Remote ML/AI Engineer

Description:

• Rillet is changing the way high-growth companies make financial decisions by aiming for zero day close reporting.
• The company is a next-gen accounting platform that automates end-to-end accounting workflows.
• Information from various sources like CRM, billing, AP, and payroll is synced instantaneously with Rillet, allowing 93% of journal entries to be booked without human intervention.
• The company has raised $38.5 million from notable investors and is looking for passionate individuals who strive for excellence.
• The role of a machine learning engineer involves working on core systems that power Rillet’s AI-driven workflows.
• The position is remote-first, with opportunities to travel for team events.
• Responsibilities include defining Rillet’s ML and AI direction, collaborating with various teams to define ML solutions, understanding user problems, developing automated pipelines for model training and evaluation, and integrating ML/AI models into production systems.

Requirements:

• Candidates must have 3+ years of relevant professional experience in product-driven tech companies.
• Strong experience in Python, including libraries such as numpy, pandas, sklearn, and pytorch, is required.
• Experience with LLM-based agent frameworks is necessary.
• A Bachelor's degree in Computer Science or a related field is required, while an advanced degree (Master’s or Ph.D.) in Artificial Intelligence is preferred.
• The candidate should be able to work both independently and collaboratively in a small team.
• A passion for finding practical solutions to real user problems without compromising on quality is essential.
• Candidates should have a desire for continuous learning and sharing their expertise with others.

Benefits:

• Employees receive medical, dental, and vision insurance.
• The company promotes a remote-first culture built on trust, autonomy, and high performance.
• Paid time off and opportunities for professional development are provided.
• Team offsites and gatherings are organized in locations such as New York, San Francisco, and internationally.
• Employees have the opportunity for equity ownership in a fast-growing early-stage startup.