Fine-tune and distill large models (LLMs, VLMs) to optimize performance and minimize latency on edge devices and cloud infrastructure
Stay up to date with the latest research in deep learning, generative AI, and optimization methods and bringing these innovations into production
Develop, train, and optimize AI models for safety, compliance, and fleet operations, including classical ML models, LLMs, and multimodal systems
Design and implement ML pipelines for petabyte-scale data processing, including feature engineering, model training, and real-time inference
Manage and scale a team of applied scientists and engineers
Conduct A/B testing and causal inference studies to evaluate the impact of AI-driven decisions
Collaborate with engineering teams to deploy models into production, ensuring robustness, interpretability, and real-time performance
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)
Requirements
sql
python
deep learning
aws
masters
team leadership
Strong experience in SQL and handling large-scale datasets
5+ years of experience in deep learning, machine learning, or applied AI
Previous experience running a technical team
Ability to translate business problems into scientific solutions and communicate technical findings to stakeholders
Proficiency in Python (TensorFlow/PyTorch, Pandas, PySpark)
Understanding of probability, statistics, and optimization techniques
Experience working with hardware, robotics, telematics, geospatial data, or sensor fusion.
Knowledge of transformer models, LLMs, and multimodal AI
Experience with ML model deployment on cloud platforms (AWS, GCP)
Masters or Doctoral degree in a quantitative field (CS, AI, Math, Statistics, or related)
Benefits
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Training + Development
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Interview process
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Visa Sponsorship
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Security clearance
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Company
Overview
Founded in 2013
Year Established
The company began as KeepTruckin in 2013 with a focus on digitizing driver hours and logs for truckers.
Rebranded 2022
New Identity Year
The company rebranded to Motive in 2022 to better reflect its expanded mission of powering the physical economy.
$150M Raised in 2022
Series F Funding
The company secured $150 million in Series F funding in 2022, contributing to its valuation.
120,000+ Businesses
Global Reach
The platform supports over 120,000 businesses worldwide, streamlining operations, safety, and finance teams.
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.
Culture + Values
Own It
Less but Better
Build Trust
Unlock Potential
Make it happen
Make it simple
Make it great
Make it different
Make it together
Environment + Sustainability
5M+ Electric Miles
Electric Vehicle Impact
Electrification initiatives have displaced over 5 million electric miles, significantly reducing environmental impact.
13% Fuel Savings
Fuel Efficiency Enhancements
Implementing advanced fleet management has achieved up to 13% reduction in fuel consumption.
20% Idling Cut
AI-Driven Fuel Insights
AI technology has successfully reduced unnecessary idling, saving fleets up to 10% in fuel costs.
15M+ CO₂ Reduced
Carbon Emissions Impact
Efforts have resulted in the displacement of 15 million pounds of CO₂ and reduced particulate matter effectively.
Carbon Neutrality target achieved for Scope 1 & 2 emissions
Upgraded fuel and carbon emissions reporting with low‑carbon integration