Senior Applied Scientist

Motive; United States; Remote; USD 124,000 - 184,000; Full time

Job summary

Motive is seeking a Senior Applied Scientist to drive innovation in machine learning and deep learning. In this role, you will develop models that enhance safety and efficiency for fleet management, utilizing cutting-edge technology to impact millions of users. Candidates should possess a strong background in quantitative fields and relevant experience in AI.

Benefits

Health, pharmacy, optical and dental care benefits

Paid time off and sick leave

401k contribution

Qualifications

• 3+ years of experience in deep learning or applied AI.
• Strong experience in SQL and handling large-scale datasets.
• Knowledge of transformer models and multimodal AI.

Responsibilities

• Develop, train, and optimize deep learning models for fleet operations.
• Design ML pipelines for large-scale data processing.
• Collaborate with engineering teams for model deployment.

Skills

Deep Learning

Machine Learning

Applied AI

Python

SQL

Data Processing

Education

Bachelor’s or Master’s degree in a quantitative field (CS, AI, Math, Statistics)

Tools

TensorFlow

PyTorch

Job description

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.

Motive serves more than 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.

We are looking for a Senior Applied Scientist 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 key contributor to our Applied Science team, you’ll 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.

What You’ll Do:

• 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

What We’re Looking For:

• Bachelor’s or Master’s degree in a quantitative field (CS, AI, Math, Statistics, or related).
• 3+ years of experience in deep learning, machine learning, or applied AI.
• 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, Azure).
• Understanding of probability, statistics, and optimization techniques.
• Ability to translate business problems into scientific solutions and communicate technical findings to stakeholders.

Pay Transparency
Your compensation may be based on several factors, including education, work experience, and certifications. For certain roles, total compensation may include restricted stock units. Motive offers benefits including health, pharmacy, optical and dental care benefits, paid time off, sick time off, short term and long term disability coverage, life insurance as well as 401k contribution (all benefits are subject to eligibility requirements). Learn more about our benefits by visiting Motive Perks & Benefits .

The compensation range for this position will depend on where you reside. For this role, the compensation range is:

United States

$124,000 - $184,000 USD

Creating a diverse and inclusive workplace is one of Motive's core values. We are an equal opportunity employer and welcome people of different backgrounds, experiences, abilities and perspectives.

Please review our Candidate Privacy Noticehere .

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.

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