Apple Hiring: PhD Intern – Apple Ads (Machine Learning) 2026:-
Apple is inviting applications for the position of PhD Intern – Apple Ads (Machine Learning) at its Hyderabad, Telangana location. This opportunity is designed for PhD scholars specializing in Computer Science, Machine Learning, Data Science, Software Engineering, or related technical disciplines.
| Company: | Apple |
| Job Role: | PhD Intern – Apple Ads (Machine Learning) |
| Job Type: | Internship |
| Experience: | PhD Scholars |
| Salary/Stipend: | As per company Standards |
| Application Deadline: | ASAP |
Role Overview:-
Apple is looking for a highly motivated PhD Intern to join its Apple Ads Machine Learning team in Hyderabad.
As a Software Engineering Intern, the selected candidate will contribute to designing, developing, and optimizing advertising platforms using machine learning technologies.
The role involves working with large-scale datasets, developing and deploying machine learning algorithms, improving ad relevance, forecasting, and optimizing advertising performance.
Interns will collaborate with experienced software engineers and cross-functional teams to build scalable, high-performance, and privacy-preserving advertising solutions.
This opportunity provides practical exposure to machine learning research, deep learning architectures, generative AI, distributed systems, and production-level software engineering.
Educational Requirements:-
Candidates must be currently pursuing a PhD in one of the following disciplines:
- PhD – Computer Science
- PhD – Software Engineering
- PhD – Machine Learning
- PhD – Data Science
- PhD – Artificial Intelligence
- PhD – Related Technical Fields
Mandatory Qualification: Currently pursuing a PhD in Computer Science, Software Engineering, Machine Learning, Data Science, or a related technical field.
Key Skills:-
Technical Skills
- Python
- Java
- Scala
- C++
- Data Structures and Algorithms
- Object-Oriented Programming
- Machine Learning
- Deep Learning
- TensorFlow
- PyTorch
- Scikit-learn
- SQL / NoSQL Databases
- Git and Version Control
- Neural Network Architectures
- Transformers, DNNs, and RNNs
- Model Optimization
- ONNX Runtime
- TensorRT
- vLLM
Machine Learning & AI Skills
- Machine Learning Model Development
- Statistical Analysis
- Predictive Modeling
- Model Training and Evaluation
- Model Inference Optimization
- Quantization
- Tensor Parallelism
- Reinforcement Learning
- Explore/Exploit Strategies
- Bandit-Based Optimization
- Generative AI (GenAI)
- Agentic AI Systems
- Training Pipelines
Data Engineering & Distributed Systems
- Apache Spark
- Hadoop
- Apache Flink
- Distributed Systems
- Ray
- Large-Scale Data Processing
- High-Throughput RPC Systems
- Data Warehousing
- Scalable Inference Workloads
- A/B Testing Infrastructure
- Performance Measurement
Functional Skills
- Advertising Technology
- Recommendation Systems
- Natural Language Processing (NLP)
- Computer Vision
- Privacy-Preserving Machine Learning
- Federated Learning
- Data Analysis and Interpretation
- Algorithm Development
- Software Development and Debugging
- Code Reviews
- Production System Optimization
Soft Skills
- Strong Analytical and Problem-Solving Skills
- Excellent Written and Verbal Communication
- Technical Documentation
- Team Collaboration
- Independent Working Ability
- Critical Thinking
- Adaptability
- Quick Learning
- Interpersonal Skills
- Ability to Explain Technical Concepts
Roles & Responsibilities:-
1. Machine Learning Model Development
- Design, develop, and optimize machine learning algorithms for Apple Ads platforms.
- Build models to improve advertising relevance, forecasting, and performance.
- Work with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Explore modern neural network architectures, including Transformers, DNNs, and RNNs.
- Participate in developing and improving machine learning training pipelines.
2. Large-Scale Data Analysis & Processing
- Work with large-scale datasets to identify meaningful patterns and insights.
- Analyze complex data to improve advertising performance and user experience.
- Work with database systems, including SQL and NoSQL.
- Explore distributed data processing technologies such as Spark, Hadoop, and Flink.
- Support scalable data processing and inference workloads.
3. Model Optimization & Performance Engineering
- Explore model optimization techniques such as quantization and tensor parallelism.
- Improve machine learning inference performance and efficiency.
- Work with technologies such as ONNX Runtime, TensorRT, and vLLM.
- Support the development of high-performance machine learning systems.
- Evaluate model performance and identify opportunities for optimization.
4. AI, GenAI & Reinforcement Learning
- Explore generative AI and agentic system applications in machine learning workflows.
- Work with reinforcement learning concepts and explore/exploit strategies.
- Understand bandit-based optimization techniques.
- Investigate opportunities to improve advertising recommendations and decision-making.
- Contribute to research involving advanced AI technologies.
5. Software Engineering & Production Development
- Write clean, efficient, and maintainable code for production systems.
- Participate in software development, debugging, and code review activities.
- Use Git and version control systems to manage development work.
- Collaborate with engineers to improve platform performance and reliability.
- Support the development of scalable advertising technology solutions.
6. Experimentation & Performance Measurement
- Work with A/B testing infrastructure and experimentation processes.
- Analyze model performance and advertising outcomes.
- Evaluate system performance at scale.
- Identify opportunities to improve ad relevance and user experience.
7. Privacy-Preserving Machine Learning
- Contribute to developing privacy-preserving advertising solutions.
- Explore privacy-focused machine learning techniques.
- Gain exposure to approaches such as federated learning.
- Support Apple’s commitment to user privacy and responsible advertising technology.
8. Cross-Functional Collaboration
- Work alongside experienced software engineers and machine learning specialists.
- Communicate technical findings with engineering and other functional teams.
- Participate in technical discussions and collaborative development activities.
- Contribute to delivering high-quality machine learning solutions.
About the Company:-
Apple is a global technology company known for developing innovative products, software, and digital services that transform how people communicate, work, and interact with technology.
Apple focuses on delivering exceptional customer experiences through hardware, software, and services.
Apple Ads is part of Apple’s Services business and provides advertising solutions across platforms such as the App Store, Apple News, Apple Maps, and MLS Season Pass.
The Apple Ads team focuses on delivering relevant advertising experiences while prioritizing user privacy, trust, and value for advertisers.
Apple Hiring: PhD Intern – Apple Ads (Machine Learning) 2026 Application Process:-
Apply Link:- Click Here To Apply
Note:- Only the shortlisted candidates will be notified for the further interview process.
