Engineer- ML tools
Qualcomm Hyderabad, Telangana, India
Job Description
"Unlock the future of technology as an Engineer- ML tools at Qualcomm, where innovation meets expertise."
As a leading technology innovator, Qualcomm is pushing the boundaries of what's possible to enable next-generation experiences. As an Engineer- ML tools, you will play a crucial role in designing, developing, and deploying cutting-edge machine learning tools that drive digital transformation and create a smarter, connected future.
In this role, you will collaborate with cross-functional teams, including systems, hardware, architecture, and test engineers, to design and develop system-level software solutions that meet and exceed customer needs.
Why you should learn this:
The demand for skilled Engineer- ML tools professionals is on the rise, with a projected growth rate of 30% in the next 5 years, driven by the increasing adoption of AI and ML technologies in various industries.
Expected Salary: $120,000 - $180,000 per year, depending on experience and location, making it a highly rewarding career choice.
How it works:
- Step 1: Design and Develop Machine Learning Tools - Use your expertise in ML to design and develop tools that can be used by various teams within Qualcomm.
- Step 2: Collaborate with Cross-Functional Teams - Work closely with systems, hardware, architecture, and test engineers to ensure that your ML tools meet the performance requirements and interface specifications.
Core Concepts to Master
Machine Learning Fundamentals
Understand the basics of machine learning, including supervised and unsupervised learning, neural networks, and deep learning. Learn about popular ML frameworks and libraries, such as TensorFlow and PyTorch.
Software Development Life Cycle
Learn about the software development life cycle, including requirements gathering, design, implementation, testing, and deployment. Understand how to apply Agile methodologies to ensure efficient and effective software development.
Cloud Computing and Edge Computing
Understand the concepts of cloud computing and edge computing, including cloud storage, cloud services, and edge computing architectures. Learn about popular cloud platforms, such as AWS and Azure, and edge computing frameworks, such as EdgeX.
Interview Questions (Beginner)
- What is machine learning, and how does it differ from traditional programming?
- Can you explain the concept of supervised and unsupervised learning?
- How do you handle imbalanced datasets in machine learning?
Job Overview
Advance Questions
- • How do you design and develop a scalable machine learning model?
- • Can you explain the concept of transfer learning and how to apply it?
- • How do you optimize the performance of a machine learning model on a specific hardware platform?