Fullstack AI Engineer

Position Overview

We are seeking a highly skilled Full Stack AI Engineer to join our team. The ideal candidate has strong expertise in AI/ML model development, deployment, and integration with scalable applications. You will work across the stack from model training and optimization to building APIs, web services, and front-end components to deliver AI solutions in production.

Key ResponsibilitiesAI/ML Development

Design, build, train, and fine-tune AI/ML models (using frameworks like TensorFlow, PyTorch, or Scikit-learn).

Design build application that leverage LLMs, VLMs, ComputerVision, ....

Optimize models for performance, scalability, and cost efficiency.

Implement MLOps best practices for continuous integration, deployment, and monitoring.

Backend Engineering

Build APIs and microservices to serve AI models in production (FastAPI, Flask, Node.js, etc.).

Manage data pipelines, ETL processes, and integrations with databases (SQL, NoSQL, Data Lakes).

Ensure system security, reliability, and scalability in cloud or hybrid environments.

Frontend Engineering

Develop intuitive dashboards, tools, and user interfaces to interact with AI systems.

Work with React, Angular, or Vue.js for responsive web applications.

Collaborate with design/product teams to ensure user-friendly AI-driven features.

DevOps / Cloud

Deploy and manage AI systems on cloud platforms (AWS, Azure, GCP).

Use containerization (Docker, Kubernetes) for scalable model serving.

Automate workflows and ensure smooth integration of AI components with enterprise systems.

Collaboration

Work closely with Data Scientists, Product Managers, and Software Engineers to deliver end-to-end AI solutions.

Stay updated with the latest AI/ML and full-stack development trends and apply them effectively.

Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related field.

3+ years of experience in software engineering, with at least 2 years in AI/ML-related projects.

Proficiency in Python and one additional programming language (JavaScript/TypeScript, Java, C++).

Strong experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

Experience in backend frameworks (FastAPI, Flask, Django, Node.js).

Solid knowledge of frontend frameworks (React, Angular, or Vue.js).

Hands-on experience with cloud services (AWS SageMaker, GCP Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).

Knowledge of databases: SQL & NoSQL.

Familiarity with MLOps concepts (model monitoring, logging, retraining pipelines).

Strong problem-solving, communication, and teamwork skills.