Machine Learning Engineer Jobs — From Models to Production

This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0-1. You'll be tackling our largest technical challenges across technologies.

We are hiring in NYC, Denver, Bangalore, Hyderabad, or Mumbai.

What you'll do

• Design and build data pipelines that capture and turn high volumes of system activity into structured process data.
• Turn raw activity streams into processes: sessionize event logs, cluster recurring sequences, and use LLMs with structured output to name, score, and conformance-check them.
• Build the evaluation backbone from scratch: stand up synthetic data generation pipelines that produce ground-truth datasets, and use them to measure and improve the quality of our discovery pipeline and model outputs.
• Own data quality and privacy.
• Partner closely with the founders and the rest of engineering to ship features end to end.

What we're looking for

• 1–4 years of experience in data engineering, AI/ML engineering, or backend work with a data focus (strong internships and projects count).
• Strong in Python and/or TypeScript, comfortable in SQL, and able to build data pipelines you can trust — moving, transforming, and validating data.
• Hands-on experience working with LLMs — structured output, prompting, and wrangling non-determinism — whether at work or in serious side projects.
• A practical sense for evaluation: you know that "it looks right" isn't the same as "it's measurably right," and you're excited to build the data and harnesses that prove it.
• Care about data privacy and handling sensitive information responsibly.
• Comfort with ambiguity and a real appetite to own a hard, open-ended problem.

Nice to have

• Background in process mining, sequence / event-log analysis, or workflow analytics — a genuine differentiator for this role.
• Deeper PostgreSQL: window functions, partitioning, pg_cron, query performance.
• Embeddings and vector search (pgvector) or semantic retrieval.
• Familiarity with cloud infrastructure.
• Any prior early-stage startup experience.
• Degree in computer science or a related field.