Sr AI/ML Engineer

Job Description

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