Intel AI Software Solutions Engineer 

United States, California, Santa Clara 

872746658

Job Description:

The Applied Machine Learning group is responsible for innovation and development of end-to-end AI solutions, technology proof of concepts, and IP development of current and future ML workloads for Intel architecture and silicon serving consumer and corporate business requirements.

In this position, you will be responsible for research, modeling, prototyping, productizing of ML techniques, generating data insights and optimizations for Intel platforms.

Responsibilities include but are not limited to:

• Builds machine learning based products/solutions, which provide descriptive, diagnostic, predictive, or prescriptive models based on data.
• Uses or develops machine learning algorithms, such as supervised and unsupervised learning, deep learning, reinforcement learning, generative AI, large language model and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, Natural Language Processing, Recommendation System, Graph Neural Network, Robotics, etc.
• Interacts with users to define requirements for breakthrough product/solutions.
• In either research environments or specific product environments, utilizes current programming methodologies to translate machine learning models and data processing methods into software.
• Completes programming, testing, debugging, documentation and/or deployment of the solution/products.
• Engineers big data computing frameworks, data modeling and other relevant software tools.
• You will play a key technical role for end-2-end machine learning and deep learning platform development based on various frameworks and hardware (such as CPU, GPU, accelerators).
• You will also be responsible for developing AI ML solutions and methodologies to bring the best performance, accuracy, efficiency, and ease-of-use to customers by working with internal and external partners.

The job scope may include but not limited to:

• End-2-end ML and DL platform component innovation and feature development in data ingestion, feature engineering, distributed training via data and model parallelization, hyper-parameter optimization, neural architecture search, model compression, quantization, distillation, and model serving.
• Algorithm and model development of advanced technologies in computer vision, natural language processing, large language model, recommendation, graph analytics, reinforcement learning, and other domains.
• Machine learning framework and workload performance profiling, optimization, insights generation for benchmark such as MLPerf as well as real-world customer use cases.
• Software and tools development in python, C++, and other languages as required.

Behavioral traits that we are looking for:

• Excellent communication skills.
• Willing to clearly communicate technical details and concept.

Qualifications:

Minimum qualifications,you must possess the below minimum qualifications to be initially considered for this position:

• Master´s degree with 4+ years or Ph.D. with 2+ years of experience in: Computer Engineering, Computer Science, Data Science, Software Engineering, Electronic Engineering, Physics, Mathematics, Aerospace engineering, applied mathematics, mechanical engineering, or related STEM disciplines

4+years of the following technical skills:

• Experience in deep learning frameworks such as PyTorch, TensorFlow, working on CPU / GPU / AI accelerators for ML/DL.
• Experience in GenAI frameworks such as transformers, PEFT, diffusers, TGI, TEI, vLLM or SGLang for both training finetuning and inference serving.
• Working with Performance optimization / tuning.
• Experience in computer vision, recommendation, natural language processing, or reinforcement learning.

Preferred qualificationsare in addition to the minimum requirements and are considered a plus factor in identifying top candidates:

• Proven track record of a leadership role in machine learning, deep learning research and applications demonstrated by patents, publications, product delivery, or other means.
• Experience on performance optimization for PyTorch framework, MLPerf benchmark and other SOTA workload.
• Distributed training, DeepSpeed, Torch DDP and FSDP, Ray SGD.
• Inference optimization such as quantization, sparsity, distillation.GenAI end-2-end workflow development and deployment for model serving, RAG and agent system.

Experienced HireShift 1 (United States of America)US, California, Santa Clara
Position of Trust

Weoffer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here:

Annual Salary Range for jobs which could be performed in the US:

This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.