AI/ML Engineer - Telematics, Geo & Time-Series (Remote)

Ring Inc; Poland; Remote; PLN 180,000 - 300,000; Full time

Benefits offered by this job

Remote-friendly environment

Job summary

Catena is hiring an AI/ML Engineer to advance the intelligence of the fleet telematics platform. You will build and scale ML pipelines for time-series data, geospatial tracking, and predictive analytics, collaborating with backend engineers and product teams.

You will deploy models, optimize latency, and work with AWS, Docker, and modern ML tooling. The role requires 5+ years of production ML experience, strong Python, and hands-on MLOps capabilities in a remote-friendly environment.

Qualifications

• 5+ years of production ML experience.
• Deep expertise in time-series forecasting and geospatial data.
• Experience with large-scale streaming data and distributed processing.
• Proficient Python and API design (FastAPI, Pydantic).
• Hands-on MLOps: deployment, monitoring, cloud infra (AWS).
• Knowledge of SQL, PostgreSQL and data tooling.

Responsibilities

• Build and scale ML pipelines for time-series data across multiple data sources.
• Apply geospatial tracking and forecasting to derive actionable insights.
• Develop anomaly detection and fraud prevention models.
• Create predictive analytics for maintenance, dispatching, and risk scoring.
• Deliver real-time inference with optimized latency and MLOps workflows.
• Collaborate with backend engineers and product teams to ship ML microservices.

Skills

Time-series forecasting

Geospatial analysis

Anomaly detection

Python

MLOps

API design

Cloud services

Data engineering

Tools

FastAPI

Pydantic

Docker

AWS SageMaker

ECS

S3

PostgreSQL

PostGIS

Kafka

Kinesis

Redis

Snowflake

AWS CDK (Python)

GitHub Actions

PyTorch/TensorFlow

NumPy

Pandas

Job description

Catena is hiring an AI/ML Engineer to advance the intelligence of the fleet telematics platform. You will build and scale ML pipelines for time-series data, geospatial tracking, and predictive analytics, collaborating with backend engineers and product teams.

You will deploy models, optimize latency, and work with AWS, Docker, and modern ML tooling. The role requires 5+ years of production ML experience, strong Python, and hands-on MLOps capabilities in a remote-friendly environment.