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4 days ago
Our ideal candidate will have a strong background in building and deploying ML models, hands-on product development experience, and a solid grasp of ML Ops practices.
Job Description- Develop machine learning models and algorithms tailored to real-world business problems.
- Collaborate with cross-functional teams to integrate ML models into existing systems and products.
- Conduct experiments, perform hyperparameter tuning, and evaluate models to improve performance.
- Implement best practices in ML Ops, including versioning, CI/CD, testing, and automated model monitoring.
- Lead or mentor junior team members and contribute to overall AI/ML strategy.
Requirements and Qualifications
- 5+ years of experience in machine learning engineering or a related field.
- Proven experience developing and deploying ML-powered products; having a demo or portfolio is a plus.
- Proficiency in programming languages such as Python (preferred), R, or Java.
- Strong understanding of ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Solid experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
- Working knowledge of cloud ML platforms such as AWS SageMaker, GCP AI Platform, or Azure ML.
- Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
- Experience with data processing and big data technologies like Hadoop and Spark.
- Strong understanding of MLOps tools and practices for monitoring, deployment, and lifecycle management.
Desired Skills and Qualifications
- Experience with deep learning architectures including CNNs, RNNs, and GANs.
- Knowledge of natural language processing (NLP) or computer vision.
- Experience with Docker, Kubernetes, or other containerization and orchestration tools.
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
- Demonstrated leadership experience or project ownership in past roles.
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