
ML Engineer
5 days ago
ML Engineer
Experience: 6-8 years
Work Mode: Remote
NOTE: Must Have: DevOps tools, Python and Excellent Communication
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:
- Bachelor's or master's 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.
Job Types: Full-time, Permanent
Pay: ₹2,000, ₹2,600,000.00 per year
Experience:
- DevOps: 5 years (Required)
- Python: 5 years (Required)
- MLOps: 5 years (Required)
Work Location: Remote
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