ML Engineer

ML Engineer

Location: New York City (Flatiron)
Company Stage: Series B — AI Infrastructure / Financial Operations Technology
Office Type: Onsite
Salary: $160K – $300K + Equity

Company Description

We’re partnering with a fast-growing Series B AI startup building machine learning systems that automate complex accounting and financial workflows. Their platform leverages large language models and advanced AI infrastructure to streamline bookkeeping, audit preparation, document processing, and operational workflows for modern financial organizations. Backed by strong momentum and top-tier investors, the company is scaling rapidly while building AI-native systems that redefine how operational work gets done.

What You Will Do

• Design and implement context ontologies and structured memory systems for AI agents
• Build and optimize data pipelines supporting low-latency state management and long-running agent workflows
• Collaborate cross-functionally to develop intuitive product interfaces and agent interaction systems
• Contribute to 01 AI product development spanning machine learning, backend systems, and full-stack engineering
• Improve agent reasoning, orchestration, and tool usage through context engineering and system design
• Analyze long-running agent trajectories to identify failure modes, improve decision-making, and optimize system behavior
• Build scalable AI-powered systems capable of handling complex real-world operational workflows
• Partner closely with engineering and product teams to iterate quickly on ambiguous, high-impact problems
• Help shape the evolution of agent infrastructure, tooling, and product architecture across the platform

Ideal Background

• Strong computer science and systems engineering fundamentals
• Experience building and deploying machine learning or AI-powered systems in production environments
• High execution velocity with the ability to iterate quickly in ambiguous startup environments
• Strong understanding of machine learning workflows, AI tooling, and modern engineering practices
• Experience working with AI-assisted development tools and workflows
• Strong communication skills with the ability to explain technical concepts clearly
• Demonstrated ownership mindset and ability to drive projects independently from idea to production
• Comfortable working across infrastructure, ML systems, and product engineering layers
• Strong problem-solving abilities and systems thinking across interconnected technical domains

Preferred

• Experience building products or infrastructure from scratch in high-growth startup environments
• Familiarity with agent-based systems, orchestration frameworks, or autonomous workflows
• Experience with LLM systems, context engineering, or AI infrastructure platforms
• Background in operational tooling, workflow automation, or AI-native enterprise products
• Experience analyzing complex system behavior and improving long-running agent performance

Compensation and Benefits

• Base salary: $160K – $300K
• Meaningful equity package with strong upside potential
• High ownership engineering culture with significant technical influence
• Opportunity to work on cutting-edge AI systems and agent infrastructure
• Fast-moving, collaborative startup environment
• Strong emphasis on sustainable pace and long-term team performance