Machine Learning Engineer supporting the Enterprise Machine Learning team in developing advanced solutions. Collaborating with stakeholders and driving data science initiatives in a hybrid work environment.
About the role
- Lead AI/ML Engineer at UPS, focusing on advanced solutions for complex business challenges. Collaborate with teams to drive innovation in AI and machine learning environments.
Responsibilities
- Lead the design, development, and deployment of advanced AI/ML solutions to solve complex business problems and drive strategic innovation across products and services.
- Provide technical leadership and mentorship to a team of AI/ML engineers and data scientists, guiding best practices in model development, deployment, and lifecycle management.
- Architect scalable AI systems and oversee the integration of machine learning models into production environments in collaboration with engineering, product, and infrastructure teams.
- Drive the development of intelligent chatbots, AI agents, and automation solutions that enhance customer engagement and operational efficiency.
- Establish and enforce robust testing, monitoring, and governance frameworks to ensure models meet standards for accuracy, fairness, transparency, and reliability.
- Continuously monitor model performance post-deployment and lead iterative improvement efforts using real-world data and user feedback.
- Serve as a key technical advisor, communicating complex AI concepts and outcomes to both technical and non-technical stakeholders, and influencing AI strategy across the organization.
- Evaluate emerging AI technologies, tools, and trends, and recommend their adoption to keep the company at the forefront of innovation.
Requirements
- 5+ years of professional experience in software/IT with a focus on artificial intelligence and machine learning
- Deep expertise in Python and ML libraries/frameworks such as TensorFlow, PyTorch, and Scikit-learn
- Strong understanding of machine learning methodologies including supervised/unsupervised learning, model evaluation, hyperparameter tuning, and model interpretability
- Proven experience leading end-to-end AI solution development from concept through deployment in production environments
- Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow) for model tracking, deployment, and lifecycle management
- Proficiency with cloud platforms (GCP, Azure, or AWS), including their AI/ML services and infrastructure
- Hands-on experience with API development, containerization, and orchestration using tools such as Flask/FastAPI, Docker, and Kubernetes
- Applied knowledge of NLP, computer vision, or deep learning techniques is a strong advantage
- Good foundation in mathematics, statistics, and data mining techniques
- Demonstrated ability to lead cross-functional initiatives, manage priorities, and communicate effectively with diverse stakeholders
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field (Master’s preferred)
Benefits
- Medical/prescription drug coverage
- Dental coverage
- Vision coverage
- Flexible Spending Account
- Health Savings Account
- Dependent Care Flexible Spending Account
- Basic and Supplemental Life Insurance & Accidental Death and Dismemberment
- Disability Income Protection Plan
- Employee Assistance Program
- 401(k) retirement program
- Vacation
- Paid Holidays and Personal time
- Paid Sick and Family and Medical Leave time as required by law
- Discounted Employee Stock Purchase Program
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