Machine Learning Engineer, Level 2

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop extraction pipelines that convert raw conversation data into organized customer memory.

• Optimize LLM prompts and frameworks to decide what an AI agent retains and discards.

• Manage retrieval paths utilizing embeddings, vector search, and ranking techniques.

• Contribute to evaluation frameworks, benchmarks, quality metrics, and regression gates.

• Troubleshoot production issues across ingestion, extraction, and indexing by analyzing logs, metrics, and traces.

• Collaborate with Product and ML teams to transform customer challenges into system modifications and evaluation standards.

• Occasionally travel for project or team meetings in person.

⛳️ Requirements

• Experience in developing backend services.

• Proven ability to learn new languages, frameworks, and tools as necessary.

• Capability to investigate system behavior in production environments.

• Commitment to continuously learning how to operate systems with precision and accountability.

• Experience in building or engaging with evaluation/quality-measurement systems, such as regression detection or quality metrics, or a willingness to learn.

• Strong foundation in observability practices, including structured logging and metrics.

• Experience in utilizing observability data to troubleshoot distributed systems in production.

• Proficiency with AI-assisted development tools for code generation, review, and debugging tasks.

• Desired: Experience with Go and/or Python.

• Desired: Familiarity with event-streaming systems like Kafka.

• Desired: Experience in creating LLM-backed products.

• Desired: Hands-on experience applying ML, including building, evaluating, or deploying models.

• This role is remote within the US and is not available for applicants in San Francisco, Oakland, San Jose, or nearby areas.

🏝️ Benefits

• Competitive salary.

• Generous time-off policy.

• Extensive parental and wellness leave.

• Healthcare insurance coverage.

• Retirement savings program.

• Eligibility for equity plans.

• Participation in corporate bonus plans.

• 401(k) retirement account options.

• Paid sick leave.

• Paid personal time off.

• Paid parental leave.

• Support for employee volunteering and donation initiatives.