Data Scientist & AI Engineer

• We are looking for a highly skilled Data Scientist & AI Engineer who is passionate about solving real-world problems using data, machine learning, and cutting-edge AI technologies. This role will give you the opportunity to work on advanced predictive modeling, Generative AI, and Natural Language Processing (NLP), while collaborating with cross-functional teams to deliver innovative solutions.
  If you love working at the intersection of data, AI, and engineering, and want to drive measurable impact through your work, this role is for you.

• Design, develop, and deploy predictive models and machine learning algorithms for classification, regression, and clustering.

• Build and optimize Retrieval-Augmented Generation (RAG) pipelines and scalable systems using large language models (LLMs).

• Fine-tune and customize LLMs to align with specific business use cases.

• Explore and evaluate open-source LLMs to stay ahead of emerging AI advancements.

• Apply traditional NLP techniques (e.g., BERT, text classification, sentiment analysis, NER).

• Develop and maintain APIs for AI models using frameworks such as FastAPI, ensuring scalability and reliability.

• Collaborate with data scientists, product managers, and engineers to integrate AI-driven features into products.

• Perform data preprocessing, feature engineering, and validation for ML/AI models.

• Document solutions and communicate insights clearly to both technical and business stakeholders.

• Continuously improve models, pipelines, and analytics processes.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.

• 2–3 years of professional experience in data science, machine learning, or AI-focused roles.

Technical Skills

• Strong programming skills in Python with libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn.

• Solid experience with SQL for data extraction and transformation.

• Hands-on experience building and tuning supervised & unsupervised ML models.

• Understanding of model evaluation metrics (accuracy, precision, recall, F1-score, ROC-AUC).

• Familiarity with GenAI concepts and production-grade implementation.

• Exposure to traditional NLP or recommendation systems is a plus.

• Knowledge of data engineering practices including cleaning, transformation, and pipeline automation.

• Experience with version control tools (Git) and Jupyter notebooks.

Soft Skills

• Strong analytical and problem-solving mindset.

• Excellent communication skills to bridge technical and non-technical teams.

• Collaborative, adaptable, and able to thrive in fast-paced environments.

• Detail-oriented with strong time management and organizational skills.

• Opportunity to work on cutting-edge AI projects including Generative AI and NLP.

• Collaborate with a team that values innovation, learning, and impact.

• Growth-oriented culture with exposure to diverse projects and technologies.