AI-ML Developer

Unissant•Ashburn, VA

1d•Onsite

About The Position

Unissant, Inc. is seeking an AI-ML Developer to join their team in Ashburn, Virginia. This role will support the ongoing modernization and maintenance systems for the Department of Homeland Security (DHS), Customs and Border Protection (CBP). The position is highly technical and requires peer screening of skills and experience. The ideal candidate will provide consultative, architectural, program, and engineering support, driving a big data approach to manage and enrich data for new insights. Responsibilities include developing, training, and deploying advanced AI/ML models, including generative AI techniques like LLMs, and designing innovative AI solutions for complex business challenges such as natural language processing. The role also involves optimizing model performance, developing user-friendly AI applications, collaborating with cross-functional teams, staying updated on AI/ML advancements, conducting research, and ensuring compliance with data privacy and security regulations. The developer will also be responsible for briefing technology partners, stakeholders, and management on technology solutions.

Requirements

5+ years of experience in the Information Technology field focusing on AI/ML engineering projects, MLOps/DevSecOps and technical architecture specifically.
Experience in architecture & design, with a preference for 3 years of experience deploying production enterprise applications on-prem or on cloud.
Experience with classification, forecasting, transformers, and generative models.
Experience in data visualization using tools like Plotly and Matplotlib.
Experience in large-scale, high-performance enterprise big data application deployment and solution architecture on complex heterogeneous environment.
Experience with machine learning and generative AI frameworks.
Experience with natural language processing techniques (e.g., text classification, language generation).
Solid understanding of any of the cloud platforms (e.g., AWS, Azure, GCP) and deployment strategies.
Database Knowledge: Knowledge of database systems (e.g., SQL, NoSQL) and data warehousing concepts.
Generative AI Models: Proficiency in developing, deploying, and fine-tuning generative AI models, including large language models (LLMs).
Programming Languages: Strong proficiency in programming languages such as Python, R, Java, and C/C++.
Front-end Development: Proficiency in any front-end development technologies (e.g., React, Angular, Vue.js, HTML, CSS, JavaScript).
Data Analytics: Expertise with libraries such as Pandas and NumPy for data manipulation and exploration.
ML Frameworks: Proficiency in ML Modeling concepts and frameworks like Sklearn, TensorFlow, Keras, PyTorch, and others.
Data Preprocessing: Strong skills in data encoding, normalizing, and regularizing to prepare datasets for ML models.
Deep Learning: Solid understanding of deep learning architectures such as CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), LSTMs (Long Short-Term Memory networks), and GANs (Generative Adversarial Networks), with the ability to apply them to real-world data sets and problems.
Anomaly Detection: Familiarity with anomaly detection techniques and deep learning models.
Cloud Platforms: Solid understanding of cloud services, such as AWS, Azure, or GCP, and deployment strategies.
Excellent verbal and written skills, ability to present proposals and performance data, comfortable interfacing all levels of organization.
Enthusiastic, proactive, positive attitude with great listening skills, high integrity, and the ability to work effectively in a team environment.
Ability to write clear and concise creative content in a highly confidential manner.
Solid ability to interface, inspire and motivate at various levels of the organization.
Ability to convey technical information to non-technical individuals.
Demonstrated experience communicating effectively across internal and external organizations.
Must have a current CBP BI clearance or be eligible to obtain one.

Nice To Haves

Any related systems engineering, or related technical certifications are desired.
AWS/Azure/GCP AI/ML certifications are preferred but not required.

Responsibilities

Provide consultative, architectural, program, and engineering support for a federal customer.
Drive a big data approach to execute government requirements to manage and enrich data to gather new insights.
Develop, train, and deploy advanced AI/ML models, including generative AI techniques like large language models (LLMs).
Design and implement innovative AI solutions to address complex business challenges, such as natural language processing.
Optimize model performance, ensuring accuracy, efficiency, and scalability.
Develop and maintain user-friendly AI applications and interfaces, including chatbots, virtual assistants, and generative content tools.
Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
Stay up to date with the latest advancements in AI/ML and emerging technologies, such as generative AI and reinforcement learning.
Conduct research and experiments to explore new AI techniques and applications, including prompt engineering, Advanced RAGs and fine-tuning LLMs.
Ensure compliance with data privacy and security regulations, especially when dealing with sensitive data and generative AI outputs.
Responsible for briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior levels of management.