What are the responsibilities and job description for the Machine Learning Architect position at SLB?
Full-time or part-time: Full-time
Job title: Machine Learning Architect
Job Location: 2700 Sand Hill Road, Menlo Park, CA 94025
Job Description:
Lead the design and implementation of state-of-the-art machine learning models and algorithms to solve complex business problems. Utilize various techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning, to extract insights from large datasets. Conduct exploratory data analysis to uncover patterns, trends, and relationships in the data. Identify relevant features and variables for model development and feature engineering. Develop data preprocessing, cleansing, and augmentation strategies to improve model performance. Ensure that machine learning models are transparent and interpretable by utilizing explainable AI techniques. Develop methods to interpret model predictions and comprehend model behavior, especially in high-stakes or regulated domains. Lead the development of backend services and infrastructure to support machine learning applications across various platforms and surfaces, ensuring seamless integration with existing systems. Design GPU optimized model pipelines to efficiently process diverse data modalities, including images, vectors, and 3D assets. Design internal AI platforms and frameworks for model inference and deployment and develop highly scalable and resilient systems to efficiently handle large-scale machine learning workloads. Collaborate closely with cross-functional teams of data scientists, software engineers, and product managers to employ innovative architectures and cutting-edge techniques to develop optimized solutions for business problems and offer technical leadership to ensure alignment with organizational goals.
Minimum Education & Experience Requirements:
Master’s degree, or foreign educational equivalent, in Computer Science, Mathematics, Physics, Applied Science, or a related STEM field, plus 2 years of post-baccalaureate experience in job offered or any Machine Learning/engineering related job titles.
Applicants must have 2 years of experience in the following: (1) data analytics, developing Machine Learning (ML) algorithms, optimization methods, and Deep Learning (DL) and Neural network libraries to optimize neural networks and train and evaluate different models; (2) Natural Language Processing, Computer Vision Technologies, Reinforcement learning, and semi-supervised learning; (3) Software development and programming skills with databases and ML frameworks; (4) data science development tools and languages including R, Python, Java, TensorFlow, PyTorch, Flask; (5) developing technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of systems; (6) Generative AI technologies and Foundational Models; and (7) processing multivariate data sets collected from equipment operations, manufacturing tests, and diagnostic routines.
Compensation for role: $200,304- $231,600/year
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Job title: Machine Learning Architect
Job Location: 2700 Sand Hill Road, Menlo Park, CA 94025
Job Description:
Lead the design and implementation of state-of-the-art machine learning models and algorithms to solve complex business problems. Utilize various techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning, to extract insights from large datasets. Conduct exploratory data analysis to uncover patterns, trends, and relationships in the data. Identify relevant features and variables for model development and feature engineering. Develop data preprocessing, cleansing, and augmentation strategies to improve model performance. Ensure that machine learning models are transparent and interpretable by utilizing explainable AI techniques. Develop methods to interpret model predictions and comprehend model behavior, especially in high-stakes or regulated domains. Lead the development of backend services and infrastructure to support machine learning applications across various platforms and surfaces, ensuring seamless integration with existing systems. Design GPU optimized model pipelines to efficiently process diverse data modalities, including images, vectors, and 3D assets. Design internal AI platforms and frameworks for model inference and deployment and develop highly scalable and resilient systems to efficiently handle large-scale machine learning workloads. Collaborate closely with cross-functional teams of data scientists, software engineers, and product managers to employ innovative architectures and cutting-edge techniques to develop optimized solutions for business problems and offer technical leadership to ensure alignment with organizational goals.
Minimum Education & Experience Requirements:
Master’s degree, or foreign educational equivalent, in Computer Science, Mathematics, Physics, Applied Science, or a related STEM field, plus 2 years of post-baccalaureate experience in job offered or any Machine Learning/engineering related job titles.
Applicants must have 2 years of experience in the following: (1) data analytics, developing Machine Learning (ML) algorithms, optimization methods, and Deep Learning (DL) and Neural network libraries to optimize neural networks and train and evaluate different models; (2) Natural Language Processing, Computer Vision Technologies, Reinforcement learning, and semi-supervised learning; (3) Software development and programming skills with databases and ML frameworks; (4) data science development tools and languages including R, Python, Java, TensorFlow, PyTorch, Flask; (5) developing technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of systems; (6) Generative AI technologies and Foundational Models; and (7) processing multivariate data sets collected from equipment operations, manufacturing tests, and diagnostic routines.
Compensation for role: $200,304- $231,600/year
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Salary : $200,304 - $231,600
