As a
You will be responsible for:
- ML Serving Architecture : Design and implement high-performance inference APIs and model serving backends using Java & Python.
- Model Lifecycle Management : Build systems for model versioning, A/B testing, canary deployments, and automated rollbacks.
- Integration Platform : Create robust APIs and SDKs that enable product teams to seamlessly integrate AI capabilities.
- Observability & Monitoring : Build comprehensive metrics, logging, and tracing systems for ML workloads.
- Cross-team Leadership : Mentor engineers & researchers, drive technical decisions, and influence platform architecture across the organization.
You should apply if you have:
- 6+ years of hands-on experience in large-scale backend development, with strong emphasis on Java programming and building high-performance AI/ML inference systems.
- Strong analytical and problem-solving skills, with the ability to debug and resolve complex technical issues in AI applications serving millions of requests daily.
- Experience with cloud platforms (AWS preferred, Azure, or Google Cloud) and building scalable microservices architectures for AI model serving and data processing pipelines.
- Advantageous experience with ML frameworks (TensorFlow, PyTorch), model serving platforms (Triton, TorchServe, KServe), and building high-throughput AI-powered APIs and data processing systems.
- Excellent communication skills, both verbal and written, with the ability to articulate technical AI system design decisions clearly and collaborate effectively with ML engineers, data scientists, and DevOps teams.
- A Bachelor's degree in Computer Science, Engineering, or a related field is preferred. Experience with AI/ML systems in production environments is highly valued.
*We operate in a flexible hybrid work model.
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