Machine Learning Engineer

MLOps

5+

Remote

Responsibilities:

? 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

? Develop monitoring and observability solutions for ML systems

? Collaborate with ML Engineers to establish best practices for optimized model deployment

? Implement cost-efficient, enterprise-scale solutions

? Collaborate in a cross-functional, distributed team for continuous system improvement

? Work with MLEs, QA Engineers, and DevOps Engineers

? Evaluate and implement new technologies and tools

? Contribute to architectural decisions for distributed ML systems

Experience and Qualifications:

? 5+ years of experience in software engineering with Python

? Experience with ML frameworks, particularly PyTorch

? Experience optimizing ML models with hardware acceleration (AWS Neuron , ONNX,

TensorRT)

? Experience with AWS ML services and hardware-accelerated instances (Sagemaker,

Inferentia, Trainium)

? Proven experience building and operating AWS serverless architectures

? Deep understanding of event-driven processing patterns, SQS/SNS and serverless caching

solutions

? Experience with containerization using Docker and orchestration tools

? Strong knowledge of RESTful API design and implementation

? Proficiency in writing good quality & secure code and be familiar with static code analysis

tools

? Excellent analytical, conceptual and communication skills in spoken and written English

? Experience applying Computer Science fundamentals in algorithm design, problem solving,

and complexity analysis