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Popular AI/ML title, mid-level experience, metro location, and broad skill requirements increase candidate competition.
Role requires specialized ML/LLM and production deployment skills but remains transferable across industries.
Explicit 3+ years, mandatory ML/LLM, and cloud/backend skills create strict shortlisting filters.
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Build and optimize large-scale conversational AI systems improving intent detection, response quality, and reliability for global organizations.
Develop and deploy cloud-native microservices and AI workflows focusing on performance, latency, and scalability, including fine-tuning large language models.
Collaborate cross-functionally to translate AI research innovations into production-grade services impacting customer and employee interactions worldwide.
Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field; Master's/Ph.D. with 1–2 years experience also acceptable.
3+ years of relevant industry experience for Bachelor's degree holders; 1–2 years for advanced degrees.
Proficiency in Python backend development, AI/ML frameworks (TensorFlow, PyTorch, Hugging Face), and experience fine-tuning LLMs and inference frameworks such as vLLM.
Experience with API development, microservice architecture, and cloud platforms (AWS, GCP, or Azure).
Experienced in deploying and scaling real-time AI applications like chatbots or voice assistants within distributed microservice architectures.
Comfortable working at the intersection of software engineering and applied machine learning influencing system architecture, model performance, and platform scalability.
Skilled collaborator able to work closely with product, research, and design teams to convert AI research into robust, enterprise-grade solutions.