AI Engineer
Pi-Square Technologies LLC
- Vienna, VA
- Training
- Full-time
We are seeking an experienced AI Engineer to design, develop, and optimize advanced machine learning and artificial intelligence models that drive business value. This role involves working across the entire AI lifecycle-from research, model design, training, and validation to deployment and monitoring. The engineer will collaborate closely with data scientists, data engineers, and visualization experts to deliver AI solutions, while also researching emerging technologies and advancing the organization's adoption of cutting-edge AI practices, including Large Language Models (LLMs) and Agentic AI frameworks. Looking for candidates with a computer science background and experience in neural networks, TensorFlow/PyTorch, Agentic A.I. frameworks, and large language models (LLMs).Key Responsibilities
- Design, build, and enhance machine learning models through all phases of development (design, training, validation, deployment, monitoring).
- Analyze large-scale numerical and textual datasets to uncover insights, patterns, and trends.
- Partner with cross-functional teams (data engineering, data science, visualization) to deliver AI-driven solutions.
- Research, evaluate, and adopt emerging AI and ML technologies.
- Develop and deploy data science solutions leveraging cloud computing infrastructure.
- Explore, fine-tune, and implement Large Language Models (LLMs) for domain-specific use cases.
- Research and experiment with Agentic AI frameworks to enhance automation and reasoning capabilities.
- Support Computer Vision, video analytics, and Natural Language Processing/Understanding projects.
- Document models, processes, and results to ensure transparency and reproducibility.
- Perform other duties as assigned.
- Advanced degree in Computer Science, Mathematics, Physics, Statistics, or related field.
- Strong expertise in machine learning model design, training, validation, and monitoring.
- Solid foundation in statistical modeling, ML algorithms, and their trade-offs.
- Hands-on experience with cloud platforms (Azure, AWS, or GCP).
- Experience with Computer Vision, image/video analytics, and NLP/NLU.
- Proficiency with deep learning frameworks such as TensorFlow or PyTorch.
- Familiarity with LLMs: research, fine-tuning, and implementation for domain-specific use cases.
- Strong problem-solving, collaboration, and independent work skills.
- Excellent written, verbal, and presentation skills to communicate complex concepts to technical and non-technical audiences.
- AI Model optimization on GPU architectures using C++/CUDA.
- Knowledge of MLOps and CI/CD pipelines for deploying and monitoring models in production.
- Understanding of AI security and safety principles.
- Experience with advanced reinforcement learning techniques.
- Background in speech recognition applications.
- Hands-on experience with Microsoft Azure AI and ML services.