
AI/ML Developer
3 days ago
Location:
Bengaluru, India (On-Site)
Experience:
5+ Years
Employment Type:
Full-Time
Role Overview
We are seeking a
Senior AI Engineer
with strong backend engineering and architectural expertise, particularly in building and scaling AI-powered systems in production environments. The role is ideal for professionals who combine backend development skills with deep knowledge of AI systems — bridging the gap between model development and large-scale real-world deployment.
You will be responsible for designing system-level architecture, enabling scalable deployments, and driving the development of AI infrastructures with a focus on backend robustness, automation, and lifecycle management.
Key Responsibilities
- Design and lead the architecture of scalable AI systems with emphasis on backend services, orchestration, and operationalization.
- Build and manage modular AI pipelines — from data pre processing to training, model serving, and monitoring.
- Develop APIs, microservices, and backend logic for AI model interaction, integration, and real-time inference.
- Collaborate with DevOps, data, and infrastructure teams to deploy models in cloud, hybrid, or edge environments.
- Ensure code quality and maintainability using CI/CD, containerization, and version control.
- Optimize systems through profiling, parallelization, and hardware-aware deployment (e.g., GPUs, Jetson).
- Implement best practices for reproducibility, governance, and observability with tools like MLflow, Prometheus, and Grafana.
- Mentor junior engineers in backend and AI system design.
Must-Have Skills
- Strong programming skills in
Python
(bonus: Go or Rust). - Experience building and deploying scalable backends with
FastAPI, Flask, gRPC
, or similar frameworks. - In-depth understanding of AI system lifecycle — from data ingestion to monitoring.
- Proficiency with
Docker, Kubernetes, and CI/CD pipelines
for ML system deployment. - Knowledge of asynchronous processing, distributed systems, and real-time API design.
- Familiarity with model versioning/tracking tools like
MLflow, DVC, or Weights & Biases
. - Hands-on experience with Linux-based systems and containerized deployments.
Nice to Have
- Exposure to computer vision (e.g., YOLO, UNet, Transformers).
- Experience with streaming inference systems (e.g., NVIDIA DeepStream, Kafka).
- Knowledge of edge AI hardware (Jetson, Coral) and optimization (ONNX, TensorRT).
- Familiarity with
AWS, GCP, or Azure
for AI deployment. - Experience in synthetic data generation, simulation, or data augmentation.
- Contributions to open-source or research publications in AI/ML infrastructure.
Qualifications
- B.E./B.Tech/M.Tech in Computer Science, Software Engineering, or related field.
- 5+ years of experience in software engineering, preferably with AI/ML systems.
- Proven expertise in designing and deploying production-grade AI solutions.
What You'll Gain
- Opportunity to design and implement cutting-edge AI infrastructures.
- Work alongside a highly skilled and collaborative technical team.
- Ownership of systems end-to-end — from architecture to deployment at scale.
- Exposure to advanced tools, frameworks, and hardware in real-world AI deployments.
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