Sr AI/ML Engineer
Indexed description
Southern Glazer’s is proud of its well-earned positive reputation, continually achieving accolades for our outstanding workplace culture. We take pride in creating a culture where our people are valued, supported, and provided opportunities for growth and belonging.
As a full-time employee, you can choose from a wide-ranging menu of our Top Shelf Benefits, including comprehensive medical and prescription drug coverage, dental and vision plans, tax-saving Flexible Spending Accounts, disability coverage, life insurance plans, and a 401(k) plan. We also offer tuition assistance, a wellness program, parental leave, vacation accrual, paid sick leave, and more.
By joining Southern Glazer’s, you would be part of a team that values excellence, innovation, and community. This is more than just a job – it's an opportunity to build the future of beverage distribution and grow with a company that truly cares about its people.
Overview
The Senior AI/ML Engineer plays a role in AI and machine learning projects at Southern Glazer's Wine and Spirits (SGWS). This position is responsible for designing, building, and deploying moderate to advanced machine learning models and AI systems to transform data into actionable insights. The role involves developing and supporting moderately complex systems with system-wide impact and integrating them across SGWS. The Senior AI/ML Engineer ensures that models developed by data scientists are scalable and seamlessly integrated into production environments, where they are monitored for data and infrastructure drift. Collaboration with Data Scientists, Software Developers, Engineers, and Domain Architects is essential for gathering requirements and integrating AI solutions into existing systems, creating a cohesive technological ecosystem. The role also requires contributing to engineering communities within SGWS and influencing the technical aspects of services, products, or platforms.
Primary Responsibilities
- Gather and clean data from a variety of SGWS sources.
- Conduct exploratory data analysis and collaborates on efforts to design and implement data collection strategies.
- Participate in the development of robust data pipelines with Data Analytics Engineers.
- Conduct feature selection and engineering in order to improve model performance.
- Propose and assist the implementation of scalable training processes for large and complex datasets.
- Design and implement machine learning models while experimenting with different model architecture and hyperparameters.
- Implement evaluation frameworks and metrics to assess model performance.
- Train and execute models on large datasets using computational resources.
- Evaluate model performance for accuracy, precision, recall, F1-score.
- Perform cross-validation and tuning to models to avoid overfitting and and/or underfitting.
- Deploy machine learning models into production environments and ensure models are scalable and able to handle real-time data processing.
- Support efforts to diagnose and resolve complex issues related to model performance.
- Integrate AI solutions with existing software and workflows.
- Monitor model performance and accuracy over time and update modes with new data when available and as requirements change.
- Debug and troubleshoot issues with model performance and/or deployment.
- Stay updated with the latest AI and ML technologies, methodologies and practices.
- Ensure AI models adhere to ethical guidelines and regulatory standards and address issues related to bias, fairness and transparency in AI systems.
- Bachelor’s or Master’s degree in related field (e.g., Computer Science, Statistics, Engineering, etc.) or equivalent combination of education and work experience
- Typically, 5 – 7+ years of experience in a relevant role (e.g., AI/ML engineering, data science, artificial intelligence, business intelligence, etc.)
- Proven experience in developing, deploying, and implementing ML models and algorithms to a production environment
- Native-level proficiency/fluent in English
- Experience in DevOps and Agile technology environments
- Physical demands include a considerable amount of time sitting and typing/keyboarding, using a computer (e.g., keyboard, mouse, and monitor), or adding machine
- Physical demands with activity or condition may include walking, bending, reaching, standing, squatting, and stooping
- May require occasional lifting/lowering, pushing, carrying, or pulling up to 20lbs
If you have any questions or concerns about whether this posting complies/adheres with local pay transparency requirements, please contact the SGWS talent acquisition team at [email protected]
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