Sylvan Learning Centers
Machine Learning Engineer, Natural Language Processing
Sylvan Learning Centers, San Mateo, California, United States, 94409
Machine Learning Engineer, Natural Language Processing
NOTE:
Exceptional candidates who can fulfill job responsibilities even in the absence of prior experience are encouraged to apply. Above all, we are looking for exceptional, versatile engineers!The Role
The AI/ML team is of critical importance to Oplus’ mission. The team works on projects that make health care safer, more efficient and effective, and accessible to a broader set of patients. The AI/ML projects are designed to ultimately deliver on the promise of AI-driven health care. As a member of the Oplus’ AI/ML team, you will be in a unique position to develop and accelerate the pace at which AI is applied to critical health care operations and deployed at the point of care. Team engineers will contribute to the development of various AI-ML products and will make critical decisions that will influence not only the team but the overall achievement of Oplus’ mission. AI/ML models designed, built, and deployed will have a direct and immediate impact on nearly 25% of the US health care population spread across 21 states.Responsibilities
Develop, prototype, benchmark, and deploy state-of-the-art NLU, NLG, IRQA, machine translation, and dialog system models.Design scalable and reliable data pipelines to implement and monitor models.Identify, research, and analyze new data sources to improve model accuracy.Work cross-functionally with software engineers, doctors, allied healthcare staff, hospital support staff, and other health system representatives to continuously improve performance.Develop production code to run locally and in the cloud – debug and tune production systems.Requirements
The team operates in both research and production settings. An ideal candidate has a strong predilection for good software and the processes that make it, including debugging/profiling, and version control.Experience with data science, statistical methods, and machine learning.Advanced knowledge in model evaluation, tuning, and performance. We train neural networks on a cluster in a distributed setting. An ideal candidate is very comfortable in cluster environments and understands the related computer systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks during training of neural networks, CUDA, pipelining/multiprocessing, etc.).We want to be at the cutting edge of deep learning applications. The ideal candidate has a strong understanding of the under-the-hood fundamentals of deep learning (layer details, backpropagation, etc.). It is additionally expected that the candidate has the ability to read and implement related academic literature and has experience in applying state-of-the-art deep learning models to NLP or closely related areas (speech, etc.).Experience with PyTorch, or another major deep learning framework such as TensorFlow, MXNet.Fluency in Linux, Git, and expert-level Python skills.A passion for improving the health of people worldwide.A strong desire to be a member of a technical team, and not be afraid to develop solutions ab initio (from first principles).Be comfortable interacting with people in a healthcare setting.Bonus Experience
Proven ability to develop and operate machine learning production systems.A track record of developing novel products.Excellence in other languages (we will plan to use C++, Rust, and Scala).Experience with SQL and noSQL databases.Location
Phoenix, AZSan Mateo, CARemote,
an option only for truly exceptional candidates .Oplus is an Equal Opportunity/Affirmative Action employer committed to diversity in the workplace.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.Oplus is also committed to working with and providing reasonable accommodations to individuals with disabilities.
Please let your recruiter know if you need accommodation at any point during the interview process.
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NOTE:
Exceptional candidates who can fulfill job responsibilities even in the absence of prior experience are encouraged to apply. Above all, we are looking for exceptional, versatile engineers!The Role
The AI/ML team is of critical importance to Oplus’ mission. The team works on projects that make health care safer, more efficient and effective, and accessible to a broader set of patients. The AI/ML projects are designed to ultimately deliver on the promise of AI-driven health care. As a member of the Oplus’ AI/ML team, you will be in a unique position to develop and accelerate the pace at which AI is applied to critical health care operations and deployed at the point of care. Team engineers will contribute to the development of various AI-ML products and will make critical decisions that will influence not only the team but the overall achievement of Oplus’ mission. AI/ML models designed, built, and deployed will have a direct and immediate impact on nearly 25% of the US health care population spread across 21 states.Responsibilities
Develop, prototype, benchmark, and deploy state-of-the-art NLU, NLG, IRQA, machine translation, and dialog system models.Design scalable and reliable data pipelines to implement and monitor models.Identify, research, and analyze new data sources to improve model accuracy.Work cross-functionally with software engineers, doctors, allied healthcare staff, hospital support staff, and other health system representatives to continuously improve performance.Develop production code to run locally and in the cloud – debug and tune production systems.Requirements
The team operates in both research and production settings. An ideal candidate has a strong predilection for good software and the processes that make it, including debugging/profiling, and version control.Experience with data science, statistical methods, and machine learning.Advanced knowledge in model evaluation, tuning, and performance. We train neural networks on a cluster in a distributed setting. An ideal candidate is very comfortable in cluster environments and understands the related computer systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks during training of neural networks, CUDA, pipelining/multiprocessing, etc.).We want to be at the cutting edge of deep learning applications. The ideal candidate has a strong understanding of the under-the-hood fundamentals of deep learning (layer details, backpropagation, etc.). It is additionally expected that the candidate has the ability to read and implement related academic literature and has experience in applying state-of-the-art deep learning models to NLP or closely related areas (speech, etc.).Experience with PyTorch, or another major deep learning framework such as TensorFlow, MXNet.Fluency in Linux, Git, and expert-level Python skills.A passion for improving the health of people worldwide.A strong desire to be a member of a technical team, and not be afraid to develop solutions ab initio (from first principles).Be comfortable interacting with people in a healthcare setting.Bonus Experience
Proven ability to develop and operate machine learning production systems.A track record of developing novel products.Excellence in other languages (we will plan to use C++, Rust, and Scala).Experience with SQL and noSQL databases.Location
Phoenix, AZSan Mateo, CARemote,
an option only for truly exceptional candidates .Oplus is an Equal Opportunity/Affirmative Action employer committed to diversity in the workplace.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.Oplus is also committed to working with and providing reasonable accommodations to individuals with disabilities.
Please let your recruiter know if you need accommodation at any point during the interview process.
#J-18808-Ljbffr