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Tier-1 brand and metro location increase competition, but seniority and specialized ML/LLM skills moderate density.
Advanced ML/LLM requirements and aerospace context need domain knowledge, yet core ML skills remain moderately transferable.
Mandatory 8+ years plus specific ML/LLM frameworks, vector DBs, and cloud/container skills create strict shortlisting.
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Design, develop, and deploy machine learning, deep learning, NLP, and generative AI models for aerospace-related business use cases.
Collaborate with cross-functional teams to translate business needs into data-driven AI/ML solutions and maintain data pipelines for model training and deployment.
Integrate unstructured data into knowledge graphs and vector databases and monitor performance to retrain models ensuring accuracy and relevance.
Bachelor's degree in Engineering, Computer Science, Data Science, Mathematics, Physics, Chemistry, or related field.
Proficiency in Python and familiarity with machine learning libraries and frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain.
Work Experience Required: Minimum 8 years in relevant engineering or AI/ML roles.
Must be located in Bengaluru, India; employer will not sponsor employment visa status.
Experienced in developing and deploying advanced AI/ML models including generative AI using frameworks like transformers, GPT, BERT.
Skillful in handling unstructured data, knowledge graph technologies (e.g., Neo4j, FAISS, ChromaDB), and cloud container platforms (OpenShift, Kubernetes, Docker).
Capable of independently managing analytics solutions with strong collaboration skills to work across global teams and flexible working hours.