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6 days ago
We are seeking a highly skilled Machine Learning Engineer to design, develop, and deploy ML models that drive business growth.
Key Responsibilities:
- Design and implement ML models for business applications using regression, classification, clustering, and deep learning techniques.
- Build and optimize data pipelines, feature engineering, and training workflows to enhance model performance.
- Deploy models to production using containerization and orchestration tools like Docker and Kubernetes, as well as cloud platforms (AWS/GCP/Azure).
- Monitor model performance, retrain, and maintain production-ready systems.
- Develop APIs and integrate ML solutions with enterprise applications to drive business value.
- Stay updated on ML/AI trends and contribute innovative solutions to drive business growth.
- Collaborate with data scientists, engineers, and product managers to align with business goals and objectives.
Qualifications:
- 3+ years of experience in ML engineering or a related field.
- Strong proficiency in Python; knowledge of Java/Scala/R is a plus.
- Expertise with popular ML libraries/frameworks such as scikit-learn, TensorFlow, PyTorch, and Keras.
- Hands-on experience with data tools like Pandas, NumPy, and Spark.
- Experience with ML deployment on cloud platforms (SageMaker, Azure ML, GCP AI, TensorFlow Serving, TorchServe).
- Familiarity with databases (SQL, MongoDB, Cassandra) and version control (Git).
- Understanding of DevOps/MLOps practices to ensure smooth model deployment and maintenance.
- Excellent problem-solving, communication, and collaboration skills to work effectively with cross-functional teams.
This role requires a strong foundation in machine learning concepts, as well as excellent problem-solving and communication skills. If you are passionate about developing innovative ML solutions and driving business growth, we encourage you to apply.
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