Role: Data Scientist / ML Researcher – AI / ML Ops

Experience: 6–8 Years

Location: Mumbai / Ahmedabad

Core Domains: Advanced Analytics, Experimentation, & Generative AI

Core Responsibilities & Technical Tracks

Algorithm Development & Statistical Modeling Creating and optimizing predictive models using advanced statistical frameworks. Implementing classical and deep learning ML algorithms tailored to industrial use cases.

Feature Engineering & Experimentation Designing complex feature engineering pipelines to maximize signal extraction from diverse, raw datasets. Managing rigorous scientific experimentation—including reproducible research, parameter logging, and experiment tracking.

GenAI Use Cases & Evaluation R&D; and prototyping for cutting-edge GenAI applications, including LLMs, fine-tuning workflows, and RAG architectures. Defining robust evaluation criteria to assess model robustness, drift, bias, and business readiness before deployment into production MLOps pipelines.

Business Translation & Communication Translating ambiguous business problems into well-defined ML deliverables. Communicating technical results clearly to both technical and non-technical stakeholders.

Required Qualifications

- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field; Master’s or PhD preferred.
- 6–8 years of hands-on experience in data science, machine learning, or AI research.
- Strong proficiency in Python (including libraries such as scikit-learn, TensorFlow, PyTorch, LangChain, Hugging Face Transformers).
- Experience building, deploying,



and monitoring ML models in production environments (MLOps, AWS).
- Solid understanding of statistical modeling, hypothesis testing, experimental design (e.g., A/B testing), and evaluation metrics.
- Demonstrated experience with LLMs, fine-tuning, RAG, prompt engineering, and GenAI application development.
- Familiarity with data engineering concepts and tools (e.g., Spark, SQL, Airflow, Kafka).
- Robust problem-solving skills and ability to translate business problems into technical ML solutions.
- Excellent communication skills and experience presenting technical insights to diverse audiences.

Preferred Qualifications

- Published research or contributions in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ACL, CVPR).
- Experience with large-scale distributed training, model compression, quantization, or inference optimization.
- Knowledge of MLOps tooling (e.g., MLflow, Weights & Biases, SageMaker, Vertex AI).
- Background in industrial applications (e.g., manufacturing, supply chain, energy, or finance).
- Hands-on experience with vector databases (e.g., Pinecone, Weaviate, Qdrant) and retrieval systems.
- Familiarity with MLOps best practices including model monitoring, drift detection, and retraining pipelines.
- Prior experience leading cross-functional AI/ML projects or mentoring junior data scientists.

Immediate joiners are highly preferred. Skills: machine learning,a/b testing,airflow,rag,retrival system,mlops,genai,data science,ml models,kafka,aws,drift detection,llm,experiemental design,spark,sql,mlflow,prompt engineering,sagemaker,vector database,ai research,icml,generative ai,python,vertex ai,neurips

📌 ???? ????????? / ?? ?????????? – ?? / ?? ??? (Ahmedabad)
🏢 Pashet
📍 Ahmedabad