Qualcomm Hiring Machine Learning Engineering Job| New Vacancy

• Position Title: Senior Engineer, Machine Learning Engineering
• Salary: Not Disclosed 
• Location: Markham, ON
• Company: Qualcomm
• Qualifications: Bachelor’s degree 
• Experience: At least 5 years
• Job Type: Full-time, Permanent

ABOUT QUALCOMM 

Qualcomm Canada is a subsidiary of Qualcomm Incorporated, a worldwide leader in wireless generation and semiconductors. Based in Canada, Qualcomm specializes in growing contemporary solutions in regions together with cell, automotive, IoT (Internet of Things), and AI (Artificial Intelligence). The employer is recognized for its contributions to the improvement of 3G, 4G, and 5G wireless technology, and its innovations in chipsets and software that power smartphones, wearables, and linked gadgets.

Qualcomm Canada plays a considerable function in driving technological improvements and participating with nearby companions, startups, and universities to foster innovation. With a sturdy emphasis on research and improvement, the business enterprise actively contributes to the improvement of next-era wi-fi communique requirements. Qualcomm’s Canadian offices offer a dynamic painting environment for engineers, researchers, and tech specialists, growing a hub for technological management inside the region.

Senior Engineer – Machine Learning Engineering: Job Overview

Overview:

The Senior Machine Learning Engineering performs a critical position in designing, growing, and deploying devices gaining knowledge of models and systems that force impactful, data-driven decisions and improvements. This role combines deep technical information with a strategic mindset to enforce system getting-to-know algorithms and facts solutions at scale, addressing actual-global demanding situations across diverse industries including e-commerce, healthcare, finance, and generation. The perfect candidate has to have a sturdy background in both software engineering and device studying, with a demonstrated potential to translate enterprise necessities into strong, efficient fashions.

Key Responsibilities:

• Model Development: Design, increase, and implement device mastering fashions for complicated records units, along with supervised unsupervised, reinforcement mastering, and deep getting-to-know fashions.
• End-to-end ML Systems: Led the introduction of scalable and manufacturing-equipped ML pipelines from information series and preprocessing to version training, testing, deployment, and monitoring.
• Collaborative Problem Solving: Work intently with information scientists, engineers, product managers, and stakeholders to understand commercial enterprise desires and translate them into effective technical answers.
• Optimization & Scalability: Optimize gadget studying fashions for both accuracy and performance, ensuring they operate efficiently at scale in manufacturing environments.
• Code Quality & Best Practices: Mentor junior engineers, assess code, and keep high standards for software program excellence documentation, and checking out.
• Research & Innovation: Stay up to date with cutting-edge advancements in machine mastering and AI, integrating modern-day strategies into current systems.
• Data Handling & Preprocessing: Develop techniques for coping with large datasets, addressing issues together with records imbalance, lacking values, and outliers.
• Performance Monitoring: Continuously screen model performance, perceived areas for development, and fine-music models primarily based on feedback and actual-world statistics.

Required Qualifications:

• Education: Bachelor’s or Master’s in Computer Science, Engineering, Statistics, Mathematics, or any associated subject. A PhD is a plus.
• Experience: At least 5 years of palms-on revel in device learning and software engineering.

Skills:

1. Proficiency in programming languages consisting of Python, Java, or C++.
2. Extensive revel in device mastering libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
3. Strong expertise in facts systems, algorithms, and disbursed computing.
4. Familiarity with cloud systems (e.g., AWS, GCP, Azure) and containerization gear (e.g., Docker, Kubernetes).
5. Soft Skills: Strong hassle-solving capacity, communication capabilities, and the potential to work independently and in a team.

Preferred Qualifications:

• Experience with deploying ML fashions into manufacturing at scale.
• Knowledge of advanced ML techniques, such as reinforcement learning or herbal language processing (NLP).
• Familiarity with CI/CD pipelines and DevOps practices.

Click Here to Apply Now

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