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Salary: USD 160,000 - 190,000 / annual
Arkestro is a hyper-growth B2B SaaS company building a Predictive Procurement Platform that applies AI, game theory, and behavioral science to enterprise negotiations. The platform helps procurement teams move from reactive supplier bidding toward data-driven offers that reduce friction and improve outcomes for both buyers and suppliers.
As a Lead AI/ML Engineer, you will own significant pieces of how Arkestro builds, ships, and operates AI-powered functionality in production. This is a startup-scale role with breadth across the full path from idea to production. You'll be a driving voice in shaping the company's AI/ML architecture and work closely with the existing ML engineer and broader Data and Product Engineering teams.
Key responsibilities include:
- Design, build, and productionize machine learning and agentic AI functionality
- Partner with product engineering squads to embed AI and agentic capabilities directly into the product
- Contribute to architecture decisions for AI/ML stack evolution
- Contribute to dbt and data pipeline work as needed for systems you build
- Own evaluations and ground truth for projects you lead, working with PMs and stakeholders to build and curate human-generated evals that feed the in-house automated eval system
- Build and maintain tooling to get AI/ML systems into production reliably, treating latency, cost, and error handling as first-class concerns
- Champion safety, reliability, and responsible-AI practices; flag risks, build guardrails, and help define "production-ready" standards for AI features
- Act as a go-to resource for other engineers on AI/ML best practices
- Communicate clearly with technical and non-technical stakeholders
- Occasionally engage directly with customers or customer-facing teams to explain AI-driven functionality
The role is remote-first with regular in-person opportunities for team building, design sprints, and customer visits.
QUALIFICATIONS:
Necessary:
- 6+ years of experience in data science, machine learning engineering, or related quantitative/engineering field, including hands-on production ML or AI system delivery
- Strong software engineering skills, particularly in Python
- Direct experience building and 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 influence technical direction without formal authority
- Excellent problem-solving and analytical skills
Ideal:
- 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
