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Applications open Full-Time Job

Engineer - AI Orchestration (Windows)

Qualcomm

  • Bengaluru, India
  • Competitive Package
  • 1-3 Years
  • Posted Yesterday
HR
Recruiter contact In post
Recruiter / hiring contact
disability-accomodations@qualcomm.com at Qualcomm

About the role

Company

Qualcomm India Private Limited

Job Area

Engineering Group, Engineering Group > Software Engineering

General Summary

Qualcomm is a global technology leader driving innovation to enable next-generation computing experiences. The Machine Learning Group develops software platforms and tools that enable efficient execution of modern machine learning and generative AI workloads on Snapdragon systems.

As a Software Engineer, you will contribute to the development of the Qualcomm Orchestrator SDK and related tools for Windows and Linux platforms. This role is ideal for an early‑career engineer who is eager to learn system‑level software development, ML runtimes, and AI orchestration frameworks while working closely with senior engineers and architects.

Minimum Qualifications

  • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.

Key Responsibilities

  • Contribute to the development and maintenance of AI orchestration frameworks, SDK components, and tools for Windows and Linux.
  • Assist in implementing and testing ML workflow execution, including model loading, scheduling, and runtime integration.
  • Work on C/C++ codebases to support ML inference and orchestration on Snapdragon platforms.
  • Help integrate and validate ML inference frameworks and runtime components.
  • Participate in debugging, performance analysis, and issue resolution across system and application layers.
  • Collaborate with senior engineers, ML teams, and platform teams to deliver high-quality software.
  • Follow established software engineering practices, including code reviews, documentation, and unit testing.
  • Continuously learn about ML systems, GenAI workflows, and heterogeneous computing architectures.

Minimum Qualifications

  • 1+ year of industry experience (or strong internship/research experience) in software engineering.
  • Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or a related field.
  • Programming experience in C and/or C++.
  • Exposure to Windows and/or Linux development environments.
  • Basic understanding of:
  • Data structures and algorithms
  • Object-oriented programming and software design principles
  • Familiarity with build tools and development workflows (e.g., Make, CMake, Visual Studio, GCC/Clang).
  • Good problem-solving skills and willingness to learn in a fast-paced environment.
  • Effective verbal and written communication skills.

Preferred Qualifications

Platform & Systems

  • Hands-on experience developing software on Windows or Linux.
  • Basic knowledge of:
  • Shared libraries (DLLs / .so files)
  • Application or runtime integration
  • Exposure to cross-platform development concepts.

Machine Learning & AI

  • Introductory experience with machine learning or inference frameworks, such as:
  • ONNX Runtime, SNPE, QNN, LiteRT, or similar
  • Familiarity with ML concepts such as:
  • Model inference
  • Execution graphs
  • Quantization or optimization (coursework or projects acceptable)
  • Interest in Generative AI and agentic AI systems.

Programming & Tooling

  • Experience with Python and/or Java for scripting, testing, or tooling.
  • Familiarity with debugging tools and basic performance profiling.
  • Exposure to version control systems (Git).

Data & Infrastructure (Nice to Have)

  • Basic experience with databases or storage systems such as SQLite or NoSQL.
  • Awareness of logging, monitoring concepts.

What You’ll Gain In This Role

  • Hands-on experience building production ML systems for Windows and Linux.
  • Exposure to GenAI workloads and agentic AI orchestration on edge platforms.
  • Mentorship from senior and staff-level engineers.
  • Opportunities to grow into senior or staff engineering roles within Qualcomm.

Required

Education Requirements

  • Bachelor’s degree in computer science, Computer Engineering, Electrical Engineering, or a related technical field.

Preferred

  • Coursework or projects related to machine learning, operating systems, or systems programming.

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.

Eligibility & process

Who can apply

Employment type: Full-time

Skills & stack

Python Java Next.js REST APIs Git Linux Machine Learning Generative AI / LLMs

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, Java, Next.js, REST APIs, Git, Linux, Machine Learning, Generative AI / LLMs) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Qualcomm Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join Qualcomm as a Engineer - AI Orchestration (Windows)?
Highlight Qualcomm's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Qualcomm Competitive Package
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