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Mid LevelFull-timePythonJavaGolangReactKubernetesMachine LearningTensorFlowPyTorchAgileAI
Salary Range
$102,000 - $138,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a ML Engineer to join our AI-native team focused on building scalable machine learning systems. This role involves developing end-to-end ML lifecycle systems and creating advanced experimentation frameworks.
Key Responsibilities
- →Build and evolve end-to-end ML lifecycle systems from data processing to model serving
- →Design and implement sophisticated monitoring systems that track technical health and quality metrics
- →Create advanced experimentation frameworks for rapid A/B testing of algorithms
- →Design low-latency, high-throughput serving systems with appropriate caching strategies
- →Establish MLOps best practices using MLflow for experiment tracking and deployment automation
- →Build stream processing pipelines for real-time feature computation
- →Scale and optimize training and serving of machine learning models
Requirements
- ✓Strong coding skills in Python, Java, Golang, or Scala
- ✓Experience with Big Data frameworks like Spark and Kubernetes
- ✓Proficient in implementing API performance monitoring solutions
- ✓Skilled in developing end-to-end machine learning pipelines
- ✓Ability to design scalable ML architectures
- ✓Familiar with model and data versioning, resource allocation, and scaling
- ✓Experienced in creating systems that monitor and react to faults
- ✓Expertise with MLOps tools for production-level deployment
- ✓Strong problem-solving skills and ability to work in a fast-paced environment
- ✓At least 2-4+ years of professional experience in building and operating machine learning systems at scale
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