AI techniques, particularly Generative AI. The ideal candidate must possess strong proficiency in ML frameworks (TensorFlow, PyTorch, Keras), Python, and have hands-on experience in architecting and deploying models like GANs, VAEs, and LLMs.

Key responsibilities include experimenting with cutting-edge AI techniques, leading the team, ensuring model scalability using big data and cloud technologies (AWS, GCP, Azure), and translating complex problem spaces into robust, creative, and critically evaluated technical solutions.

Key Responsibilities and Generative AI Deliverables

Advanced Model Development and Deployment :

- Design, develop, and deploy advanced machine learning models, specializing in generative AI models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), LLMs (Large Language Models), and autoregressive models.

- Implement models using core machine learning frameworks and libraries (e. g., TensorFlow, PyTorch, Keras, Scikit-learn).

- Ensure model scalability and production readiness, leveraging big data technologies and cloud platforms (e. g., AWS, GCP, Azure) for deployment.

Research and Innovation :

- Experiment with state-of-the-art techniques in AI and Generative AI to solve complex business problems and continually improve the performance and robustness of existing solutions.

- Utilize Experience with generative models (GANs, VAEs, etc. ) and natural language processing (NLP) techniques for advanced text, image, or synthetic data generation tasks.

Technical Leadership and Architecture :

- Demonstrate Experience in architecting end-to-end ML and data science pipelines, ensuring efficiency, scalability, and adherence to MLOps principles.

- Take a leading role in guiding and mentoring junior team members, fostering a Collaborative and team-oriented mindset.

Analytical Foundation and Tools :

- Apply Expertise in statistical analysis, data mining, and predictive modelling to interpret data, validate hypotheses, and evaluate model performance metrics.

- Maintain Proficiency in programming languages such as Python (primary), R, or C/C++ for development and scripting.

- Apply Strong problem-solving skills and the ability to think critically and creatively to address ambiguity in novel problem domains.

Mandatory Skills & Qualifications

- Experience : 812 years in Data Science/Machine Learning.

- AI/ML Frameworks : Strong knowledge of machine learning frameworks and libraries (TensorFlow, PyTorch, Keras, Scikit-learn).

- Generative AI : Experience with generative models (GANs, VAEs, LLMs) and natural language processing (NLP).

- Programming/Stats : Proficiency in programming languages such as Python and Expertise in statistical analysis, data mining, and predictive modelling.

- Architecture : Experience in architecting and leading the team.

- Cloud/Big Data : Familiarity with big data technologies and cloud platforms (AWS, GCP, Azure).

Preferred Skills

- Deep experience in MLOps tools (e.g., MLflow, Kubeflow) and containerization (Docker, Kubernetes).

- Publications in peer-reviewed journals or major AI conferences (e.g., NeurIPS, ICML).

- Experience with reinforcement learning or causality inference.

- Specific domain expertise related to the company's sector (e.g., Finance, Healthcare).