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- Develop and deploy machine learning models from initial research to production, ensuring scalability and performance for visibility, prediction, demand forecasting, and freight audit use cases.
- Own the end-to-end ML pipeline (data processing, model development, testing, deployment, and continuous optimization), implementing MLOps best practices for reliability and scalability.
- Architect, build, and maintain AI-driven data pipelines using AWS Bedrock and other AWS services, ensuring data governance, security, and quality across the data lifecycle.
- Evaluate and implement agentic AI solutions to automate workflows, incorporating compliance requirements (especially in financial contexts) and optimizing operational efficiency.
- Collaborate with cross-functional teams to gather requirements, perform feature engineering, tune models, conduct code reviews, and ensure production-ready solutions.
- Implement and maintain data governance, data security, and data quality measures throughout the data lifecycle.
- Work closely with engineering teams to integrate AI-driven functionalities into our products.
- Participate in code reviews and provide technical expertise to ensure best practices in AI/data engineering.
- Continuously research and evaluate emerging AI and data technologies to enhance solutions, tools, and processes, driving business value and innovation.
- Bachelor's degree in Computer Science, Engineering, or a related field
- Approximately 5 years of experience in AI/data engineering roles
- Proficiency in one or more programming languages commonly used in AI/data engineering (e.g., Python, Node.js)
- Strong knowledge of ETL/ELT processes, data warehousing concepts, and data pipeline orchestration
- Practical experience with machine learning model development, including model training, tuning, and deployment
- Familiarity with REST APIs or GraphQL endpoints
- Experience working in Scrum Agile software engineering teams
- Excellent problem-solving, analytical, and communication skills
- Experience with Next.js and TypeScript.
- Familiarity with Terraform or other Infrastructure as Code (IaC) tools.
- Exposure to large language models or generative AI techniques.
- Experience with advanced data visualization tools or analytics platforms.