Introduction
We are seeking a Real-Time AI Applications Developer who specializes in creating AI systems with strict latency and performance requirements. If you are passionate about building real-time inference systems that power critical applications in finance, healthcare, autonomous systems, or IoT, this role provides the opportunity to work on cutting-edge AI infrastructure.
As a Real-Time AI Applications Developer at our organization, you will design and optimize AI pipelines for speed, resilience, and scalability. You’ll collaborate with engineers, data scientists, and product teams to deploy high-performance applications that respond instantly in dynamic environments.
We offer competitive compensation, comprehensive benefits, and opportunities to design the next generation of real-time AI solutions.
Objectives of this role
- Develop AI systems optimized for real-time performance and low latency.
- Ensure system reliability in high-frequency and mission-critical environments.
- Collaborate with infrastructure teams to integrate real-time AI pipelines.
- Continuously improve system resilience and fault tolerance.
Your tasks
- Design and implement real-time AI inference pipelines.
- Optimize models for GPU/TPU acceleration and edge hardware deployment.
- Build monitoring systems for latency, throughput, and uptime.
- Collaborate on CI/CD pipelines for rapid and safe deployment.
- Conduct stress testing and performance benchmarking.
- Document and communicate best practices in real-time AI deployment.
Required skills and qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 4+ years of experience in real-time systems or high-performance AI applications.
- Proficiency with ML frameworks and deployment tools (TensorRT, ONNX Runtime).
- Strong programming skills in Python, C++, or Rust.
- Experience with low-latency systems and distributed architecture.
Preferred skills and qualifications
- Knowledge of event-driven and streaming architectures (Kafka, Flink).
- Experience deploying real-time AI for finance, healthcare, or AVs.
- Familiarity with edge AI optimization techniques.
- Strong background in systems performance tuning and debugging.
- Contributions to open-source real-time AI frameworks.
