As a Senior AI/ML Engineer, you will be a key leader in the entire lifecycle of our clients strategic AI/ML initiatives. You will be instrumental in architecting and implementing sophisticated AI models, spanning both robust traditional methodologies and cutting-edge generative techniques, strategically leveraging the best of open-source and proprietary technologies. You will collaborate with visionary AI product designers, a talented team of Data Scientists and Engineers, and innovative Software Engineers to build robust, scalable, secure, and impactful AI-powered products.

What You'll Do:

● Design, development, and deployment of advanced AI models and end-to-end pipelines for a diverse portfolio of government applications, encompassing both traditional ML and state-of-the-art Generative AI.

● Masterfully work with complex and sensitive datasets, strategic data preprocessing, insightful feature engineering, and rigorous analysis to prepare data for optimal model training, precise fine-tuning, model calibration and comprehensive evaluation.

● Expertly utilize and potentially contribute to leading open-source AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, and a range of specialized ML/GenAI tools.

● Maintain robust and highly scalable AI pipelines leveraging open-source orchestration, deployment, and monitoring tools (e.g., Kubeflow, MLflow, Airflow, Langchain, LlamaIndex, n8n, MCP), ensuring security and compliance.

● Proactively experiment with and strategically implement cutting-edge techniques in both traditional and Generative AI.

● Contribute significantly to the evolution of our internal AI/ML infrastructure and champion best practices, rigorously promoting code quality, ensuring reproducibility of results, and establishing efficient and secure workflows.

● Critically evaluate model performance using appropriate centric metrics and proactively implement robust AI safeguard strategies to ensure ethical, transparent, and reliable AI solutions, driving continuous improvement and optimization.

What You'll Bring:

● Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a closely related quantitative field with a strong analytical foundation.

● A minimum of 3 years of demonstrable and impactful hands-on experience in the end-to-end lifecycle of developing and deploying robust machine learning models or GenAI solutions in a demanding production environment.

● Deep theoretical understanding and significant practical experience in a broad spectrum of traditional machine learning algorithms and techniques, with a proven ability to apply them effectively to real-world problems.

● Strong demonstrated experience with the intricacies of generative AI models and techniques, including practical application of large language models (LLMs), diffusion models, and generative adversarial networks (GANs).

● Exceptional proficiency in core programming languages essential for AI/ML, particularly Python, with a focus on writing clean, efficient, and well-documented code.

● Extensive practical experience with key open-source AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers) and a strong understanding of their underlying principles.

● Proven experience in building and deploying resilient AI pipelines utilizing open-source orchestration, deployment, and monitoring tools (e.g., Kubeflow, MLflow, Airflow, Langchain, LlamaIndex, n8n, MCP, Docker, Kubernetes), with a focus on security and scalability.