Machine Learning Engineer – W2

Job Description

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About the opening:

We are looking for a skilled Machine Learning Engineer to design, develop, and deploy machine learning models that solve real-world problems. You will collaborate with data scientists, engineers, and business stakeholders to implement scalable AI/ML solutions.

Key Responsibilities:

* Design and develop machine learning models and algorithms for various use cases.
* Preprocess, clean, and analyze large datasets to extract meaningful insights.
* Train, tune, and optimize models for performance, accuracy, and scalability.
* Deploy machine learning models into production environments using MLOps best practices.
* Develop APIs or integrate models into applications for real-time or batch inference.
* Monitor model performance and retrain/update models as necessary.
* Work closely with software engineers, data scientists, and business teams to understand requirements and deliver AI-driven solutions.
* Stay updated with the latest ML research, tools, and techniques to improve existing models and processes.
Required Skills & Qualifications:

* Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
* Strong experience with Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
* Hands-on experience with data preprocessing, feature engineering, and model development.
* Proficiency in SQL and NoSQL databases for data storage and retrieval.
* Experience with cloud platforms like AWS, Azure, or GCP for deploying models.
* Knowledge of containerization tools like Docker, Kubernetes.
* Familiarity with MLOps practices, CI/CD pipelines, and model monitoring tools.
* Strong problem-solving skills and the ability to work in a collaborative environment.
Preferred Qualifications:

* Experience with NLP, computer vision, or deep learning.
* Knowledge of big data technologies like Spark, Hadoop.
* Experience working with AutoML and model interpretability techniques.