AI / Data Scientist

About the Role

We’re looking for a driven AI / Data Scientist with at least 2 years of experience to join our team. You’ll play a key role in developing and deploying machine learning models, working on real-world AI applications, and turning data into actionable insights. This role is ideal for someone who has moved beyond entry-level work and is ready to take ownership of projects while continuing to grow technically.

What You’ll Do

• Design, build, and optimize machine learning and AI models
• Work with large, complex datasets to extract insights and improve model performance
• Develop AI-powered solutions such as recommendation systems, NLP models, or predictive analytics tools
• Collaborate with engineering and product teams to deploy models into production environments
• Evaluate and monitor model performance, ensuring reliability and scalability
• Contribute to data pipelines and feature engineering processes
• Stay current with emerging AI trends, including generative AI and LLMs
• Build solutions for document image processing using tools like Google Cloud Vision, AWS Tex tract, and OCR libraries
• Perform advanced image processing tasks, including manipulating and enhancing images while preserving original metadata, resolution, and archival integrity

What We’re Looking For

• Bachelor’s or Master’s Degree in Computer Science, Data Science, AI, or a related field
• 2+ years of hands‑on experience in data science or AI roles
• Strong proficiency in Python
• Experience with machine learning frameworks (e.g., scikit‑learn, TensorFlow, PyTorch)
• Solid understanding of statistical methods and machine learning concepts
• Experience working with SQL and large datasets
• Ability to take ownership of tasks and deliver end‑to‑end solutions
• Strong communication skills and ability to work cross‑functionally

Preferable

• Experience with NLP, computer vision, or recommendation systems
• Familiarity with LLMs, prompt engineering, or generative AI applications
• Experience deploying models using cloud platforms (AWS, GCP, Azure)
• Knowledge of MLOps practices (CI/CD, model monitoring, versioning)
• Experience with big data tools (Spark, Hadoop)