AI Engineers, Software Developers, and Full-Stack Innovators

Job Description

Job Description

We are expanding our AI-driven teams and hiring

developers, engineers, and researchers

who are passionate about building the next generation of artificial intelligence systems. Whether your strength lies in

building user interfaces ,

developing back-end logic ,

training AI models , or

designing infrastructure , we have a place for you! You don’t need to know exactly where you fit—we’ll guide you. Just read the descriptions below and tell us which area matches your skills and interests best. Requirements 1. Front-End Developer

Designs and implements user-facing applications and dashboards. Key Skills:

React,

JavaScript/TypeScript,

TailwindCSS, Figma, UX principles.

2. Back-End Developer

Builds APIs and server-side systems that power AI tools and data pipelines. Key Skills:

Python, FastAPI, Go, SQL/NoSQL, REST/GraphQL.

3. Full-Stack Engineer

Develops end-to-end applications connecting front-end interfaces with back-end AI logic. Key Skills:

Combination of Front-End and Back-End skills, API design, CI/CD.

4. Machine Learning Engineer

Deploys, fine-tunes, and maintains AI models in production. Key Skills:

PyTorch/TensorFlow,

MLOps, model serving, inference optimization.

5. Data Engineer

Builds scalable data pipelines and manages datasets for training and evaluation. Key Skills:

Apache Airflow, Spark, SQL, Python, BigQuery, ETL systems.

6. Research Engineer

Bridges the gap between AI theory and implementation by building prototypes. Key Skills:

Python, ML libraries, LLM experimentation, rapid prototyping.

7. DevOps / Site Reliability Engineer (SRE)

Ensures reliability, monitoring, and automation across AI systems. Key Skills:

Kubernetes, Docker, Prometheus, CI/CD, Python/Bash.

8. Infrastructure Engineer

Designs and maintains the cloud infrastructure supporting AI training and deployment. Key Skills:

AWS/GCP, Terraform, distributed systems, cost optimization.

9. Security Engineer

Secures the platforms and services powering our AI stack. Key Skills:

Cloud security, identity management, penetration testing, audits.

10. AI Researcher (LLM / CV / RL)

Conducts experiments to advance the science behind our models (e.g., LLMs, computer vision, reinforcement learning). Key Skills:

Research publications, advanced ML theory, model development, experimentation.