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Artificial Intelligence Engineer

4 years

0 Lacs

Posted:21 hours ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Job Title: AI/ML Engineer Experience: 4+ Years Location: Remote Job Type: Full-Time Job Summary: We are looking for a passionate and results-driven AI/ML Engineer with 4 years of experience in designing, building, and deploying machine learning models and intelligent systems. The ideal candidate should have solid programming skills, a strong grasp of data preprocessing, model evaluation, and MLOps practices. You will collaborate with cross-functional teams including data scientists, software engineers, and product managers to integrate intelligent features into applications and systems. Key Responsibilities: Design, develop, train, and optimize machine learning and deep learning models for real-world applications. Preprocess, clean, and transform structured and unstructured data for model training and evaluation. Implement, test, and deploy models using APIs or microservices (Flask, FastAPI, etc.) in production environments. Use ML libraries and frameworks like Scikit-learn, TensorFlow, PyTorch, Hugging Face, XGBoost, etc. Monitor and retrain models as needed for performance, accuracy, and drift mitigation. Collaborate with software and data engineering teams to operationalize ML solutions using MLOps tools. Stay updated with emerging trends in AI/ML and suggest enhancements to existing systems. Required Skills and Qualifications: Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, Data Science, or related field. 4+ years of hands-on experience in machine learning model development and deployment. Strong experience in Python and libraries like Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in model deployment using Flask, FastAPI, Docker, and REST APIs. Experience with version control (Git), model versioning, and experiment tracking (MLflow, Weights & Biases). Familiarity with cloud platforms like AWS (SageMaker), Azure ML, or GCP AI Platform. Knowledge of databases (SQL/NoSQL) and data pipelines (Airflow, Spark, etc.). Strong problem-solving and debugging skills, with an analytical mindset.

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