AI / ML Solutions Engineer

BAE Systems, Inc. is seeking an AI/ML Engineer for its Enterprise Integration team. The role designs, develops, and deploys machine-learning and large language model solutions, translating business needs into actionable solutions and supporting data analysis and integration opportunities.

Responsibilities:

• Own end-to-end solutions of design, develop, and deploy robust machine-learning algorithms, including large language models
• Collaborate with stakeholders to understand business requirements and translate them into actionable solutions
• Conduct data discovery and analysis by cleaning, preprocessing, and transforming raw data into usable formats, ensuring data quality and integrity
• Produce visualizations and insights with the goal of communication to both technical and non-technical audiences
• Develop and train large language models using deep learning techniques, such as transformers and recurrent neural networks
• Participate in BAE Systems citizen developer programs centered around AI and become a resource for the system admin and integration services team
• Work closely with the existing AI/ML team at BAE Systems to leverage their expertise, share knowledge, and drive innovation in AI/ML solutions

Requirements:

• 8+ years of professional experience as an AI/ML Engineer, with a focus on generative AI and machine learning
• Bachelor's degree in a related field or equivalent combination of education and work experience
• Excellent communication and presentation skills
• Experince with canonical standards
• Strong understanding of large language models (LLMs) and their applications in AI
• Experience with Agent + RAG system and its application in data science and AI
• Proficiency in Python/R programming languages and popular machine learning libraries such as langchain, scikit-learn, TensorFlow, and PyTorch
• Experience with data visualization tools such as Tableau, Power BI, and others
• Familiarity with cloud-based services and solutions such as AWS, Azure, and Dataiku
• Graph experience is required, including graph databases, graph algorithms, and graph-based data analysis
• Experience with data mapping and modeling is a plus
• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related field
• Experience working with large datasets and high-performance computing environments
• Strong understanding of data modeling, statistical inference, and machine learning techniques
• Experience with Docker and containerization
• Familiarity with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines
• Experience with cloud-based data warehousing and big data processing (e.g., AWS Glue, Apache Spark)