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Arkestro

AI-powered procurement orchestration SaaS

Lead Artificial Intelligence/Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • At least 6 years of experience in data science, machine learning engineering, or a related quantitative or engineering field, including hands-on production machine learning or artificial intelligence system delivery.
  • Strong software engineering skills, particularly in Python.
  • Direct experience building and shipping machine learning models or artificial intelligence or agentic functionality in production.
  • Experience building or curating evaluation sets or ground truth for machine learning or large language model-based systems.
  • Experience with MLOps tools and practices for production machine learning or artificial intelligence systems.
  • Familiarity with cloud platforms, preferably AWS, and data warehousing such as Snowflake.
  • Understanding of machine learning concepts and their practical production application.
  • Experience with version control and continuous integration and continuous delivery practices.
  • Ability to lead technical work with limited oversight and influence technical direction without formal authority.
  • Strong problem-solving and analytical skills.

Responsibilities

  • Design, build, and productionize machine learning and agentic artificial intelligence functionality.
  • Partner with product engineering squads to embed artificial intelligence and agentic capabilities directly into Arkestro's product.
  • Contribute to architecture decisions for Arkestro's artificial intelligence products and systems, including its evolving artificial intelligence and machine learning stack.
  • Contribute to dbt and data pipeline work when needed for the systems being built.
  • Own evaluations and ground truth for led projects in partnership with product managers and stakeholders; work with the existing machine learning engineer to build and curate human-generated evaluations for the in-house automated evaluation system.
  • Build and maintain tooling that reliably brings artificial intelligence and machine learning systems into production, treating latency, cost, and error handling as first-class concerns.
  • Champion safety, reliability, and responsible artificial intelligence practices by flagging risk, building guardrails, and helping define production readiness for artificial intelligence features.
  • Serve as a go-to resource for other engineers on artificial intelligence and machine learning best practices.
  • Communicate with technical and non-technical stakeholders.
  • Occasionally engage directly with customers or customer-facing teams to explain how artificial intelligence-driven functionality works.

Desired Qualifications

  • Experience embedding large language model-based or agentic features into a production product.
  • Experience with dbt for data transformations.
  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
  • Experience mentoring other engineers or serving as a team's technical go-to person.
  • Knowledge of procurement or supply chain data models.
  • Prior experience in enterprise software and startups.

About the Company

Arkestro

AI-powered procurement orchestration SaaS

Arkestro is a SaaS platform that uses AI to streamline and optimize procurement for large global companies. It provides Predictive Procurement Orchestration (PPO), which automates the process of collecting and comparing supplier quotes and extracts predictive insights to guide purchasing decisions. The product integrates with a company's existing systems to automate routine procurement tasks, enabling teams to operate at scale without manual data gathering. Unlike traditional procurement tools, Arkestro focuses on AI-driven orchestration across suppliers to speed up decisions and improve supply chain resilience. The company's goal is to help enterprises achieve faster, more informed buying decisions, reduce cycle times, and realize cost savings through smarter procurement.

Company size
51-200
Company stage
Series B
Total funding
$102.4M
Headquarters
San Francisco, CA
Founded
2017

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