* Define the ML/AI strategies and product direction for all HueDx intelligent platforms* Design, engineer and contribute to all core ML/AI technologies* Establish cloud resources for testing, deploying and monitoring all ML/AI resources* Manage data acquisition and preparation pipelines* Drive product vision to capture future market opportunities

* Oversee transfer of technology from Ephesoft to Tungsten Automation following acquisition* Collaborate with a team of 5 ML/AI engineers to develop solutions to intelligent document processing* Spearhead integration of new technologies into the Tungsten Automation Platform* Lead CI/CD and MLOps efforts in model development and cloud deployments* Research and prototype emerging technologies in NLP and CV to apply across Tungsten's product offerings

* Lead, grow and mentor a team of 5 ML engineers, data scientists, and cloud engineers across multiple time zones* Drive complex, company-wide technology initiatives with agile methodologies* Build large, scalable system architectures in partnerships with multiple departments* Communicate roadmaps, results and analyses to senior executives, engineers, and business stakeholders* Contribute to code reviews, on-call rotations and daily operations with a player-coach/lead-by-example mentality* Foster an environment of continual education and self-improvement* Drive the adoption of MLOps best practices and cloud-based solution management

* Research, implement and deploy large-scale machine learning applications within the AWS ecosystem* Develop cutting-edge deep learning solutions in TensorFlow including YOLO object detectors, FRCNNs and SSDs, HuggingFace visual transformers, document autoencoders, image classifiers, active learning systems and layout analyzers.* Implement classical machine learning algorithms for clustering, text classification, image analysis, and image registration/warping* Collaborate across departments to align strategic business objectives with data science and engineering efforts* Lead and mentor a team of data scientists, ML engineers and software engineers* Guide the long-term AI development plan within the company

Assist clients in developing customized scientific computing and AI products for their sector, and manage or create datasets from existing sources to solve client objectives. Previous projects include: - Collected, cleaned and applied datasets for deep learning solutions- Built neural networks and algorithmic approaches to solve a priori problems with monocular hyperfocal distance, depth mapping and autofocus in photography- Designed a system using unsupervised machine learning and neural networks to detect and classify anomalous radio frequency signals in the spectral domain- Implemented Bayesian optimization solutions in real-time to enhance biological cell growth and health- Created fully convolutional neural network architectures to process hyperspectral microscopy images- Utilized word embeddings and recurrent neural networks to identify, unify and classify key concepts within medical device safety reports

- Researched and applied machine learning algorithms to analyze and quantify medical device and drug safety data- Designed and constructed NLP components for processing big-data medical texts- Interpreted raw insurance data to quantify litigation risk profiles in medical devices

-Construct methods for data mining text in order to locate valuable and relevant information-Develop proprietary software and NLP tools to handle large amounts of data-Utilize machine learning algorithms to create predictive-analytics tools-Interface the UMLS into developed software for high-level medical data processing and concept mapping

-Handled technical troubleshooting and network support within a professional environment-Provided managerial support and resource management for other workers-Directed and trained new technicians and ensured quality of service through review process