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
