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