Staff Data Scientist

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:

• Experience with ML frameworks, including Caffe, TensorRT, OpenCL, SNPE, OpenVino, and ONNX.
• Experience in embedded platforms, make files, build systems, and familiarity with Jenkins.
• 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.