Senior AI/ML Engineer — Remote + Real-Time Telematics

Catena, Inc.; United States; On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Remote-friendly environment

Job summary

Catena is hiring an AI/ML Engineer to advance the intelligence side of the Catena platform. You will build and scale ML pipelines for high-frequency telematics data, perform geospatial and time-series modeling, and develop predictive analytics to support dispatching, maintenance, and risk scoring.

You’ll ensure low-latency real-time inference and collaborate with engineers to bring ML microservices to market in a remote-friendly environment.

Qualifications

• 5+ years of professional ML experience in production.
• Deep background in time-series forecasting and geospatial data analysis.
• Experience with anomaly detection and common ML algorithms.
• Production-level Python expertise and robust API design.
• Experience with MLOps and cloud infrastructure.

Responsibilities

• Build and scale ML pipelines to ingest, clean, and normalize time-series data.
• Model geospatial tracking and time-series forecasts for actionable insights.
• Develop algorithms for anomaly detection and fraud protection.
• Architect predictive models for maintenance, dispatching, and risk scoring.
• Optimize real-time inference latency and deploy ML microservices.
• Collaborate with backend engineers to integrate ML into core infra.

Skills

5+ years professional ML experience

Time-series forecasting

Geospatial data analysis

Anomaly detection

Python (Pandas, NumPy, Scikit-learn)

SQL

Tools

FastAPI

Pydantic

Docker

AWS SageMaker

AWS ECS

AWS S3

Kafka

Kinesis

PostgreSQL

PostGIS

Redis

Snowflake

AWS CDK

Python

GitHub Actions

Job description

Catena is hiring an AI/ML Engineer to advance the intelligence side of the Catena platform. You will build and scale ML pipelines for high-frequency telematics data, perform geospatial and time-series modeling, and develop predictive analytics to support dispatching, maintenance, and risk scoring.

You’ll ensure low-latency real-time inference and collaborate with engineers to bring ML microservices to market in a remote-friendly environment.