AI/Machine Learning Engineer

Brooksource is seeking a highly skilled Artificial Intelligence/Machine Learning Engineer to support a Fortune 15 health services organization within their advanced analytics and AI division. The role involves designing, developing, and deploying AI/ML solutions that drive automation and measurable business value across multiple pharmacy business units.

Responsibilities:

• Lead the development, training, and optimization of machine learning and deep learning models
• Design and implement scalable, reliable data pipelines to support AI/ML workloads
• Integrate AI systems with enterprise applications, cloud platforms, and microservices architectures
• Develop and maintain high-performance AI algorithms, ensuring efficiency, scalability, and robustness
• Collaborate with cross-functional teams to drive data-driven decision-making and align analytics initiatives with business goals
• Plan, execute, and lead analytics and AI projects from concept through deployment
• Present technical findings and model insights to stakeholders, translating complex results into actionable recommendations
• Ensure compliance with data governance, security, and regulatory standards across all modeling activities
• Mentor junior data scientists and engineers, promoting best practices in AI/ML development and MLOps

Requirements:

• 6+ years of experience developing and deploying machine learning or AI solutions in a professional environment
• Bachelor's degree in Computer Science, Data Science, Engineering, or related field (Master's preferred)
• Hands-on experience building AI-driven chatbots, RAG pipelines, and AI agents using frameworks such as LangChain
• Advanced proficiency in Python and SQL for data science and model development
• Strong understanding of supervised, unsupervised, and reinforcement learning techniques
• Expertise in deep learning architectures (CNNs, RNNs, Transformers) and modern NLP methods
• Experience designing scalable AI systems, including microservices, REST APIs, and distributed model serving
• Proficiency with cloud platforms such as AWS, Azure, GCP, and Databricks
• Knowledge of MLOps best practices, including CI/CD, containerization (Docker, Kubernetes), and secure access provisioning
• Strong communication skills with the ability to convey technical insights to both technical and non-technical audiences
• Experience with distributed computing frameworks such as Apache Spark
• Familiarity with advanced AI tools and platforms including PyTorch, Hugging Face, and Kafka
• Demonstrated leadership in driving AI/ML initiatives within a business environment
• System design expertise with a focus on scalability, reliability, and performance in AI deployments