This role is for one of the Weekday's clients
Min Experience : 5 years
JobType : full-time
This role is ideal for someone who thinks like a backend engineer but speaks the language of AI — bridging the gap between advanced AI development and real-world deployment at scale. We are looking for a Senior AI Developer with strong backend engineering and architectural expertise to design, build, and scale production-grade AI systems.
This is a hands-on, technical role that involves working across data pipelines, APIs, model serving, and monitoring — ensuring robustness, reproducibility, and automation throughout the AI lifecycle.
Requirements
Key Responsibilities
- Design and implement scalable AI architectures with focus on backend services, orchestration, and operationalization.
- Build modular pipelines for data preprocessing, model training, serving, and monitoring.
- Develop APIs, microservices, and backend logic for real-time AI model integration and inference.
- Collaborate with DevOps, data, and infrastructure teams to deploy AI models across cloud, hybrid, and edge environments.
- Apply best practices for CI / CD, containerization, and version control.
- Optimize performance with profiling, parallelization, and hardware-aware deployments (GPUs, Jetson, etc.).
- Ensure reproducibility and observability using tools like MLflow, Prometheus, and Grafana.
- Mentor junior engineers in scalable AI system design and engineering best practices.
Must-Have Skills
Strong backend programming in Python (bonus : Go, Rust).Experience with FastAPI, Flask, gRPC, or similar frameworks.Deep understanding of the AI lifecycle — data ingestion → training → deployment → monitoring.Proficiency with Docker, Kubernetes, and CI / CD pipelines.Knowledge of distributed systems, asynchronous processing, and real-time API patterns.Experience with MLflow, DVC, or Weights & Biases.Comfortable with Linux systems and containerized AI deployments.Nice to Have
Exposure to computer vision (YOLO, UNet, transformers).Experience with streaming inference systems (e.g., NVIDIA DeepStream, Kafka).Hands-on with edge AI hardware (Jetson, Coral) and optimizations (ONNX, TensorRT).Familiarity with cloud platforms (AWS, GCP, Azure).Experience in synthetic data generation or augmentation.Open-source contributions or publications in AI / ML systems.Qualifications
B.E. / B.Tech / M.Tech in Computer Science, Software Engineering, or related field.5+ years of software engineering experience, ideally in AI / ML product companies.Proven track record of designing, building, and deploying production-grade AI systems.Skills : Python
Artificial IntelligenceMachine LearningOpenCVTensorFlowDockerNode.jsExpress.js