Data Scientist - Artificial Intelligence/Machine Learning

Description :

Overview :

Job Responsibilities :

Research & Innovation :

- Stay current with the latest LLM research, architectures, and advancements in the field including real-time models and multimodal systems.

- Evaluate emerging techniques and methodologies for potential application to business problems.

- Monitor developments in transformer architectures, fine-tuning approaches, model optimization, and real-time inference.

- Research and assess new LLM capabilities, frameworks, and API features as they emerge

Solution Design & Prototyping :

- Identify and define approaches for complex AI challenges leveraging state-of-the-art LLMs.

- Design and build proof-of-concept solutions to validate technical feasibility.

- Rapidly prototype LLM-based applications using modern frameworks and orchestration tools.

- Conduct rigorous experiments to evaluate different approaches and methodologies.

- Work collaboratively in multi-disciplinary team environments and establish professional networks with subject matter experts

Production Development & Software Engineering :

- Write clean, maintainable, production-quality code following software engineering best practices and design patterns.

- Develop robust, scalable agentic workflows using orchestration frameworks (such as LangGraph, CrewAI, or similar).

- Implement advanced LLM features, including tool calling, function calling, structured outputs, and multi-turn conversations.

- Build production-grade systems utilizing Model Context Protocol (MCP) and other emerging standards.

- Design and implement scalable, fault-tolerant architectures for real-time LLM-powered applications.

- Conduct thorough code reviews and maintain high code quality standards.

- Optimize code for performance, memory efficiency, and cost-effectiveness in production environments

Experimentation & Optimization :

- Design rigorous experiments to test hypotheses and validate model performance.

- Develop evaluation frameworks for LLM outputs, system performance, and user experience.

- Optimize prompt engineering strategies, fine-tuning approaches, and inference efficiency.

- Conduct A/B tests, performance benchmarking, and statistical analysis

Requirements :

- 7-10 years of experience in data science, machine learning, and AI development with strong focus on NLP and LLM applications

- Bachelor's/Master's or higher degree in Computer Science, Machine Learning, Statistics, or related technical field

- Proven track record of building and deploying production ML/AI systems from research to deployment

- Mastery of Python with strong software engineering fundamentals (OOP, design patterns, testing)

- Deep hands-on experience with LLM frameworks and APIs (OpenAI, Anthropic, or similar)

- Strong experience with at least one deep learning framework (PyTorch or TensorFlow)

- Proficiency with modern ML orchestration and agentic frameworks (LangGraph, CrewAI, LangChain, or similar)

- Solid understanding of NLP techniques : embeddings, information extraction, semantic search, classification

- Experience with diverse ML models : neural networks, transformers, SVM, Random Forest, clustering, Bayesian models

- Hands-on experience with advanced LLM features : tool calling, function calling, multi-turn conversations, structured outputs

- Strong knowledge of software development practices : version control (Git), testing (pytest)

- Experience with REST APIs, async programming, and building scalable backend services

- Familiarity with vector databases and embedding systems (Pinecone, Weaviate, FAISS, or similar)

- Knowledge of distributed computing, cloud platforms (AWS, GCP, or Azure), and containerization (Docker)

- Strong experimental design skills with ability to formulate hypotheses and conduct rigorous analysis

- Excellent problem-solving abilities and intellectual curiosity to stay current with AI research

- Self-motivated with proven ability to work collaboratively in multi-disciplinary teams