Senior Applied Scientist

United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Transportation and Logistics, AI & Machine Learning, Fleet Management, Safety and ComplianceIndustries

Requirements

Candidates should possess a Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Artificial Intelligence, Mathematics, or Statistics, and have at least 3 years of experience in deep learning, machine learning, or applied AI. Proficiency in Python, including experience with TensorFlow, PyTorch, NumPy, and Pandas is required, along with strong knowledge of SQL and the ability to handle large-scale datasets. Familiarity with transformer models, LLMs, and multimodal AI is also necessary, as is experience with ML model deployment on cloud platforms like AWS, GCP, or Azure. A solid understanding of probability, statistics, and optimization techniques is expected.

Responsibilities

The Senior Applied Scientist will develop, train, and optimize deep learning models for safety, compliance, and fleet operations, including LLMs, transformer models, and multimodal AI. They will design and implement ML pipelines for large-scale data processing, including feature engineering, model training, and real-time inference. This role involves working with vision, telematics, and sensor data to improve event detection models, fine-tuning and distilling large models for efficient deployment, and collaborating with engineering teams to deploy models into production while conducting A/B testing and causal inference studies to evaluate model impact.

Skills

Machine Learning

Deep Learning

Large Language Models (LLMs)

Forecasting

Multimodal Deep Learning

Geospatial Data

Telematics

Sensor Data

Model Optimization

Inference Performance

AI Deployment

Data Handling at Petabyte Scale

Collaboration with Engineering and Domain Experts

Motive

Enhances broadband services for providers

About Motive

Motive focuses on enhancing the customer experience for broadband service providers. They offer a strategy called the High Leverage Network, which helps service providers simplify their offerings, making it easier for customers to buy, own, and use their services. This approach allows providers to fully utilize their networks to improve business outcomes and stand out in a competitive market. Unlike other companies, Motive emphasizes continuous innovation as a key differentiator, enabling service providers to create a more personalized and engaging experience for their customers. The ultimate goal of Motive is to help service providers deliver a superior customer experience that drives loyalty and business success.

Austin, TexasHeadquarters

1871Year Founded

IPOCompany Stage

Data & Analytics, Enterprise SoftwareIndustries

51-200Employees