AI Engineer

Gurlinka Solutions - New York, NY

Full-time

New York, NY

About the position

Our client is an innovative AI platform specifically designed for accounting firms, providing them with a team of AI assistants that seamlessly integrate into their existing accounting software such as SAGE and Quickbooks. This integration allows accounting teams to delegate core workflows and automate time-consuming manual tasks, significantly enhancing their operational efficiency. The platform has garnered attention and support, having raised a $3.6 million seed round led by Better Tomorrow Ventures, with participation from BoxGroup, Avid Ventures, and several prominent accounting firms and leaders from the accounting and machine learning communities. In today's business landscape, accountants are not just responsible for maintaining books and filing taxes; they have evolved into trusted advisors who guide businesses through both routine planning and complex challenges. The potential of AI in this domain goes beyond simple chatbots; it requires a deep integration into the workflow of accounting practices. This is why our client collaborates with accounting firms across various practice areas to develop and refine solutions that are inherently aligned with their workflows. The platform is already making strides in serving clients in areas such as CFO advisory, assurance, client accounting services, and bookkeeping. As an AI Engineer, you will play a pivotal role in shaping the future of this platform. Your responsibilities will include building and designing evaluation experiments, monitoring processes for machine learning, and engineering operational systems at the forefront of complex ML workflows. You will take ownership of significant parts of the technology and product, reporting directly to the co-founders. This role requires you to oversee end-to-end ML operations, set the culture and practices within the engineering team, and serve as a subject matter expert for your colleagues. You will also be instrumental in hiring and building out the early engineering team, balancing long-term strategic thinking with the need for rapid, iterative shipping of features and improvements.

Responsibilities

• Build and design evaluation experimentation and monitoring processes for machine learning.
• Engineer operational systems at the cutting edge of complex ML workflows.
• Take ownership of significant parts of the technology and product.
• Report directly to co-founders.
• Oversee end-to-end ML operations.
• Set culture and practices within the engineering team.
• Shape the early engineering culture and processes.
• Serve as a source of subject matter expertise for the rest of the engineering team.
• Help hire and build out the early engineering team, taking on significant responsibilities.
• Balance long-term thinking with the need for fast, iterative shipping.

Requirements

• 5-10 years of experience in machine learning engineering.
• Experience with Python, vector databases, and Large Language Models.
• Experience building out production ML systems around complex workflows.
• Interest in LLMs, NLP, Reinforcement Learning, Probabilistic Graphs, and deep learning.
• Data engineering and ETL pipeline experience.
• Excellent communication skills for engaging with both technical and non-technical stakeholders.

Nice-to-haves

• Demonstrated passion for startups or early-stage companies.
• Experience in financial services.
• Ability to work on either frontend or backend aspects of the project, with flexibility to move across the stack.