Job description
- Developing, training, and deploying machine learning models to solve real-world problems.
- Designing and implementing scalable AI/ML pipelines, from data preprocessing to model deployment.
- Collaborating with data engineers and backend teams to integrate models into production systems.
- Optimizing algorithms and models for performance, accuracy, and efficiency.
- Conducting exploratory data analysis to uncover insights and inform model development.
- Staying abreast of the latest AI/ML advancements and apply them to enhance project outcomes.
- Troubleshooting and refining models with minimal guidance, ensuring robustness and reliability.
Job Requirements/ Skills:
- 3-5 years of experience in AI/ML development, with a focus on practical applications.
- Strong proficiency in Python and libraries such as TensorFlow, PyTorch, scikit-learn, or Keras.
- Experience with data manipulation tools (e.g., Pandas, NumPy) and working with large datasets.
- Knowledge of supervised and unsupervised learning techniques, NLP, or computer vision (depending on project needs).
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for model training and deployment.
- Ability to work independently, prioritize tasks, and deliver high-quality results with minimal oversight.
- Solid understanding of software engineering principles and version control (e.g., Git).
- Excellent analytical skills and a strong foundation in statistics and mathematics.
Preferred Qualifications:
- Experience with MLOps tools (e.g., MLflow, Kubeflow) or containerization (e.g., Docker).
- Familiarity with big data frameworks like Spark or Hadoop.
- Prior work in deploying AI models in production environments or real-time systems.
- Exposure to Agile methodologies or cross-functional team settings.
