Cloud AI platform Staff Engineer

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Software Engineering

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.

• 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Qualification

Bachelor’s degree in engineering, Information Systems, Computer Science, or related field and 10+ years of Software Engineering or related work experience OR

Master’s degree in engineering, Information Systems, Computer Science, or related field and 8+ year of Software Engineering or related work experience OR

PhD in Engineering, Information Systems, Computer Science, or related field.

As a Staff Engineer, your responsibilities will include:

Strong Machine Learning Fundamentals: A deep understanding of machine learning algorithms, statistical modeling, and data preprocessing.

Designing and Developing ML Systems: You'll implement and remodel machine learning models and algorithms, ensuring they align with project objectives. Algorithm Prototypes: Build AI algorithm prototypes based on project specifications.

AI Apps: Support internal teams and customers by providing interfaces and apps to service new features.

Performance Assessment: Run tests to evaluate AI performance, analyzing data to identify strengths and weaknesses.

Model Evaluation: Familiarity with metrics like accuracy, precision, recall, and F1-score to assess model effectiveness.

Deployment and Scalability: Knowledge of deploying ML models in production environments and handling scalability challenges.

Algorithm Optimization: Implement changes to algorithms to enhance AI performance.

Programming Languages: Proficiency in languages such as Python, C, or C++ for implementing ML models and data manipulation.

Deep Learning Frameworks: Experience with frameworks like TensorFlow, PyTorch, etc. for neural network development.

Feature Engineering: Ability to create relevant features from raw data to improve model performance.

Domain Expertise: Understanding of the specific industry or domain where ML solutions will be applied.

Troubleshooting and Documentation: Address issues with deployed AI systems, documenting the development process.

Staying Current: Keep up to date with the latest innovations in machine learning and AI in general.

Effective Communication: As a machine learning engineer, you’ll often need to explain complex algorithms and models to various stakeholders. Clear communication to ensure everyone understands the technical details and project progress.

Teamwork and Collaboration: Collaborating with data scientists, software engineers, and other team members is essential for successful project outcomes. Problem-Solving Skills: Machine learning is all about solving complex problems and creating innovative solutions. You need to be resourceful and adaptable.

Adaptability: The field evolves rapidly, so staying open to new techniques, tools, and approaches is crucial for a machine learning engineer.

Time Management: Balancing multiple tasks, deadlines, and priorities is essential.

Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

If you would like more information about this role, please contact Qualcomm Careers.