Machine Learning Engineer
US-Remote
NCI Information Systems Inc.
Req #: 7698
Type: Regular Full-Time
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Overview: Empower AI is AI for government. Empower AI gives federal agency leaders the tools to elevate the potential of their workforce with a direct path for meaningful transformation. Headquartered in Reston, Va., Empower AI leverages three decades of experience solving complex challenges in Health, Defense, and Civilian missions. Our proven Empower AI Platform(r) provides a practical, sustainable path for clients to achieve transformation that is true to who they are, what they do, how they work, with the resources they have. The result is a government workforce that is exponentially more creative and productive. For more information, visit www.Empower.ai. Empower AI is proud to be recognized as a 2022 Military Friendly Employer by Viqtory, the publisher of G.I. Jobs. This designation reflects the company's commitment to hiring and supporting active-duty and veteran employees. Responsibilities: Empower AI: The Machine Learning Engineer will design, build, and integrate high quality solutions using Machine Learning techniques. In assuming this position, you will be a critical contributor to meeting Empower AI's mission: To deliver innovative, cost-effective solutions and services that enable our customers to rapidly adapt to dynamic environments. * Design, build, and integrate high quality solutions using machine learning techniques * Work with a variety of different types, sources, and volumes of data by scraping, cleaning, extracting, and providing assessment to guide a viable machine learning solution * Adapt open-source projects, implement research papers, and develop novel solutions to solve diverse business problems * Being able to adapt and deal with various constraints such as varied data quality, security constraints, hardware limitations, and other resource limitations * Staying current with state-of-the art techniques in machine learning from newly published research papers * Effectively communicate realistic goals and status to varied stakeholders including internal and external customers * Work with cross functional teams to integrate ML solutions within existing or in progress applications * Lead or participate in project development during all steps of the Software Development Lifecycle, including client requirement definition, architecture design, production deployment, and maintenance activities * Provide support for pilot projects and proof of concepts with accelerated timelines while working closely with solutions architects and professional services teams * Work in a remote environment autonomously with minimal oversight Qualifications: Requirements: * Technical experience in Machine Learning Engineering/Data Science or Software Development with recent coursework in ML/DS * Experience building and deploying Machine Learning Models trained on real data ideally deployed in a production environment * Experience with structured and unstructured datasets * Strong individual contributor who can operate autonomously within all stages of development lifecycle on cross functional teams or as a sole contributor * Comfortable working in at least one Python ML framework ideally both PyTorch and Tensorflow * Comfortable using version control * Secret or ability to obtain a Secret clearance * BS in Computer Science, Engineering, or related technical field * 10-15 years experience Preferred Education and Experience: * Deep knowledge of modern NLP techniques, frameworks, and architectures like transformers * Experience with computer vision machine learning techniques * Understanding of or experience in implementing deep neural networks * Experience with distributed training * Familiar with semi-supervised techniques * Experience with reinforcement learning techniques * Varied deployment experience * Experience developing APIs * Comfortable working with databases * Experience gathering and curating datasets * Experience monitoring models in production * Strong software development skillset * Experience generating synthetic data
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