Manager, Applied Science (Safety)

Overview

Lead team building AI models for fleet safety and operations

Key Responsibilities

• model development
• ml ops
• data engineering
• a/b testing
• team management
• model optimization

Tasks

-Develop, train, and optimize AI models for safety, compliance, and fleet operations, including classical ML models, LLMs, and multimodal systems -Stay up to date with the latest research in deep learning, generative AI, and optimization methods and bringing these innovations into production -Work with vision, telematics, and sensor data (e.g., dashcam, GPS, IMU, accelerometer) to improve event detection models (e.g., collision detection, risky driving behavior) -Collaborate with engineering teams to deploy models into production, ensuring robustness, interpretability, and real-time performance -Design and implement ML pipelines for petabyte-scale data processing, including feature engineering, model training, and real-time inference -Conduct A/B testing and causal inference studies to evaluate the impact of AI-driven decisions -Manage and scale a team of applied scientists and engineers -Fine-tune and distill large models (LLMs, VLMs) to optimize performance and minimize latency on edge devices and cloud infrastructure

Requirements

• llms
• python
• aws
• sql
• masters
• deep learning

What You Bring

-Knowledge of transformer models, LLMs, and multimodal AI -Ability to translate business problems into scientific solutions and communicate technical findings to stakeholders -5+ years of experience in deep learning, machine learning, or applied AI -Masters or Doctoral degree in a quantitative field (CS, AI, Math, Statistics, or related) -Previous experience running a technical team -Proficiency in Python (TensorFlow/PyTorch, Pandas, PySpark) -Experience with ML model deployment on cloud platforms (AWS, GCP) -Strong experience in SQL and handling large-scale datasets -Experience working with hardware, robotics, telematics, geospatial data, or sensor fusion. -Understanding of probability, statistics, and optimization techniques

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About Motive

-Launched with a simple goal: digitize driver hours and logs for truckers. -Evolved into an integrated platform combining IoT devices and AI-powered apps for managing vehicles, safety, compliance, assets, maintenance, and expenses. -Typical projects include rolling out fleet-wide dashcam systems with real-time safety alerts and automating compliance workflows for construction or oil-and-gas fleets. -Specializes in fleet management for sectors like trucking, logistics, construction, field service, agriculture, transit, and delivery. -A standout achievement: its Motive Card achieved a $1 billion annualized spend run rate, showcasing strong traction in spend management.

Sector Specialisms