AI/ML Engineer-NLP, Python, Machine learning, RAG, Langchain, etc
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Protocol Intelligence
Data-driven signals on your job's competitivenessStrong employer brand, popular mid-level ML role with broad AI/LLM requirements drives high candidate competition.
Core ML/LLM engineering skills transfer across industries, while healthcare/regulatory experience increases domain specificity.
Explicit 5+ years requirement plus mandatory ML/LLM, MLOps, and production deployment skills enforce high strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, deploy, and scale machine learning and generative AI solutions including advanced NLP, LLMs, Retrieval-Augmented Generation, and AI agents for enterprise use cases.
Optimize AI models and implement MLOps best practices including CI/CD, model versioning, automated testing, and production monitoring ensuring performance, scalability, and reliability.
Lead technical discussions, collaborate with cross-functional teams, mentor engineers, and establish AI governance and responsible AI principles to drive organizational AI initiatives.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Data Science, Engineering, or related field.
Minimum 5 years professional experience in developing and deploying AI/ML solutions in enterprise environments.
Proficiency in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, or Hugging Face.
Experience developing APIs, microservices, cloud-native applications, and knowledge of CI/CD pipelines, software testing, and secure software development methods.
Ideal Candidate Profile
Experienced in end-to-end AI/ML solution delivery in enterprise settings with a focus on advanced NLP, LLMs, and generative AI technologies.
Skilled at bridging technical and business requirements, capable of leading architecture reviews and mentoring engineering teams.
Knowledgeable in MLOps, responsible AI, model governance, and deploying scalable AI systems in regulated or healthcare-adjacent industries.