Design, develop, deploy, and maintain enterprise-scale ML models and end-to-end ML pipelines. Perform data preparation, feature engineering, model training, evaluation, and optimization. Deploy and monitor ML models in production, including model drift detection and automated retraining.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
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Job Title: Machine Learning Engineer
Location: Cincinnati, OH (Onsite)
Duration: Long Term
Job Summary
We are seeking a Machine Learning Engineer with years of experience in designing, building, and deploying enterprise-scale Machine Learning solutions. The ideal candidate will have deep expertise in Python, TensorFlow/PyTorch, MLOps, Cloud Platforms (AWS/Azure/GCP), Docker, and Kubernetes, along with experience in architecting scalable ML pipelines and production AI systems.
Top 3 Required Skills
- Python & Machine Learning
- TensorFlow / PyTorch
- MLOps with AWS/Azure/GCP
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Required Skills
- Python (NumPy, Pandas, Scikit-learn)
- Machine Learning
- TensorFlow
- PyTorch
- MLOps
- AWS / Azure / GCP
- ML Pipelines
- Model Deployment & Monitoring
- CI/CD
- Git / Version Control
- Feature Engineering
- Model Evaluation & Optimization
- ML System Design
- Performance Tuning
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Preferred Skills
- MLflow
- Amazon SageMaker
- Azure Machine Learning
- Docker
- Kubernetes
- Apache Spark
- Ray
- Large Language Models (LLMs)
- Deep Learning
- Transformers
- Vector Databases
- ML Governance
- Technical Leadership / Mentoring
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Key Responsibilities
- Design, develop, deploy, and maintain enterprise-scale ML models and end-to-end ML pipelines.
- Perform data preparation, feature engineering, model training, evaluation, and optimization.
- Deploy and monitor ML models in production, including model drift detection and automated retraining.
- Build scalable ML systems using AWS, Azure, or GCP.
- Drive MLOps initiatives, CI/CD automation, governance, and model lifecycle management.
- Collaborate with Data Engineering, DevOps, and business stakeholders.
- Mentor engineers and provide technical leadership on AI/ML initiatives.
- Evaluate and adopt emerging AI/ML technologies and best practices.
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