Lead AI/ML Engineer

About this Role

As a Lead AI/ML Engineer, you'll own significant pieces of how Arkestro builds, ships, and operates AI-powered functionality in production. This is a startup-scale role: you'll work across more of the path from idea to production than a comparable role would at a larger company, and you should be energized by that breadth rather than looking to specialize narrowly. You'll be a driving voice in shaping our AI/ML architecture, working closely with our existing ML engineer and the broader Data and Product Engineering teams.

Responsibilities

• Design, build, and productionize machine learning and agentic AI functionality yourself
• Partner with product engineering squads to embed AI and agentic capabilities directly into Arkestro's product.
• Contribute to architecture decisions for how Arkestro builds AI products and systems, including our still-evolving AI/ML stack.
• Contribute to dbt and data pipeline work when it's needed for the systems you build
• Own evals and ground truth for the projects you lead, in partnership with PMs and stakeholders. Work with our existing ML engineer to build and curate the human-generated evals that feed our in-house automated eval system.
• Build and maintain the tooling that gets AI/ML systems into production reliably, treating latency, cost, and error handling as first-class concerns.
• Champion safety, reliability, and responsible-AI practices in the systems you build: flag risk, build in guardrails, and help define what "production-ready" means for AI features at Arkestro.
• Act as a go-to resource for other engineers on AI/ML best practices.
• Communicate clearly with both technical and non-technical stakeholders.
• Occasionally engage directly with customers or customer-facing teams to explain how AI-driven functionality works

Necessary Qualifications

• 6+ years of experience in data science, machine learning engineering, or a related quantitative/engineering field, including hands-on production ML or AI system delivery
• Strong software engineering skills, particularly in Python
• Direct experience building & shipping ML models or AI/agentic functionality in production
• Experience building/curating evaluation sets/ground truth for ML or LLM-based systems
• Experience with MLOps tools and practices for production ML/AI systems
• Familiarity with cloud platforms (preferably AWS) and data warehousing (e.g. Snowflake)
• Understanding of machine learning concepts and their practical, production application
• Experience with version control and CI/CD practices
• Demonstrated ability to lead technical work with limited oversight and to influence technical direction without formal authority
• Excellent problem-solving and analytical skills

Ideal Qualifications

• Experience embedding LLM-based or agentic features into a production product
• Experience with dbt for data transformations
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes)
• Experience mentoring other engineers or acting as a technical go-to person on a team
• Knowledge of procurement and/or supply chain data models
• Prior experience in enterprise software and startups

Additional information

If you're passionate about turning innovative ideas into scalable solutions and want to make a significant impact in the procurement space, we'd love to hear from you. Join us in revolutionizing how companies manage their spend and supply chains!

Pay Range $160,000—$190,000 USD

Arkestro is committed to providing our employees with a benefits package designed to give you the flexibility you need to ensure a healthy life/work balance. Arkestro offers our employees great benefits and perks, including, but not limited to:

• Competitive salary and startup equity
• Medical, Dental, Vision insurance premiums covered up to 100% (employee only)
• 401K discretionary employer matching
• Unlimited PTO
• A remote-first team with regular opportunities to get together in person for team building, design sprints, and customer visits
• Annual budget of $1,000 for learning and professional development
• Diverse, inclusive, highly collaborative, and vibrant culture