Machine Learning Engineer
3 weeks ago
Job Duties
- Develop and deploy machine learning models for traditional ML, NLP, and Generative AI solutions.
- Design, build, and maintain MLOps pipelines for seamless model deployment and continuous updates.
- Collaborate with stakeholders to gather requirements and translate them into technical solutions.
- Create scalable data pipelines for data collection, cleaning, and feature engineering.
- Implement best practices for code quality, version control, testing, and documentation.
- Conduct A/B testing and automated tests to validate model performance and reliability.
- Participate in code reviews and provide mentorship on machine learning practices.
- Monitor and optimize model performance in production environments.
- Stay updated on industry trends to continuously improve and innovate solutions.
- Bachelor's or Master's degree in computer science, Data Science, or a related field.
- Extensive experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn, including model training, tuning, and deployment.
- Experience in building Retrieval-Augmented Generation (RAG) applications, leveraging LLMs to augment search and retrieval tasks.
- Proficiency in big data technologies, specifically distributed computing frameworks such as PySpark, for handling large-scale data processing and analysis.
- Hands-on experience with natural language processing (NLP) libraries like NLTK, SpaCy, and Hugging Face's Transformers, and familiarity with Large Language Models (LLMs) and their applications.
- Experience with SQL and NoSQL databases, with strong skills in database design, query optimization, and data retrieval.
- Strong experience with cloud platforms, preferably Microsoft Azure, including Azure Machine Learning, Azure Databricks, and Azure DevOps for CI/CD pipeline automation.
- Proven expertise in Python programming, with experience in Django or Flask for designing and implementing RESTful APIs to deploy and integrate models.
- Solid understanding of MLOps practices, including model lifecycle management, deployment, monitoring, and continuous integration.
- Strong problem-solving abilities and the ability to work independently, manage complex projects, and deliver results in fast-paced environments.
Equivalent experience and skills are welcome. We encourage all qualified candidates to apply
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