Sharp Decisions · 6 hours ago
Sr. AI Platform Developer (509)
Sharp Decisions is seeking a Sr. AI Platform Developer with extensive experience in AI and machine learning. The role involves developing AI platforms, utilizing programming languages, and applying machine learning concepts and frameworks to deliver effective solutions.
Responsibilities
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
Qualification
Required
Citizenship: U.S. citizens
Hybrid Office: Must be in office at least 4 days per week (Herndon, VA)
Years of Experience: 7-10
Mastery of Python is essential, with R, Java, and C++ also being highly valuable
Deep understanding of ML concepts (supervised, unsupervised, reinforcement learning) and neural network architectures like CNNs and RNNs
Proficiency is required in tools like TensorFlow, PyTorch, Keras, and scikit-learn
Skills in data acquisition, cleaning, preprocessing, and feature engineering are crucial, along with knowledge of SQL and NoSQL databases
Familiarity with platforms like Apache Spark and OpenSearch is often necessary for handling large-scale data
A strong foundation in linear algebra, calculus, probability, and statistics is fundamental
Expertise in NLP techniques and libraries such as NLTK, spaCy, and Hugging Face Transformers is key
Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps principles is vital for deploying and managing AI models