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PDS Inc, LLC
http://www.pdsinc.com
http://www.pdsinc.com
true
ML Modeling Engineer
Posted: 03/11/2025
2025-03-11
2025-04-23
Employment Type:
Direct Hire
Job Category: Software Engineer
Job Number: 24472
Workplace Type: Hybrid
Job Description
About the Role
We are seeking a skilled ML Modeling Engineer to design, develop, and optimize machine learning models that power our products and services. You will work closely with data scientists, software engineers, and product teams to build robust, scalable, and high-performance ML solutions.
Key Responsibilities
? Required:
? Preferred:
Compensation: $220k
We look forward to reviewing your application. We encourage everyone to apply - even if every box isn’t checked for what you are looking for or what is required.
PDSINC, LLC is an Equal Opportunity Employer.
We are seeking a skilled ML Modeling Engineer to design, develop, and optimize machine learning models that power our products and services. You will work closely with data scientists, software engineers, and product teams to build robust, scalable, and high-performance ML solutions.
Key Responsibilities
- Research, develop, and implement machine learning models for various business applications.
- Fine-tune models for accuracy, efficiency, and scalability.
- Perform data preprocessing, feature engineering, and model evaluation.
- Optimize models for deployment in real-world environments (latency, memory, inference speed).
- Experiment with hyperparameter tuning, model ensembling, and transfer learning.
- Stay up to date with state-of-the-art ML research and incorporate new techniques when applicable.
- Collaborate with ML Infrastructure Engineers to ensure seamless model deployment and monitoring.
- Write clean, efficient, and well-documented code.
? Required:
- Strong background in machine learning and deep learning (CNNs, RNNs, Transformers, etc.).
- Proficiency in ML frameworks (TensorFlow, PyTorch, JAX).
- Experience with classical ML algorithms (XGBoost, LightGBM, scikit-learn).
- Solid understanding of statistics, probability, and optimization techniques.
- Experience with model evaluation, interpretability, and performance optimization.
- Familiarity with cloud platforms (AWS, GCP, Azure) and ML pipeline tools.
? Preferred:
- Experience in large-scale distributed trainingÂ
- Knowledge of model compression techniques (quantization, pruning, distillation).
- Familiarity with experiment tracking tools (Weights & Biases, MLflow).
- Exposure to MLOps and model deployment in production environments.
Compensation: $220k
We look forward to reviewing your application. We encourage everyone to apply - even if every box isn’t checked for what you are looking for or what is required.
PDSINC, LLC is an Equal Opportunity Employer.
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