AI Engineer Associate

Collaborate with data scientists, machine learning engineers, and DevOps teams to create robust, scalable, and reliable AI pipelines.
Develop and maintain automated processes for model training, deployment, and inference, ensuring best practices for model versioning, monitoring, and scaling.
Gathering and preparing large datasets for training and testing machine learning models including data cleaning, pre-processing, feature engineering and data quality.
Implement infrastructure as code (IaC) templates to create reproducible AI development environments.
Integrate AI pipelines into continuous integration and continuous deployment (CI/CD) workflows.
Ensure seamless and secure deployment of AI models into production environments.
Implement monitoring solutions to track model performance, detect data drift, and maintain data quality.
Implement deep learning algorithms and neural networks for tasks such as image recognition, natural language processing (NLP), and speech recognition.
Troubleshoot and optimize AI pipelines for efficiency, reliability, and compliance.
Build and maintain infrastructure to support AI development initiatives.
Implement robust security controls for AI systems to ensure compliance with industry standards (e.g., GDPR, HIPAA) based on Design document.

A relevant Bachelors or higher-education degree in Computer Science, Data Science, or related fields.
1-3 years of experience in AI operations, machine learning, or DevOps.
Preferred certifications in AI, machine learning, and cloud platforms (e.g., AWS, Azure, GCP).
Proficiency in Python, SQL, and relevant AI libraries (e.g., TensorFlow, PyTorch).
Familiarity with cloud platforms (e.g., GCP, AWS) and containerization (Docker, Kubernetes).
Strong problem-solving and critical thinking abilities.
Expertise in designing, implementing, and optimizing end-to-end AI pipelines.
Ability to work collaboratively in a cross-functional team environment.
Strong communications skills.

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