Artificial Intelligence Engineer

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as an AI Engineer, Machine Learning Engineer, Applied AI Engineer, or similar role.
• Strong experience training, fine-tuning, and deploying machine learning models to production.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
• Experience operating and maintaining production ML systems.
• Hands-on experience with AWS, GCP, or Azure cloud platforms.
• Familiarity with cloud ML services such as SageMaker, Vertex AI, or similar platforms.
• Strong understanding of API design and distributed system architecture.
• Experience implementing MLOps practices, CI/CD pipelines, and model monitoring.
• Experience with Docker and Kubernetes.
• Knowledge of PostgreSQL and modern data infrastructure.
• Experience with LLMs, RAG systems, and vector databases is a strong plus.
• Excellent written and verbal communication skills in English.

Responsibilities

• Own end-to-end delivery of production AI and ML systems from experimentation to deployment.
• Train, fine-tune, and optimize machine learning models, including LLMs and open-weight models.
• Build and maintain training, data processing, and inference pipelines.
• Improve model performance across accuracy, latency, reliability, and cost.
• Implement MLOps best practices for deployment, monitoring, CI/CD, and automated retraining.
• Develop evaluation frameworks, benchmark datasets, and quality checks for production models.
• Design and maintain scalable APIs and services that expose AI capabilities.
• Collaborate with Product, Backend, and Frontend teams to integrate AI into customer-facing workflows.
• Monitor production systems and continuously improve model and infrastructure performance.
• Research and evaluate emerging AI techniques, tools, and frameworks.

Job Details

Location: Remote

Interview Process

• Recruiter Screening
• Hiring Manager Discussion
• Applied AI Technical Assessment
• Founder Round
• Final HR Discussion