Principal ML Engineer, Admin Central

Description

The company is a Fortune 500 firm and a leading AI platform for managing people, money, and agents.

Two teams are hiring engineers. One is changing how administrators work across the platform, replacing scattered tools and disconnected AI with a single unified experience, so that the company implementations rely on built-in intelligence instead of manual effort.

The other team, Business Process Optimize, runs core platform infrastructure: distributed systems, high-availability usage pipelines, agentic features, and event-driven data flows across global regions that keep enterprise billing accurate at scale. The work involves building new systems from the ground up at a fast pace, affecting thousands of admins every day.

Responsibilities

• Lead the architecture and hands-on build of the company's next-generation AI platforms and autonomous agent frameworks.
• Turn AI research into production systems that handle tens of millions of daily requests for hundreds of enterprise tenants, including more than 100 Tier-0 tenants.
• Design the ML infrastructure, multi-agent orchestration layers, and high-availability usage pipelines that support decisions, usage tracking, automatic tenant maintenance, and billing accuracy across international regions.
• Build and maintain agent capabilities such as tool use, coordination across several agents, planning over long horizons, reasoning frameworks, and human review points.
• Build secure, high-throughput REST services and event-driven pipelines using Python, AWS, Kubernetes, and cloud-native tools, and design multi-tenant runtimes that serve low-latency inference to millions of users worldwide.
• Set end-to-end MLOps standards covering CI/CD, observability, evaluation, model monitoring, and privacy and anonymization safeguards, so systems stay explainable, secure, and resilient in production.
• Work with software engineers, product managers, data engineering, SRE, and legal and compliance teams to turn unclear business needs into scalable designs and long-term data governance plans.

Requirements

• 12+ years in ML development, including R&D leadership, with 8+ years working on advanced ML methods, distributed frameworks, and cloud platforms, and a record of designing complex, scalable, production-grade ML systems.
• 6+ years building and running scalable ML services, microservices, and high-throughput data pipelines in production, using Java, Go, Scala, or Python.
• 4+ years working with LLMs, generative AI, RAG pipelines, and autonomous agent frameworks in real enterprise applications.
• Expertise in high-throughput streaming with Kafka, real-time feature extraction with Spark or Flink, and distributed columnar storage such as ClickHouse or Iceberg for large ML pipelines.
• Deep knowledge of deep learning, LLM orchestration, RAG, and agentic systems, including applying ML algorithms and Model-Based Design, with MCP integrations and tool-use frameworks, to multi-agent coordination, intent classification, and workflow optimization.
• Proven ability to lead exploratory data analysis on multi-tenant agentic workflows to shape data strategy, plus strong command of high-dimensional embeddings, vector database management, and data isolation.
• Proven ability to lead building, fine-tuning, and deploying domain-specific foundation models, including Kubernetes and Docker deployment, automated CI/CD retraining, and managing drift and latency at scale.
• Deep command of Python and the ML ecosystem (PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, Scikit-learn), with experience running production systems on PostgreSQL, Redis, Kafka, and AWS, GCP, or Azure.
• Skilled at collaborating and mentoring, leading cross-functional pods, running sprint planning, and explaining technical and governance decisions to executives.
• Bachelor's degree in computer science, data science, statistics, mathematics, engineering, or a related field, or equivalent experience; a Master's or PhD is strongly preferred.

Conditions

The annualized base salary for the primary location, USA.CA.Pleasanton, is $228,000 USD to $342,000 USD.

The annualized base salary for other listed US locations is $190,600 USD to $342,000 USD.

Pay varies by work location and is set by geography, experience, skills, job duties, and business need, among other factors.

Flex work model: at least 50% of time each quarter is spent in the office or in the field with customers, prospects, and partners, depending on the role, with no fixed number of office days. Remote home-office roles may also join in-office gatherings for important moments.

Equal opportunity employer including individuals with disabilities and protected veterans; applicants with arrest and conviction records are considered under applicable Fair Chance law.

Benefits

• May be eligible for the company Bonus Plan or a role-specific commission or bonus.
• May be eligible for annual refresh stock grants.
• Comprehensive benefits are available, and recruiters can share more detail during the hiring process.