Sr AI/ML Engineer

Job Title: Sr AI/ML Engineer Duration: Long Term Location: Albany, NY (Remote) • • 100% REMOTE • • Essential Responsibilities: Develop, evaluate, and deploy advanced capabilities in semantic search and recommendation systems, utilizing state-of-the-art machine learning models and information retrieval techniques Articulate potential challenges of building scalable search and recommendation solutions to engineering teams and leadership, and offer creative, technically sound solutions Build and maintain robust monitoring and evaluation pipelines to validate and continuously optimize the performance of search and recommendation engines Assist in the growth of other engineers by sharing technical expertise, best practices, and emerging industry standards for search, ranking, and personalized recommendation systems Ensure high quality standards and clean code practices by performing thorough peer reviews of code pull requests Minimum Qualifications: Bachelor's degree in computer science, Computer Engineering, relevant technical field, or equivalent practical experience Advanced experience building machine learning-powered search or recommendation systems, including the use of vector search, semantic retrieval, and ranking models 5+ year experience of software or application development 4+ years of experience in one or more of the following areas: machine learning/artificial intelligence, information retrieval, or systems engineering Excellent communication skills, able to adapt messaging to technical and non-technical audiences Ability to positively influence team norms, culture, and technical vision Software Engineering Specific Qualifications and Requirements: Experience developing search and recommendation applications using cloud services (e.g., Azure AI Search, AWS Kendra, or equivalent) Deep understanding of vector databases (e.g., Milvus, Azure Search Vector Index) and semantic retrieval frameworks Experience with development tools and workflows for prototyping, evaluation, and deployment of information retrieval systems Strong background in DevOps practices, testing frameworks, and CI/CD Familiarity with retrieval-augmented generation (RAG) architectures and integrating recommendation engines with LLMs and MCPs Strong expertise in API development and management, including security, versioning, and observability best practices