Senior AI/ML Engineer

Catena, Inc.; United States; Remote; 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

About Catena

Catena is the universal API for fleet telematics data. We give insurers, factors, TMS providers, brokers, fintechs, and freight-tech platforms a single integration to access carrier vehicle data across every major ELD and telematics provider, replacing dozens of one-off connections. Carriers opt in through a quick, permissioned flow, and our customers immediately get standardized, real-time data on a clean, normalized layer.

About the Role

We're hiring an AI/ML Engineer to advance the intelligence side of the Catena platform.

Responsibilities

• Telematics Data Normalization: Build and scale ML pipelines to ingest, clean, and normalize messy, high-frequency time-series data across diverse ELD providers and vehicle sensor networks.

• Geospatial & Time-Series Modeling: Leverage geospatial tracking and time-series forecasting to extract actionable insights from millions of daily data points (e.g., dynamic ETAs, route optimization, driver safety scoring).

• Anomaly & Fraud Detection: Develop and deploy algorithms to identify anomalous behaviors, location spoofing, or irregular route deviations to protect brokers, factoring companies, and load boards from freight fraud.

• Predictive Analytics: Architect models for predictive maintenance, intelligent dispatching, and risk scoring by synthesizing historical records, Hours of Service (HOS) data, and real-time telematics.

• Real-Time Inference & MLOps: Optimize model latency and throughput to ensure predictive features and data enrichments are delivered seamlessly through Catena's low-latency API without degrading system performance.

• Cross-Functional Collaboration: Partner closely with backend engineers and product teams to integrate ML microservices into Catena's core infrastructure and bring new data products to market.

Qualifications & Tech Stack

• Experience: 5+ years of professional experience building, deploying, and maintaining machine learning models in production environments.

• Core ML Expertise: Deep background in time-series forecasting, geospatial data analysis, anomaly detection, and classic machine learning algorithms (e.g., XGBoost, Random Forests, clustering techniques).

• High-Velocity Data Engineering: Proven ability to work with large-scale, high-throughput streaming data (IoT, GPS pings, sensor data) and distributed processing frameworks.

• Software Engineering: Production-level Python proficiency, strong API design habits (e.g., FastAPI, Pydantic), object-oriented programming, and robust automated testing practices.

• MLOps Foundations: Hands-on experience with model deployment, containerization (Docker), monitoring tools, and cloud infrastructure (AWS).

• Languages: Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow), SQL.

• Data Infrastructure: PostgreSQL (PostGIS for geospatial), Apache Kafka / Kinesis (for streaming telematics), Redis, Snowflake, AWS CDK (Python).

• MLOps & Cloud: Docker, AWS (SageMaker, ECS, S3), GitHub Actions.

Preferred

• Experience in telematics, IoT, logistics, fintech, or insurance data — anywhere the data has physical-world ground truth and someone makes a money decision on it

• Time-series or geospatial data at scale: geofencing, map matching, trip and stop inference, H3 or similar indexing

• Data-sharing and multi-tenant delivery patterns: Snowflake shares, per-tenant credential isolation, consent-scoped access

• Experience building against many third-party APIs at once, where you control neither the schema nor the uptime

• Working in a SOC 2 environment, or helping get a company there

Why Catena, Why Now

• Early-stage startup: high ownership, real impact, and a seat at the table

• Work directly with leadership and have your voice heard on product and API direction

• Be the technical authority customers rely on, and help build the Sales Engineering function from the ground up

• Remote-friendly environment

Catena has raised $8.25M from Shaper Capital, Floating Point, Plug and Play, Liquid 2, and leading industry angels. Customers are already using us in production including modern TMS platforms (Mastery, Optym), large brokerages, and mid-to-large direct carriers operating 100-1,000+ trucks. Many of them are also investors.

Compensation: Competitive salary, full benefits, equity and 401k match.

US only, no sponsorship available. Occasional travel for team on-sites.