AI Engineer, FutureFit

• 3-5 years of experience in machine learning, data science/engineering, or a related engineering field
• A technical background (education or professional experience with CS, Statistics, Engineering)
• Strong programming skills in Python and experience in writing production-grade code
• Familiar with SQL programming and SQL / NoSQL databases (such as MongoDB, ElasticSearch)
• Experience in data engineering tasks such as scoping, building, optimizing, and scaling data pipelines and APIs
• Proficiency in cloud tech stacks and specifically AWS services/tools such as Redshift, Airflow, and Sagemaker
• Basic to advanced experience in NLP/NLU: NER models like spaCy; building text classifiers and algorithms from SVM to neural networks like BERT; information retrieval and document understanding
• Experience with LLM deployment, fine-tuning, training, prompt engineering, etc
• Exposure to AI/autonomous LLM agent architectures and methods including feedback mechanisms, data preparation, and memory solutions

Desirable

• Partner with engineering in building scalable data pipelines to service LLM agent APIs
• Assist in developing and deploying APIs and models aligned to generative AI feature needs and our product roadmap
• Assist in developing, improving, and scaling LLM agents and underlying architecture
• Advise and work alongside engineering on data architecture and database design suited to natural language and enterprise reporting requirements
• Collaborate with other data scientists to improve an LLM-focused evaluation and testing methodology
• Provide input into data, training, fine-tuning, and other methods to ensure our models improve over time and remain defensible
• Help lead technical components of our AI projects end-to-end, from requirements, scoping, and design, to implementation, in a highly collaborative and cross-functional environment
• Exercise good taste in systems design and consult other engineering members for input on the technical design of ML systems and APIs
• Design, develop, and deploy ML models aligned to our product and data roadmaps
• Proactively explore innovative approaches for continued improvement, including a proclivity to stay up-to-date on research papers, methods, and open-source tools (ArXiv, Hugging Face, etc.)
• Work alongside data engineering to optimize and scale our pipelines and data warehouse
• Contribute mentorship to other data scientists and cross-functional team knowledge-sharing
• Ensure data privacy and compliance with relevant regulations
• Participate in code reviews and provide constructive feedback