AI Engineer
1 week ago
Responsibilities:
- Support the design and development of data pipelines for AI and machine learning workflows.
- Assist in building, training, testing, and evaluating ML models in collaboration with senior engineers.
- Work with large structured and unstructured datasets, ensuring data quality and readiness.
- Prepare training datasets and implement data preprocessing/feature engineering techniques.
- Participate in deploying and monitoring ML models in production environments.
- Learn and apply MLOps best practices such as model versioning, CI/CD for ML, and automation workflows.
- Research and experiment with new AI/ML technologies, LLMs, and emerging tools.
Qualifications:
- Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, or related fields. (Fresh Graduates are strongly encouraged to apply)
- Basic understanding of machine learning concepts, model training, and data preprocessing.
- Programming skills in Python and familiarity with ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch).
- Basic understanding of data engineering concepts: SQL, ETL, data modeling.
- Strong analytical thinking, problem-solving skills, and willingness to learn.
- Internship or project experience in AI/ML, data engineering, or related fields.
- Familiarity with cloud platforms (AWS, GCP, Azure).
- Knowledge of big data tools (Spark, Hadoop) or workflow tools (Airflow, Prefect).
- Experience with Git, APIs, Docker, or basic DevOps concepts.
- Interest in LLMs, generative AI, vector databases, or modern AI stacks.
- Excellent in English.
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