Senior Specialist - Data Sciences

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 productionready 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 ProductDelivery Security Privacy Store Operations Merchandising and other crossfunctional partners to implement practical AI solutions The role must balance model quality latency cost privacy maintainability and operational usefulness 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 productionquality 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 finetuning 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 acceptableuse 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 APIapplication 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 privacyaware 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

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 5 years of experience in software engineering machine learning engineering applied AI engineering or production ML systems 3 years of handson experience building training finetuning or deploying machine learning models in applied business environments Strong proficiency in Python and modern machine learning frameworks such as PyTorch TensorFlow scikitlearn 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 productionquality APIs services or batchstreaming 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 eventdriven architectures REST APIs message queues data lakes and metadataevent pipelines preferred Experience with distributed inference realtime AI systems highthroughput 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, Mandatory Skills : Machine Learning - AIOPS, Python - Data Science

LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI - enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM - a Larsen & Toubro company - owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it. Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for