Machine Learning Engineer - Computer Vision & LLM
Bengaluru, Karnataka, India
Apple
We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways.Summary
Posted: Nov 18, 2024Role Number:200577546
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. Do you want to impact the future of Manufacturing here at Apple through cutting edge ML techniques? This position involves a wide variety of skills, innovation, and is a rare opportunity to be working on groundbreaking, new applications of machine-learning, research and implementation. Ultimately, your work would have a huge impact on billions of users across the globe. You can help inspire change, by using your skills to influence globally recognized products' supply chain. Apple’s Manufacturing & Operations team is looking for an extraordinary Machine Learning Engineer with expertise in Computer Vision (CV) and Large Language Models (LLMs) to join our team. You will craft, design and implement our machine learning strategy to the massive iPhone, Mac, iPad supply chains and help build the future of our manufacturing systems. In this role, you will develop and deploy machine learning models to optimize processes, automate quality control, and improve operational efficiency. The role requires a candidate with practical experience fine-tuning LLMs and applying them in combination with CV techniques to tackle challenges in manufacturing environments.
Description
As a key member of our team, you’ll collaborate with different engineering and operations teams leading development of ML solutions for a variety of vision and language-based tasks and projects. You will be responsible for delivering ML technologies aligned with the fast pace new technology and short product lifecycle, while ensuring the highest standards of product quality and reliability. In this role, you’ll be embedded inside a vibrant team of machine learning engineers and data scientists. You’ll be expected to help conceive, code, and deploy machine learning models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metric. You will have the opportunity to work both independently and collaboratively to help partner teams meet predefined objectives. If you are passionate to influence the quality, speed and efficiency of our ML algorithms, come and help enable our vision to create the most refined products in the world. Join our team as a key contributor, leading the development of machine learning solutions for diverse tasks and projects. Collaborate with engineering and operations teams to deliver cutting-edge ML technologies, ensuring top-tier product quality and reliability in a fast-paced environment. KEY RESPONSIBILITIES - Develop and deploy scalable Computer Vision and Machine Learning algorithms on local and cloud-based inferencing platforms - Perform rapid prototyping to design algorithms for challenging real world manufacturing problems in the domain of Intelligent Visual Inspection. - Leverage Large Language Models to automate document analysis, knowledge extraction, and process optimization within manufacturing workflow - Fine-tune LLMs for domain-specific applications such as improving operational documentation, production reports, and automating technical analysis. - Work with resources in cross-functional teams and the factory to integrate ML applications - Abilities to independently learn new technologies; prioritize tasks and take ownership; and meaningfully present results of analyses in a clear and impactful manner
Minimum Qualifications
- Experience developing deep learning models such as CNNs, Vision Transformers, or YOLO for image-based tasks in production systems.
- Proven research and practical experience in developing algorithms for image processing, content-based video/image analysis, object detection, segmentation and tracking
- Proven experience in fine-tuning LLMs for domain-specific use cases such as document analysis and operational efficiency.
- Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
- iOS CoreImage/CoreML and native App development experience is a big plus.
- Experience deploying ML models in cloud environments (AWS, GCP, or Azure) for scalable production use.
Preferred Qualifications
- Strong grasp of deep learning principles in both Computer Vision and Natural Language Processing (NLP).
- Familiarity with LLM architectures like BERT, GPT, and experience fine-tuning these models for improved performance in manufacturing settings.
- Knowledge of machine learning and Deep Learning libraries such as PyTorch, OpenCV, Hugging Face, is essential.
- Proven ability to implement, improve, debug, and maintain machine learning models
- Familiar with version control systems such as Git
- Strong optimization and debugging skills
- Self-motivated, responsible, excellent written and verbal interpersonal skills
- Experience with handling and visualizing very large data sets and creating performance reports
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Job stats:
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Tags: Architecture AWS Azure BERT Computer Science Computer Vision CoreML Deep Learning Engineering Feature engineering GCP Git GPT LLMs Machine Learning ML models NLP OpenCV Prototyping PyTorch Research Testing Transformers YOLO
Region:
Asia/Pacific
Country:
India
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