Developer T4

"WE DO WHAT WE SAY "JTSi is a federal government consulting firm, providing technical services to the Federal Government, i.e., DoD, Client and various Civilian Agencies. We are proud to have earned the reputation of honesty, integrity and the ability to build long-term professional relationships with our employees and clients. Please visit our website at www.JTSUSA.com to learn more about who we are and what we do.Company Name: - JTSi (Johnson Technology Systems, Inc.)Title: DEVELOPER T4Location: Hybrid Office: Must be in office at least 4 days per week (Herndon, VA) with the expectation that there maybe weeks where 5 days are requiredSalary : $142K-$148K/ Year on W2Description Of Project And Tasks Citizenship: U.S. citizens Hybrid Office: Must be in office at least 4 days per week (Herndon, VA) with the expectation that there maybe weeks where 5 days are required. Conversion Status: Must be willing to convert to FTE in October 2026Sr. AI Platform Developer (Years of Experience: 7-10) Programming Languages: Mastery of Python is essential, with R, Java, and C++ also being highly valuable. Machine Learning (ML) & Deep Learning (DL): You'll need a deep understanding of ML concepts (supervised, unsupervised, reinforcement learning) and neural network architectures like CNNs and RNNs. AI/ML Frameworks and Libraries: Proficiency is required in tools like TensorFlow, PyTorch, Keras, and scikit-learn. Data Science and Analysis: Skills in data acquisition, cleaning, preprocessing, and feature engineering are crucial, along with knowledge of SQL and NoSQL databases. Big Data Technologies: Familiarity with platforms like Apache Spark and OpenSearch is often necessary for handling large-scale data. Mathematics and Statistics: A strong foundation in linear algebra, calculus, probability, and statistics is fundamental. Natural Language Processing (NLP): For language-based AI, expertise in NLP techniques and libraries such as NLTK, spaCy, and Hugging Face Transformers is key. Cloud Computing and MLOps: Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps principles is vital for deploying and managing AI models.