Research, benchmark and adapt state-of-the-art AI based models on real field measurements for anomaly detection, event recognition, and inference etc. Extract critical business insights using advanced data analytics on large scale databases containing multi-modal field measurements. Design and optimize algorithms enabling efficient downhole data compression and inference at the edge. Develop hybrid models by merging the predictive insights of data-driven approaches with physics-driven mechanical models to model field behavior. Engineer smart sensor fusion frameworks to integrate multiple sources of field measurement for effective parameter estimation with uncertainty quantification. Orchestrate and optimize MLOps workflows to streamline the training, validation, deployment, and monitoring of machine learning models. Design and integrate robotic systems encompassing both hardware and software components, to enhance operational efficiency through automation. Develop solutions for Bayesian state estimation, uncertainty quantification, path planning and robotics control. Lead the adoption of AI based algorithms that improve robustness and scalability. Collaborate and mentor interns and contractors, present technical talks at conferences and symposia within and external to the company. Work with domain specific tools including Maxwell, Telemetry Tool Planner and Conveyance tool Planner.

Master's degree in Computer Science, Electrical and Computer Engineering, Electronics and Communication Engineering, or a related STEM field, or a foreign degree equivalent plus 3 years post-baccalaureate experience in job offered or any Machine Learning/Engineering related job titles.

Must possess 3 years of experience in the following: (1) Programming Languages - Python, MATLAB, and C++ to develop algorithms packaged as software solutions, and for analytics/inference applications; (2) Deep Learning Frameworks - Tensorflow, Pytorch, Keras to design, train and infer deep learning models like neural networks as part of data-driven modeling; (3) Data Science Platforms Dataiku and Supervisely to interact with database systems and develop advanced analytics workflows to label images/videos, train and deploy deep neural network models; (4) Robotics Tool Actin to develop motion control sequences for industrial robots and integrate robotic software solutions; (5) Computer Vision Libraries OpenCV and Halcon to integrate machine vision systems and develop advanced imaging and video processing applications; (6) MLFLow to automate machine learning models; (7) Maxwell for data extraction and processing; and (8) and Bit inspection, Depth estimation, Borehole Image compression.

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