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1 Exponential Machine Job
Senior Machine Learning Engineer
Exponential Machine
posted 2d ago
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Job Description
We are looking for an experienced Machine Learning Engineer to join our team. The ideal candidate will have a strong foundation in algorithm design, complexity analysis, and hands-on experience in developing machine learning models from scratch. The role will involve building scalable and efficient ML systems, optimizing models, and integrating them into products. This individual should also be passionate about staying updated with new technologies and trends in the ML and AI space.
- Enjoy programming and be comfortable with Object Oriented Programming in Python
- Eager to quickly learn new concepts, languages, tools and technologies as required
- Enjoy building products that are generic and can cater to multiple tenants, through appropriate parameterization/abstraction
- Be excited to work in a startup environment and take end-to-end responsibilities working with the co-team members
- Write clean, maintainable, and well-tested code
- Engage in the full development life-cycle including architectural design and testing
- Solid understanding of distributed systems Microservices/Reactive architecture, event driven systems, NoS L databases, queues, caching, docker containers, etc.
- Machine Learning and Algorithms:
- Strong experience in designing, implementing, and optimizing machine learning algorithms.
- Deep understanding of algorithms like Gradient Boosting, Random Forests, SVM, and clustering techniques.
- Proficiency in Python with a focus on ML frameworks such as TensorFlow, Keras, PyTorch, and Scikit-learn.
- Familiarity with distributed computing and parallel processing for large-scale machine learning tasks.
- Understanding of deep learning architectures (e.g., CNNs, RNNs, GANs, etc.) and ability to implement them for real-world applications.
- Experience in working with large datasets and tools for data preprocessing, feature engineering, and model training.
- Familiarity with big data tools like Spark and distributed ML libraries such as Spark-MLlib.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud for managing ML workloads and deployments.
- Strong familiarity with Git-based version control and CI/CD practices for continuous integration of models.
- Excellent problem-solving skills and ability to analyze complex datasets to extract valuable insights.
- Strong communication and collaboration skills to work with cross-functional teams.
- Education: Bachelor s degree in Computer Science, Engineering, Mathematics, or a related field.
- Certifications: ML/AI-related certifications, such as from AWS, Google Cloud, or Azure, will be a plus.
- Experience with machine learning libraries like TensorFlow, Keras, PyTorch, and Spark- MLlib.
- Familiarity with cloud services (AWS, GCP, Azure) for deploying ML models at scale.
- Experience in implementing end-to-end machine learning pipelines.
Employment Type: Full Time, Permanent
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