Data Scientist - Artificial Intelligence/Machine Learning

Job Description :

Key Responsibilities :

- Design, develop, and deploy AI and ML solutions using Python and modern frameworks.

- Work with LLM APIs such as OpenAI, Anthropic, or similar, integrating them into production systems.

- Develop intelligent applications using LangChain, CrewAI, or AutoGen frameworks (experience with at least one is sufficient).

- Build function-calling pipelines and tool-using agents that can interact with external APIs and dynamic systems.

- Conduct prompt engineering and optimize responses using techniques like Chain-of-Thought reasoning and ReAct patterns.

- Translate business requirements into technical architectures and workflows, ensuring data consistency and accuracy.

- Handle dirty or inconsistent data, designing effective data-cleaning and validation workflows.

- Define and manage edge cases, error handling, and fallback strategies within AI applications.

- Collaborate with non-technical stakeholders to understand requirements and deliver interpretable AI-driven insights.

- Write clean, maintainable, and well-documented code with detailed technical explanations and usage documentation.

- Debug and resolve complex production issues, optimizing performance and scalability.

Required Skills & Experience :

- 3- 8 years of professional experience as a Data Scientist or AI/ML Engineer.

- Proven experience in deploying at least one AI or ML system into production (currently live).

- Strong hands-on experience in Python development and ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn).

- Practical experience with LLM APIs and frameworks like LangChain, CrewAI, or AutoGen.

- Working knowledge of prompt design, few-shot learning, and model evaluation techniques.

- Experience with API integration, microservices, and containerized environments (Docker/Kubernetes) is a plus.

- Strong analytical and problem-solving abilities with an eye for detail and data accuracy.

- Excellent written and verbal communication skills with the ability to explain technical concepts to non-technical audiences.

- Experience working in agile, collaborative, and remote team environments.

Preferred Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related disciplines.

- Experience with MLOps tools, vector databases, or embedding-based retrieval systems (e.g., Pinecone, FAISS).

- Exposure to cloud platforms (AWS, Azure, or GCP) for model deployment and data management.