Senior AI Engineer (AWS, ML/LLMOps, Generative AI)

We are looking for a highly skilled Senior AI Engineer to spearhead the development of innovative AI and ML solutions, including Recommendation Systems, Data Classification, Search Optimization, and Knowledge Graphs. This role includes collaborating with a staff-augmented team to deliver cutting-edge features using AWS infrastructure and advanced ML/LLMOps practices. Responsibilities Design, develop, and implement AI, Generative AI, and ML solutions aligned with business needs Build and fine-tune predictive models for customer retention, search optimization, and specialized language capabilities Develop data aggregation, normalization, and enrichment workflows to empower intelligent insights Utilize AWS services such as SageMaker, compute, and storage to deploy reliable and scalable cloud infrastructures Create and deploy recommendation systems for delivering personalized insights and enhancing user experiences Leverage knowledge graphs and entity linking for data enrichment and semantic understanding Implement context-aware AI solutions to deliver enhanced search capabilities based on user intent Develop dashboards and scoring mechanisms for decision-making and user-focused analytics Set up automated alerts and strategies based on machine learning risk thresholds Collaborate with team members to define research goals and implement intelligent research tools using APIs Build and maintain machine learning pipelines following ML/LLMOps best practices, including deployment and monitoring Apply domain expertise in training models using diverse data sources, both structured and unstructured Requirements 3+ years of experience in AI, ML, and MLOps, with a track record of developing and deploying production-grade solutions Expertise in AWS tools and services such as SageMaker, compute, and storage Proficiency in Python and frameworks such as TensorFlow, PyTorch, and Scikit-learn Skills in ML/LLMOps to implement CI/CD workflows and manage the scalability of deployed models Familiarity with recommendation systems, semantic data, and retrieval-augmented generation (RAG) frameworks such as LangChain or LlamaIndex Knowledge of advanced search engine optimization techniques and context-aware models Background in creating domain-specific language models for high accuracy in specialized research fields Understanding of data enrichment techniques, entity linking, and the construction of knowledge graphs Capability to implement symbolic AI and domain-tuned techniques for specialized use cases Excellent command of written and spoken English (B2+ level) Nice to have Experience with AWS Lambda and AWS Step Functions for workflow orchestration Familiarity with academic and research data trends, discovery methods, and prediction models Showcase of building scalable AI-driven automated systems enhanced by RAG techniques Competency in enhancing medical reasoning and crafting intelligent research tools