Deep Learning Software Engineer
The Applied Machine Learning group is a fast moving agile team focused on customer and application centric innovation. They are responsible for research and development of AI methodologies and 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 within the Applied ML team, the candidate will be responsible for innovative research, modeling, and prototyping of AI/ML techniques, generating data insights and optimizations for Intel platforms and applying them towards real world use cases working with internal and external customers.
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, Bayesian analysis and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, NLP, Robotics, etc. Interacts with customers 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 end to end 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.
- The candidate will play a key technical role for machine learning & deep learning platform components development based on various frameworks and hardware (such as CPU, GPU, accelerators).
- They 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.
An ideal candidate would exhibit behavioral skills that indicate:
- Excellent written and oral communication skills and be able to clearly communicate technical details and concept
- Ability to clearly understand real world use cases and associated pain points, investigate the utility of AI/ML techniques towards solving the pain points, translating them into technical requirements towards developing tangible solutions.
The candidate must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. This is an entry level position and would be compensated accordingly.
- Ph.D. degree in Computer Engineering, Computer Science or Electrical Engineering or related technical discipline with a focus on cutting edge AI/ ML research and applications
1+years of machine learning and deep learning techniques:
- Experience with or knowledge of modern machine learning libraries frameworks and techniques eg TensorFlow PyTorch Deep Learning Transfer Learning Keras NLP feature engineering automated hyperparameter tuning and conventional machine learning techniques
- Software development and coding experience in python and C++ /other languages
- Experience in data collection model building testing and validation
- Experience delivering AI/ML solutions to address real world use cases working with collaborators.
- Strong publication record with papers, presentations and talks in conferences such as ICML, CVPR, NeurIPS, ICLR, SIGGRAPH and others.
- Strong participation and performance in leaderboards in Kaggle competitions and other AI/ML challenges
Inside this Business Group
- You should have a proven track record and proficiency in machine learning & deep learning research and applications demonstrated by publications, product delivery, or other means.
- Experience on developing cutting edge AI/ML algorithms and performance optimization for Pytorch/TF/MXNet framework, MLPerf benchmark and other SOTA workload
- Ability to utilize and develop HPO and NAS algorithms, Bayesian optimization, Optuna, Ray Tune
- Ability to run workloads using Big data platforms, Hadoop, Spark, Modin
- Utilize ML DevOps such as MLflow, Airflow and Kubeflow towards applications
Intel Architecture, Graphics, and Software (IAGS) brings Intel's technical strategy to life. We have embraced the new reality of competing at a product and solution level—not just a transistor one. We take pride in reshaping the status quo and thinking exponentially to achieve what's never been done before. We've also built a culture of continuous learning and persistent leadership that provides opportunities to practice until perfection and filter ambitious ideas into execution.
US, Oregon, Hillsboro
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.