
Senior Artificial Intelligence Specialist
- Washington DC
- Permanent
- Full-time
- Holding a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related technical fields, with equivalent work experience in data science, machine learning, and cloud technologies.
- Demonstrating advanced proficiency in Python and other programming languages (e.g., Java, Bash), with expert-level skills in data science development, scripting, and automation.
- Applying deep knowledge of AI/ML, Natural Language Processing (NLP), and Generative AI, including hands-on experience with frameworks such as PyTorch, Transformer, TensorFlow, SpaCy, and Scikit-learn.
- Designing, developing, and deploying AI/ML solutions in cloud environments, particularly AWS, using services such as SageMaker, Bedrock, and Databricks, and tools like Docker, Kubernetes, GitLab, and Terraform.
- Building and optimizing ETL/ELT pipelines, data models, and integrations from various sources into centralized data lakes using Databricks, Spark, and SQL for scalable analytics.
- Implementing data governance, security best practices, and compliance with federal cloud regulations, including FedRAMP and FISMA, across infrastructure and applications.
- Practicing DevSecOps and CI/CD methodologies to automate testing, deployment, and monitoring of cloud-native AI solutions and infrastructure.
- Conducting fine-tuning of LLMs (e.g., GPT, Llama, Claude, Mistral) and contributing to open-source AI projects or communities to advance generative AI capabilities.
- Collaborating with cross-functional teams and communicating complex technical concepts clearly to both technical and non-technical stakeholders.
- Maintaining industry certifications in AWS cloud architecture, machine learning, and development, while staying current on emerging trends and best practices in AI, cloud, and data engineering.
- US Citizenship
- Collaborating with cross-functional teams to identify opportunities and design innovative AI/ML and Generative AI solutions tailored to business challenges.
- Researching, developing, and deploying new machine learning and AI features/products using an iterative, hands-on approach from model selection to production integration.
- Maintaining and improving existing AI/ML implementations by monitoring model performance, retraining models, and enhancing training datasets and feature sets.
- Leveraging AWS AI services (e.g., SageMaker, Bedrock, Comprehend, Rekognition) to accelerate development, deployment, and operationalization of AI solutions.
- Designing and managing scalable, secure, and repeatable cloud-based data pipelines and infrastructure using AWS tools such as S3, Redshift, and DynamoDB.
- Operationalizing and automating the deployment and monitoring of Generative AI systems with observability, controllability, and performance tuning in place.
- Ensuring AI system security through best practices, regular audits, and integration with DevSecOps and CI/CD workflows for secure and efficient deployment.
- Defining and implementing best practices for data modeling, including Bronze/Silver/Gold lakehouse architecture within Databricks to support analytical and operational workloads.
- Translating business requirements into data-driven solutions and providing thorough documentation, including data models, dictionaries, and system artifacts.
- Leading training initiatives, workshops, and promoting a culture of innovation and adoption of next-generation analytics and AI technologies across the organization.
- A Bachelor’s degree in Computer Science, Information Systems, or other related field is required or related work experience
- Certifications in AWS AI or Machine Learning, as appropriate