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# Senior Associate Data Science/Machine Learning - Chicago - Hybrid

- **Company:** Sapient Corporation
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $117,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Data Cleansing, Information Engineering, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Google Cloud, Cloud Platform System, Feature Engineering, Pytorch, Model Validation, Containerization, AI Platforms, Kubernetes, Data Analytics, Machine Learning Operations, Data Pipelines, Docker
- **Published:** September 10, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88285240/1

## About the Role

* 5+ years of experience in machine learning, data science, or AI engineering.
 * Strong expertise in ML model development, deployment, and optimization.
 * Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.
 * Experience with MLOps, CI/CD pipelines, and model monitoring.
 * Hands-on experience with cloud-based ML platforms (AWS SageMaker, GCP AI Platform, Azure ML).
 * Strong understanding of data engineering, data pipelines, and big data technologies.
 * Excellent problem-solving and analytical skills.

Set Yourself Apart With

 * Experience in building and deploying large-scale AI/ML systems.
 * Knowledge of Kubernetes, Docker, and other containerization technologies.
 * Expertise in time-series forecasting, NLP, or computer vision.
 * Certifications in ML engineering, MLOps, or cloud platforms.

## Description

As a Senior Associate Data Scientist, you will be responsible for developing and deploying machine learning models at scale. You will work closely with cross-functional teams to design, implement, and optimize data-driven solutions that drive business impact. Your expertise in ML engineering will be crucial in building robust, scalable, and efficient AI systems.
Your Impact

 * Design, develop, and deploy machine learning models to solve complex business problems.
 * Collaborate with data engineers, product managers, and business stakeholders to implement end-to-end ML solutions.
 * Optimize and scale machine learning pipelines for performance and efficiency.
 * Ensure the reliability, scalability, and maintainability of AI/ML systems in production.
 * Utilize cloud-based platforms (AWS, GCP, Azure) for model training, deployment, and monitoring.
 * Implement best practices in data preprocessing, feature engineering, and model evaluation.
 * Stay updated with the latest advancements in ML engineering and AI technologies.


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