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

We are looking for a highly skilledSenior 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