Lead Data Scientist

` About the Company : We are a forward-thinking organization dedicated to leveraging cutting-edge technology to drive innovation and efficiency in our industry.

About the Role : We are seeking an enthusiastic AI / ML Engineer to join our team, focusing on developing intelligent systems that utilize both traditional machine learning and advanced Generative AI. The position requires practical experience with image classification models and strong skills in exploratory data analysis (EDA) to support model development and evaluation.

Responsibilities : ML Model Development

Design and optimize models for image classification, anomaly detection, and predictive analytics.

Utilize transfer learning and fine-tuning techniques with architectures like CNNs, ResNet, or EfficientNet.

Assess model performance using metrics such as precision, recall, F1-score, ROC-AUC, and confusion matrices.

Generative AI Applications

Develop and implement GenAI features using LLMs (e.g., GPT, Claude, Mistral) for enterprise solutions.

Apply prompt engineering, RAG pipelines, and embedding-based search systems.

Collaborate on agentic workflows and multi-modal GenAI projects.

Exploratory Data Analysis (EDA)

Conduct thorough EDA to identify patterns, outliers, and feature relationships.

Visualize data using tools like pandas, seaborn, matplotlib, and Plotly.

Support feature engineering and data preparation for training models.

Collaboration & Innovation

Work with architects, product managers, and stakeholders to align AI solutions with business objectives.

Engage in brainstorming sessions, feasibility studies, and planning for GenAI initiatives.

Qualifications :

At least 6 years of experience in ML model development, including image classification.

Strong Python skills and experience with ML libraries (e.g., PyTorch, TensorFlow, scikit-learn).

Experience with GenAI tools and frameworks (e.g., Hugging Face Transformers, LangChain).

Solid understanding of EDA methods and data visualization.

Preferred Skills :

Experience with multi-modal models and vector databases (e.g., FAISS, Pinecone).

Familiarity with cloud platforms (Azure or AWS) and MLOps practices.

Exposure to enterprise-level GenAI applications and agentic AI systems.

Pay range and compensation package : Competitive salary based on experience and qualifications.

Equal Opportunity Statement : We are committed to creating a diverse and inclusive workplace. We encourage applications from all qualified individuals regardless of race, gender, age, sexual orientation, disability, or any other characteristic.