Machine Learning Engineer
1 week ago
Job Title: Machine Learning Engineer
Experience: 5 to 8 Years
Notice: Immediate or 15 days only
Job Description:
Key Responsibilities:
- Design, develop, and deploy machine learning models for real-world applications.
- Implement and optimize end-to-end ML pipelines using PySpark and MLflow.
- Work with structured and unstructured data using Pandas, NumPy, and other data processing libraries.
- Train and fine-tune models using scikit-learn, TensorFlow, or PyTorch.
- Integrate and experiment with Large Language Models (LLMs) such as OpenAI GPT, Hugging Face Transformers, etc.
- Collaborate with cross-functional teams including data engineers, product managers, and software developers.
- Monitor model performance and continuously improve model accuracy and reliability.
- Maintain proper versioning and reproducibility of ML experiments using MLflow.
Required Skills:
- Strong programming experience in Python.
- Solid understanding of machine learning algorithms, model development, and evaluation techniques.
- Experience with PySpark for large-scale data processing.
- Proficient with MLflow for tracking experiments and model lifecycle management.
- Hands-on experience with Pandas, NumPy, and Scikit-learn.
- Familiarity or hands-on experience with LLMs (e.g., OpenAI, Hugging Face Transformers). Understanding of MLOps principles and deployment best practices.
Preferred Qualifications:
- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or a related field.
- Experience in cloud ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) is a plus.
- Strong analytical and problem-solving abilities.
- Excellent communication and teamwork skills.
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