Manager of Applied Science, Motive
Safety
$187-235k
Fleet management platform for trucks
Open for applications
Fleet management platform for trucks
1001+ employees
Open for applications
$187-235k
1001+ employees
Company mission
To connect the world’s trucks.
Role
Who you are
- Masters or Doctoral degree in a quantitative field (CS, AI, Math, Statistics, or related)
- Previous experience running a technical team
- 5+ years of experience in deep learning, machine learning, or applied AI
- Experience working with hardware, robotics, telematics, geospatial data, or sensor fusion
- Proficiency in Python (TensorFlow, PyTorch, NumPy, Pandas)
- Strong experience in SQL and handling large-scale datasets
- Knowledge of transformer models, LLMs, and multimodal AI
- Experience with ML model deployment on cloud platforms (AWS, GCP)
- Understanding of probability, statistics, and optimization techniques
- Ability to translate business problems into scientific solutions and communicate technical findings to stakeholders
- The applicant must be authorized to receive and access those commodities and technologies controlled under U.S. Export Administration Regulations. It is Motive's policy to require that employees be authorized to receive access to Motive products and technology
What the job involves
- We are looking for a Manager, Applied Science to help develop and deploy cutting-edge machine learning and deep learning models that power Motive’s safety and fleet management solutions
- You will work on LLMs, forecasting, and multimodal deep learning models, driving innovation in areas like collision detection, driver safety scoring, spend management, and fleet optimization
- This role sits at the intersection of science and engineering, requiring you to push the boundaries of AI while ensuring models are robust, scalable, and production-ready
- As a manager on the Applied Science team, you’ll mentor a team and also directly work with massive datasets (petabyte-scale), including geospatial, telematics, and sensor data, to build models that enhance decision-making across thousands of fleets
- You’ll collaborate with engineers, product managers, and domain experts to develop novel ML algorithms, optimize inference performance, and deploy models in real-world applications that impact millions of drivers and businesses
- Manage and scale a team of applied scientists and engineers
- Develop, train, and optimize deep learning models for safety, compliance, and fleet operations, including LLMs, transformer models, and multimodal AI
- Design and implement ML pipelines for large-scale data processing, including feature engineering, model training, and real-time inference
- Work with vision, telematics and sensor data (dashcam, GPS, IMU, accelerometers) to improve event detection models (e.g., collision detection, risky driving behavior)
- Fine-tune and distill large models (LLMs, Vision Transformers, etc.) to optimize latency and deployment efficiency on edge devices and cloud infrastructure
- Collaborate with engineering teams to deploy models into production, ensuring robustness, interpretability, and real-time performance
- Conduct A/B testing and causal inference studies to evaluate the impact of AI-driven decisions
- Stay up to date with the latest research in deep learning, generative AI, and optimization methods, bringing innovations into production
Our take
Trucking is a huge but fragmented industry that was largely ignored by Silicon Valley until companies such as Motive (formerly KeepTruckin) came along. The integrated fleet management platform acts as air traffic control for trucks, bringing drivers online and into the 21st century.
The company offers both hardware and software solutions to freight companies, allowing them to manage their fleet and keep their drivers safe. One of these solutions is an AI-powered dashcam that detects unsafe driving behavior in real time and instantly alerts the driver.
The platform, which is used by over 120,000 companies, from small businesses to Fortune 500 enterprises, received $150 million in VC in 2025, which is being used to accelerate its investment in AI and grow its enterprise capabilities.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-13% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Jul 2025
$150m
LATE VC
May 2022
$150m
SERIES F
Total funding: $717.3m
Company HQ
Yerba Buena, San Francisco, CA
Leadership
Obaid Khan
(Co-Founder & Board Member)Studied Political Science and Government at University of California before founding KeepTruckin in 2013.
Shoaib Makani
(Co-Founder & CEO)Studied Government & Economics at LSE. Analytics Intern at Yahoo. Worked for a year at Google as APMM. Went on to work in Business Development at AdMob.
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