AI/ML Engineer
hitachivantara
Job Description
- Translate complex business and product requirements into scalable AI/ML solutions using classical ML, deep learning, and GenAI techniques
- Design, develop, fine-tune, and evaluate models for NLP tasks such as information extraction, classification, entity recognition, and semantic understanding
- Build and productionize end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring
- Implement LLM-based solutions using prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning approaches
- Deploy and manage training and inference workloads on Kubernetes-based platforms (e.g., Kubeflow, KServe, Ray, or similar)
- Develop scalable APIs and microservices for model inference with performance, latency, and cost considerations
- Establish continuous training, evaluation, and feedback loops (CI/CD/CT pipelines) for model improvement
- Monitor model performance, data drift, and system health in production, and implement automated retraining strategies
- Collaborate closely with data engineering, platform, and product teams to ensure seamless integration into production systems
- Ensure compliance with data privacy, security, and governance standards throughout the ML lifecycle