AI/ML Engineer

DataE2E Technologies

5 years

0 Lacs

India

Posted:1 day ago| Platform:

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Skills Required

ai ml design cutting data software learning regression preprocessing engineering model evaluation metrics aws azure gcp documentation research development python tensorflow pytorch numpy algorithms mlflow containerization docker git sagemaker vertex

Work Mode

Remote

Job Type

Full Time

Job Description

Job Title: AI/ML Engineer

Location: 100% Remote

Job Type: Full-Time

About the Role:

We are seeking a highly skilled and motivated AI/ML Engineer to design, develop, and deploy cutting-edge ML models and data-driven solutions. You will work closely with data scientists, software engineers, and product teams to bring AI-powered products to life and scale them effectively.

Key Responsibilities:

Design, build, and optimize machine learning models for classification, regression, recommendation, and NLP tasks.
Collaborate with data scientists to transform prototypes into scalable, production-ready models.
Deploy, monitor, and maintain ML pipelines in production environments.
Perform data preprocessing, feature engineering, and selection from structured and unstructured data.
Implement model performance evaluation metrics and improve accuracy through iterative tuning.
Work with cloud platforms (AWS, Azure, GCP) and MLOps tools to manage model lifecycle.
Maintain clear documentation and collaborate cross-functionally across teams.
Stay updated with the latest ML/AI research and technologies to continuously enhance our solutions.

Required Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
2–5 years of experience in ML model development and deployment.
Proficient in Python and libraries such as scikit-learn, TensorFlow, PyTorch, pandas, NumPy, etc.
Strong understanding of machine learning algorithms, statistical modeling, and data analysis.
Experience with building and maintaining ML pipelines using tools like MLflow, Kubeflow, or Airflow.
Familiarity with containerization (Docker), version control (Git), and CI/CD for ML models.
Experience with cloud services such as AWS SageMaker, GCP Vertex AI, or Azure ML.

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