Staff Data Scientist

Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.

About Us
Netradyne, an innovator in fleet and road safety technologies, utilizes the potential of Artificial Intelligence and Edge Computing to transform the transportation ecosystem. By adopting Netradyne's  vision-based technology, organizations have achieved remarkable results, such as a 50% reduction in road accidents and over 90% decrease in dist racted driving incidents, while also excelling in other performance indicators.   

With its headquarters in Bangalore and San Diego, Netradyne's Driver
•I assists organizations in enhancing safety, boosting driver retention, increasing profitability, and facilitating transparency

Job Title: Staff Data Scientist

Experience: 5 to 8 years

Job Responsibilities: 

As a Staff Data Scientist, you will be an integral member of our cross-functional team consisting of Data Scientists, Engineers, and Analysts. Your primary responsibilities will include:

• Collaborating closely with cross-functional teams to identify and implement data-driven solutions addressing key business challenges.
• Applying advanced statistical methods, machine learning and deep learning techniques to uncover trends, patterns, and anomalies in large-scale datasets.
• Design, develop and deploy production ready scalable solutions on edge, cloud or both (hybrid) that utilizes Signal Processing, Gen-AI, DNN, Traditional ML models or/and data-driven rules.
• Creating robust frameworks and tools to automate and enhance data mining, labeling, model training, and validation processes for internal ML/DL initiatives.
• Conducting studies, setting up automation tools and frameworks, and regularly publishing internal and external KPI audits.

Requirements:

• B. Tech, M. Tech or PhD in Data Science, Computer Science, Electrical Engineering, Operations Research, Statistics, Mathematics or a related area.
• Strong foundational knowledge in Statistics, Probability Theory, Machine Learning, Gen-AI and Signal Processing.
• Excellent programming skills – Python(required) and C++ (desired), with strong fundamentals in object-oriented programming, algorithms, and data structures.
• Hands-on experience in handling edge deployments targeting various HW platforms.
• Good understanding of database internals and schema design for relational (RDBMS) and non-relational (NoSQL) data stores.
• Exposure to AWS cloud services, including Kinesis, SQS, EKS, Auto Scaling Groups, etc.
• Knowledge of best practices in software development, including version control, testing, and continuous integration.

Desired skills:

• Worked with Pytorch , Transformers, sklearn or similar ML/ DL packages.
• Proficient in Python programming
• Experience with ML frameworks, including Caffe, TensorRT, OpenCL, SNPE, OpenVino, and ONNX.
• Working knowledge of common industry frameworks and tools around building LLMs, such as OpenAI, GPT, BERT, etc.
• Experience with MLOps tools and practices for continuous deployment and monitoring of AI models.

We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.

If there is a match between your experiences/skills and the Company's needs, we will contact you directly.

Netradyne is an equal-opportunity employer.

Applicants only - Recruiting agencies do not contact.

Recruitment Fraud Alert

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Please review and apply to our available job openings at For more information on avoiding and reporting scams, please visit the Federal Trade Commission's job scams website.