Principal Machine Learning Engineer
Job Description
Okta is hiring a Principal Machine Learning Engineer (Okta Secures AI) to evolve authorization for agent access policies using dynamic AI security mechanisms.
Responsibilities
- Build intent-based enforcement to confirm agent runtime requests match intended purpose
- Apply LLM reasoning and prompt parsing to interpret prompts, tool payloads, and intent in real time
- Integrate low-latency inference or semantic evaluation engines into the API gateway request path
- Use embeddings, vector search, or zero-shot classification to score alignment between agent intent and executed actions
- Design confidence-scored decision engines that feed semantic verification results into policy frameworks such as Cedar
- Establish evaluation benchmarks, prompt injection defenses, and guardrails to prevent bypasses or false positives
- Architect scalable ML and Generative AI systems with retrieval, inference, and evaluation pipelines
- Optimize prompting, context retrieval, and RAG workflows for accuracy, safety, and efficiency in Claude-based systems
- Build automated evaluation pipelines to measure model quality, correctness, groundedness, and safety in production
- Implement schema validation, structured output enforcement, and guardrails for reliable, compliant AI outputs
- Mentor and coach engineers to support team and community growth
Requirements
- 10+ years of software development experience with strong Python expertise; Go or TypeScript familiarity is a plus
- Hands-on experience with applied machine learning, including feature engineering, training, and fine-tuning models
- Hands-on experience with modern Generative AI platforms such as AWS Bedrock, OpenAI, Anthropic, etc.
- Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows
- Hands-on experience with AI agent frameworks including LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or similar
- Familiarity with ML frameworks such as FastAPI, PyTorch, TensorFlow, and Spark ML, plus orchestration tools like Airflow
- Experience defining evaluation metrics, pipelines, and feedback loops for ML/GenAI systems
- Proven ability to collaborate with product and engineering teams to drive greenfield initiatives, manage unknowns, and iterate quickly
- Experience building tools or infrastructure for AI/ML applications with deep understanding of the developer lifecycle in an AI-native world
Technologies
- Python, Go, TypeScript
- AWS Bedrock, OpenAI, Anthropic
- LiteLLM, LangGraph, LangChain, LlamaIndex, MCP
- FastAPI, PyTorch, TensorFlow, Spark ML
- Airflow, Cedar
- Claude-based systems
Location & Salary
- San Francisco, CA (hybrid)
- USD 238,000 - 326,000 per yearly
Education
- Bachelor’s or Master’s degree in Computer Science or related field
Benefits
- Equity (where applicable), bonus, and benefits including health, dental and vision insurance
- 401(k)
- Flexible spending account
- Paid leave including PTO and parental leave
Extra Credit
- Experience integrating AI-driven systems with identity, authentication, or security products
- Exposure to ethical AI, model risk, or compliance frameworks
- Familiarity with evaluation datasets, synthetic data generation, or LLM-as-a-judge methods
Okta Experience
- Supporting Your Well-Being
- Driving Social Impact
- Developing Talent and Fostering Connection + Community