About the Company :

We are a rapidly growing AI company building cutting-edge, production-grade AI solutions in computer vision, industrial automation, and smart monitoring. Our mission is to transform operations across industries through scalable and intelligent AI systems.

Role Summary :

We are seeking a Senior AI Developer who combines deep backend engineering expertise with a strong understanding of AI systems. You will play a key role in designing, building, and scaling AI-powered platformsfrom data pipelines to model deployment and monitoring.

This role suits an engineer who bridges AI development with real-world application, and thrives in creating scalable, robust, and automated AI infrastructures.

Key Responsibilities :

- Lead the design and development of scalable AI systems focusing on backend services, orchestration, and production readiness.

- Build modular AI pipelines for data processing, model training, deployment, and performance monitoring.

- Develop APIs, microservices, and backend logic for real-time AI inference and system integration.

- Collaborate with DevOps and infrastructure teams to deploy AI models across cloud, hybrid, or edge environments.

- Implement best practices for CI/CD, containerization, version control, and code quality.

- Optimize system performance through profiling, parallelization, and hardware-aware deployment (e.g., Jetson, GPUs).

- Ensure model reproducibility, monitoring, and observability using tools like MLflow, Prometheus, and Grafana.

- Mentor junior developers and promote best practices in scalable AI system design.

Must-Have Skills :

- Strong proficiency in Python; experience with Go or Rust is a plus.

- Expertise in backend development using FastAPI, Flask, or gRPC.

- In-depth understanding of AI system lifecycles from data ingestion to deployment.

- Hands-on experience with Docker, Kubernetes, and CI/CD for production deployments.

- Solid knowledge of distributed systems, asynchronous processing, and real-time APIs.

- Familiarity with model versioning and tracking tools like MLflow, DVC, or Weights & Biases.

- Comfortable working on Linux environments and deploying containerized AI workloads.

Preferred Qualifications :

- Experience with computer vision tasks (e.g., object detection, tracking) using frameworks like YOLO, UNet, or Transformers.

- Exposure to streaming inference systems (e.g., NVIDIA DeepStream, Kafka).

- Familiarity with edge AI hardware like Jetson or Coral and optimization tools like ONNX and TensorRT.

- Understanding of cloud platforms such as AWS, GCP, or Azure.

- Background in synthetic data generation, simulations, or data augmentation.

- Contributions to open-source projects or research in AI/ML infrastructure.

Educational Background :

- B.E./B.Tech/M.Tech in Computer Science, Software Engineering, or a related field.

- Minimum 5 years of professional experience in software engineering, preferably within AI/ML product teams.