Responsibilities
Design, develop, and deploy end-to-end AI/ML systems, including data ingestion, model training, evaluation, and integration into production environments.
Build and optimize applications leveraging LLMs and open-source GenAI frameworks such as LangChain, LlamaIndex, Haystack, Transformers, AutoGen, and DSPy.
Implement advanced GenAI techniques including agent-based orchestration, prompt engineering, retrieval-augmented generation (RAG), and model fine-tuning.
Write production-grade software in Python and C# or Java, ensuring maintainability, scalability, and performance.
Collaborate with cross-functional teams to translate business requirements into technical solutions.
Ship and maintain large-scale AI applications, with a focus on performance monitoring and continuous improvement.
Conduct rigorous evaluation of AI models using appropriate metrics and benchmarks.
Optimize models for latency, throughput, and accuracy in real-world scenarios.
Work closely with data scientists, product managers, and other engineers to drive AI initiatives.
Stay current with the latest advancements in GenAI, LLMs, and AI frameworks.
Prototype and experiment with emerging technologies to assess feasibility and impact.
Qualifications
Bachelor's Degree in Computer Science, Data Science or related technical field
Should have total 5+ years in Data Science experience
2+ years technical engineering experience with coding in languages including C#, Python and Pytorch
2+ years of experience in shipping at least 2 large scale ML/AI-based services or applications on cloud platforms (Azure, AWS, GCP, etc.)
3+ years of experience with LLMs and open-source GenAI frameworks, such as LangChain, LlamaIndex, Haystack, or equivalents (e.g., Transformers, AutoGen, DSPy), including agent-based orchestration, prompt engineering, retrieval-augmented generation (RAG), and fine-tuning and evaluation.
Proficiency in writing production-quality software code in one or more modern programming languages (Python, C#)
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