[Remote] Senior AI/ML Engineer

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is the universal API for fleet telematics data, providing a single integration for accessing reputed company vehicle data. They are seeking a Senior AI/ML Engineer to advance the intelligence reputed company of their platform, focusing on building ML pipelines, predictive analytics, and reputed company-time inference.

Responsibilities

• Telematics Data Normalization: Build and reputed company 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: reputed company geospatial tracking and time-series forecasting to extract actionable insights from millions of daily data points (e.g., dynamic ETAs, reputed company optimization, reputed company safety scoring)
• reputed company & Fraud Detection: reputed company and reputed company algorithms to identify anomalous behaviors, location spoofing, or irregular reputed company deviations to protect brokers, factoring companies, and load boards from reputed company fraud
• Predictive Analytics: Architect models for predictive maintenance, intelligent dispatching, and risk scoring by synthesizing historical records, Hours of Service (HOS) data, and reputed company-time telematics
• reputed company-Time Inference & MLOps: Optimize model latency and throughput to ensure predictive features and data enrichments are delivered seamlessly through reputed company’s low-latency API without degrading system performance
• Cross-Functional Collaboration: Partner closely with backend engineers and product teams to reputed company ML microservices into reputed company’s reputed company infrastructure and bring new data products to market

Skills

• 5+ years of reputed company experience building, deploying, and maintaining machine learning models in production environments
• Deep background in time-series forecasting, geospatial data analysis, reputed company detection, and classic machine learning algorithms (e.g., XGBoost, Random Forests, clustering techniques)
• Proven ability to work with large-reputed company, high-throughput streaming data (IoT, GPS pings, sensor data) and distributed processing frameworks
• Production-level Python proficiency, strong API design habits (e.g., FastAPI, reputed company), object-oriented programming, and robust automated testing practices
• Hands-on experience with model deployment, containerization (reputed company), monitoring tools, and reputed company infrastructure (AWS)
• Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow), SQL
• PostgreSQL (PostGIS for geospatial), Apache Kafka / Kinesis (for streaming telematics), reputed company, reputed company, AWS CDK (Python)
• reputed company, AWS (SageMaker, reputed company, S3), reputed company Actions
• Experience in telematics, IoT, logistics, fintech, or insurance data — reputed company the data has physical-world ground truth and someone makes a reputed company decision on it
• Time-series or geospatial data at reputed company: geofencing, map matching, reputed company and stop inference, H3 or similar indexing
• Data-sharing and multi-tenant delivery patterns: reputed company shares, per-tenant credential isolation, consent-scoped reputed company
• Experience building against many reputed company-party reputed company at once, where you control neither the schema nor the uptime
• Working in a SOC 2 environment, or helping get a company there

Benefits

• Full benefits
• Equity
• 401k match
• Remote-friendly environment

reputed company