SDE III - MLOps (AI Engineering)

TL;DR

SDE III - MLOps (AI Engineering): Develops the blueprint for highly scalable and performant ML model serving. Focus on building and optimizing model serving infrastructure with a focus on inference latency and cost optimization, also architecting efficient inference pipelines that balance latency, throughput, and cost across various acceleration options.

Location: Bangalore

Company

hirify.global is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer.

What you will do

• Upgrade ML assets (models, data) management systems for better developer experience and robust governance capabilities.
• Build and optimize model serving infrastructure with a focus on inference latency and cost optimization.
• Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options.
• Implement cost-efficient, enterprise-scale solutions.
• Collaborate in a cross-functional, distributed team for continuous system improvement.
• Contribute to architectural decisions for distributed ML systems.

Requirements

• 5+ years of experience in software engineering with Python.
• Experience with model lifecycle management (MLFlow, Weights & Biases or equivalent).
• Experience with data management ecosystem (quality, transformation, catalog).
• Experience with ML frameworks, particularly PyTorch.
• Experience optimizing ML models with hardware acceleration (AWS Neuron , ONNX, TensorRT).
• Proven experience building and operating AWS serverless architectures.
• Excellent analytical, conceptual and communication skills in spoken and written English.

Nice to have

• Experience with any of the following: model compilation and quantization, performance profiling and benchmarking ML inference systems.
• Experience working in regulated industries with strict compliance requirements for cloud-native solutions.

Culture & Benefits

• Friendly and supportive environment.
• Adaptable and flexible culture.
• Opportunities for growth and development.
• Collaboration with diverse teams.
• Focus on innovation and impact.