Applied AI Engineer New Grad

As an Applied AI Engineer at iManage, you will build and ship AI systems that work at scale in production. You will work within the Applied AI team alongside engineers, data scientists, and product stakeholders to develop AI capabilities for iManage's enterprise work platform, including Ask iManage, document classification, extraction, and LLM-driven features. ## Responsibilities - Contribute to AI systems across the ML lifecycle, from model development and evaluation to production serving, with guidance and mentorship from senior engineers. - Write, test, and maintain production-quality code for ML/LLM features and APIs. - Help build and run evaluations that measure model quality and catch regressions. - Support deployment and monitoring of ML systems on cloud infrastructure and learn CI/CD and DevOps practices. - Collaborate with teammates and product stakeholders, ask good questions, and take ownership of well-scoped work. - Continuously grow skills through code review, pairing, and best-practice guidance. - Build internal platform tooling and paved paths that make it faster and safer for the wider team to ship AI systems. ## Qualifications - Bachelor's degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Statistics, or a related field. - 0-2 years of experience, including internships, research, or substantial coursework or personal projects in ML/AI or software engineering. - Proficiency in Python and familiarity with modern AI frameworks such as PyTorch and Hugging Face. - Solid grasp of ML fundamentals, with hands-on exposure to modern generative AI or transformer architectures. - Foundational software engineering skills, including version control with Git/GitHub and an understanding of how code is built and tested. - Ability to work collaboratively, communicate clearly, and take ownership of learning. - A growth mindset and genuine enthusiasm for building AI systems. ## Bonus Qualifications - Internship experience shipping software or ML features. - Personal, academic, or open-source projects involving LLMs, RAG, or agentic systems. - Exposure to Docker, Kubernetes, or cloud infrastructure such as Azure, AWS, or GCP. - Coursework or projects in NLP, deep learning, or distributed systems. ## Work Arrangement This role follows a flexible working policy and requires in-office presence in the Chicago office on Tuesdays and Thursdays. ## Compensation and Benefits - US annual base salary range of $100,000-$130,000, excluding bonuses, commission, and benefits. - Annual performance-based bonus. - Health, vision, dental, and life insurance. - 401(k) retirement savings plan with company match up to 4%. - Enhanced parental leave: 20 weeks fully paid primary leave and 10 weeks fully paid secondary leave. - Flexible time off policy. - Company wellness days. - Access to RethinkCare behavioral health and well-being resources. - Unlimited access to LinkedIn Learning and interactive Microsoft courses and training.