Job Description : Responsibilities :
- Provide data science and AI expertise to design, build, and deliver scalable ML and deep learning solutions.
- Work extensively with tabular data to develop predictive models, perform feature engineering, and optimize performance for real-world applications.
- Apply conventional machine learning techniques (e.g., regression, classification, ensemble methods) alongside advanced deep learning methods.
- Build and optimize deep learning models for structured and unstructured data, including text and audio.
- Lead development of solutions for audio data, including classification, recognition, and signal processing tasks.
- Design, fine-tune, and deploy LLMs (Large Language Models), SLMs (Small Language Models), and other Generative AI solutions for diverse business applications.
- Translate business problems into well-structured ML / AI problems and deliver actionable insights.
- Deploy production-grade models with a focus on efficiency, scalability, and maintainability.
- Collaborate with cross-functional teams including product managers, engineers, and domain experts to deliver high-impact projects.
- Mentor junior data scientists and interns, fostering innovation and best practices.
Qualification Requirements :
Educational :
Bachelor's degree with at least 7 years of experience or Master's with at least 4 years of experience in Data Science / ML / AI.Preferred to have degree from a Tier-1 / 2 institute (IIT / IISc / NITs if studied in India) or a globally top-ranked university (as per QS).Technical :
Proven expertise working with large-scale tabular data and building machine learning models.Strong knowledge of conventional ML algorithms (tree-based models, SVMs, clustering, etc.).Hands-on experience with deep learning frameworks such as TensorFlow / PyTorch.Mandatory expertise in LLMs, SLMs, and Generative AI, including fine-tuning, prompt engineering, and deployment.Proficiency in Python and libraries such as scikit-learn, pandas, NumPy.Exposure to model deployment frameworks and tools (ONNX, Triton, TensorRT, FastAPI, etc.).Familiarity with cloud platforms (Azure / GCP) for training and deploying ML solutions.Experience with Databricks is a plus.Strong understanding of MLOps practices, reproducibility, and model monitoring.Other :
Excellent written and verbal communication skills in English.Demonstrated experience working collaboratively in cross-functional teams.Ability to balance research and production priorities while meeting deadlines.Passionate about applying AI / ML to solve diverse real-world problems, especially at the intersection of GenAI and enterprise AI adoption.(ref : hirist.tech)