Back
Strong employer brand, metro location, and mid-level generalist ML role increase applicant competition.
NLP/LLM engineering skills are transferable, but enterprise MCP/governance experience adds specificity.
Explicit 5+ years NLP requirement plus mandatory ML frameworks, LLM, and cloud skills raises strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end development, productionization, and maintenance of advanced NLP/GenAI machine learning systems and pipelines.
Lead research and implementation of GenAI algorithms; build scalable microservices and MCP servers to augment business workflows.
Mentor junior engineers, establish ML lifecycle best practices, and collaborate cross-functionally to integrate AI solutions into enterprise systems.
Bachelor’s degree or above in Computer Science, Math, Computational Linguistics, Computer Engineering, or related fields.
5+ years professional experience in NLP with strong Python skills and frameworks like Spacy and Hugging Face.
Proven expertise in full ML lifecycle for NLP applications including production deployment and monitoring.
Experience with machine learning frameworks (TensorFlow, PyTorch), Generative AI, LLMs, embedding models, scalable backend microservices in AWS.
Experienced in building enterprise-grade AI/ML platforms with governance, compliance, and scalability considerations.
Strong software engineering skills with ability to write maintainable production code and troubleshoot complex system issues.
Capable of leading both technical execution and mentoring, while effectively collaborating with diverse cross-functional teams to deliver business-impacting AI solutions.