AI/ML Engineer for Edge, IoT & Digital Twin

Nutanix; San Diego (CA); On-site; USD 123,000 - 184,000; Full time

Benefits offered by this job

Competitive benefits

Job summary

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools for state-of-the-art AI across mobility, edge, auto, and IoT products.

You will collaborate with cross-functional teams to translate requirements into AI-enabled solutions, contribute to AI and Generative AI efforts, and ensure scalable, high-quality software through sound engineering practices.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
• Experience delivering AI-enabled software products or features from concept through production deployment.
• Familiarity with AI concepts, agentic AI frameworks, knowledge management systems, and other LLM-based applications.
• Strong communication, collaboration, analytical, and problem-solving skills.

Responsibilities

• Collaborate in the design, development, and delivery of AI-powered capabilities that advance Nimbus product objectives and address customer needs.
• Contribute to the development, evaluation, and deployment of AI and Generative AI solutions supporting network optimization, Digital Twin technologies, and other strategic AI-driven products.
• Work closely with engineering, product, and domain experts to translate business and customer requirements into practical AI-enabled solutions.
• Communicate technical concepts, project status, and recommendations effectively to both technical and non-technical audiences.
• Stay current with emerging AI technologies, industry trends, and best practices, identifying opportunities to apply them across Nimbus initiatives.

Job description

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools for state-of-the-art AI across mobility, edge, auto, and IoT products.

You will collaborate with cross-functional teams to translate requirements into AI-enabled solutions, contribute to AI and Generative AI efforts, and ensure scalable, high-quality software through sound engineering practices.