Lead Engineer AIML Onsite

We are seeking a Machine Learning Engineer to join the Information Technology organization at our corporate office in Springfield MO.

The Machine Learning Engineer designs builds tests and optimizes machine learning systems that support enterprise AI initiatives across the business. This role is responsible for developing production-ready model code inference logic and reusable ML components that convert approved enterprise data into reliable operational signals recommendations automations or insights.

This position works closely with AI leadership Data Science MLOps Data Engineering Product/Delivery Security Privacy Store Operations Merchandising and other cross-functional partners to implement practical AI solutions. The role must balance model quality latency cost privacy maintainability and operational usefulness.

This position requires working onsite in our Springfield MO headquarters. Occasional travel to field locations may be required.

ESSENTIAL FUNCTIONS:

• Design develop and evaluate machine learning models and inference pipelines for enterprise AI use cases across retail operations merchandising customer experience supply chain and corporate functions.
• Build production-quality Python code for model training evaluation preprocessing postprocessing inference services and reusable model components.
• Partner with Data Scientists to define ground truth datasets labeling requirements evaluation metrics confidence thresholds and acceptable error tradeoffs.
• Partner with MLOps / Cloud ML Engineering to package register deploy monitor and optimize models in cloud edge or hybrid environments.
• Evaluate and select model architectures pretrained models fine-tuning approaches and inference strategies appropriate for the business problem and operating environment.
• Prepare and transform approved structured and unstructured data for model development while following privacy retention and acceptable-use constraints.
• Build or integrate data labeling sampling augmentation and validation workflows needed for model development and evaluation.
• Optimize inference performance for latency cost throughput reliability and deployment target.
• Implement model output schemas and event metadata structures in partnership with Data Engineering and API/application teams.
• Integrate model outputs with APIs event streams dashboards reports applications or other approved enterprise presentation layers.
• Write automated tests for model code preprocessing logic inference services schema contracts and regression checks.
• Troubleshoot model failures caused by data quality domain shift operational changes drift or degraded source data.
• Document model assumptions limitations dependencies reproducibility steps evaluation results and production readiness criteria.
• Support responsible AI practices including PII minimization privacy-aware design model explainability where practical and secure handling of approved enterprise data.
• Contribute to architecture decision records model cards technical runbooks documentation and reusable engineering standards.
• ALL OTHER DUTIES AS ASSIGNED.

EXPERIENCE/QUALIFICATIONS:

Minimum Degree Required: Bachelors Degree in Computer Science Artificial Intelligence Machine Learning Data Science Electrical Engineering Computer Engineering Applied Mathematics or a related technical field or equivalent experience.

• 8 years of experience in software engineering machine learning engineering applied AI engineering or production ML systems.
• 5 years of hands-on experience building training fine-tuning or deploying machine learning models in applied business environments.
• Strong proficiency in Python and modern machine learning frameworks such as PyTorch TensorFlow scikit-learn OpenCV or equivalent tools.
• Experience with one or more ML domains such as natural language processing forecasting classification recommendation systems optimization anomaly detection multimodal AI or generative AI.
• Experience building production-quality APIs services or batch/streaming inference components.
• Experience with Git automated testing code review containerization and collaborative engineering practices.
• Familiarity with model optimization and deployment formats or tooling such as ONNX TensorRT OpenVINO quantization batching or similar techniques preferred.
• Familiarity with Azure Machine Learning Azure AI services Databricks MLflow or equivalent cloud ML platforms preferred.
• Familiarity with event-driven architectures REST APIs message queues data lakes and metadata/event pipelines preferred.
• Experience with distributed inference real-time AI systems high-throughput event processing or enterprise integration patterns preferred.
• Experience working with security privacy and governance requirements for sensitive operational data preferred.

KNOWLEDGE SKILLS AND ABILITY:

• Strong software engineering fundamentals and ability to build maintainable ML systems beyond notebooks.
• Strong understanding of the machine learning lifecycle including data preparation training evaluation deployment monitoring and retraining.
• Strong understanding of model failure modes in real-world environments.
• Ability to make practical model tradeoffs across accuracy latency cost privacy reliability and maintainability.
• Ability to translate business use cases into technical model requirements without over-scoping the solution.
• Ability to collaborate effectively with Data Scientists MLOps Engineers Data Engineers platform teams and business stakeholders.
• Ability to document model behavior and limitations clearly for both technical and nontechnical audiences.
• Proficiency with Git-based development workflows and Agile delivery practices.
• Commitment to responsible and ethical AI development aligned with company standards.

TRAVEL REQUIREMENTS:

Occasional travel up to 10% may be required for field observation technical validation troubleshooting or stakeholder workshops.

PHYSICAL REQUIREMENTS:

Regularly completes computer work and sits.

Occasionally walks and stands.

Seldomly or never lifts up to 50lbs.

INDEPENDENT JUDGEMENT:

Performs duties within scope of general company policies procedures and objectives. Analyzes problems and performs needs assessments. Uses judgment in adapting broad guidelines to achieve desired result. Regular exercise of independent judgment within accepted practices. Makes recommendations that affect policies procedures and practices.

Full Time Benefits Summary:
Enjoy discounts on retail merchandise our restaurants world-class resorts and conservation attractions!

• Medical
• Dental
• Vision
• Health Savings Account
• Flexible Spending Account
• Voluntary benefits
• 401k Retirement Savings
• Paid holidays
• Paid vacation
• Paid sick time
• Bass Pro Cares Fund
• And more!

Bass Pro Shops is an equal opportunity employer. Hiring decisions are administered without regard to race color creed religion sex pregnancy sexual orientation gender identity age national origin ancestry citizenship status disability veteran status genetic information or any other basis protected by applicable federal state or local law.

Reasonable Accommodations

Qualified individuals with known disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws.
If you need a reasonable accommodation for any part of the application process please visit your nearest location or contact us at