Machine Learning Engineer
2 weeks ago
Roles and responsibilities :
- Collaborate with cross-functional teams such as Product Partners and Partner Team
- Developers to identify opportunities for process improvements that can be solved using machine learning and generative AI.
- Design, develop, and deploy machine learning models and algorithms for various business applications.
- Work on data preprocessing, feature engineering, model selection, and performance evaluation.
- Optimize and scale machine learning models for production, ensuring high performance, accuracy and low latency.
- Monitor and maintain machine learning pipelines, ensuring continuous improvement of deployed models.
- Contribute to the development of APIs and integration of machine learning models with production systems.
- Stay up-to-date with the latest machine learning research, tools, and techniques to continually enhance your skill set and improve solutions.
- Lead junior ML Engineers and guide them. Coordinate for product release and spread adoption among user communities
- Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs.
- Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough and precise monitoring.
Experience and qualifications :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 4+ hands-on experience in machine learning and data science in a production environment.
- Strong proficiency in ML frameworks (e.g. Tensorflow, Pytorch, Scikit-learn, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java
- Experience with large language models (LLMs), Prompt Engineering Techniques, Langchain, OpenAI SDK, RAG system, Vector DB's (Mandatory).
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