2 hours ago
Responsibilities
- Design, build, and evolve scalable machine learning systems and services, including low-level system design, API design, and data modeling.
- Own end-to-end delivery of ML features and platforms from problem framing and feature engineering through model development, testing, deployment, monitoring, and operational support.
- Translate ambiguous business and customer problems into production ML solutions in collaboration with product, data, and engineering teams.
- Improve model and system quality, reliability, performance, observability, security, and operational excellence.
- Operate production ML workflows, monitor model and data health, respond to incidents, and iterate based on experiments and operational feedback.
- Lead technical design discussions and mentor engineers and data practitioners through reviews and knowledge sharing.
Requirements
- Bachelor’s degree in Computer Science or a related technical field, or equivalent related professional experience.
- 8+ years of relevant professional experience.
- Strong proficiency in at least one modern programming language used for ML, such as Python or Java.
- Deep understanding of software engineering, system design, API design, data modeling, and ML fundamentals including training, evaluation, and deployment.
- Experience integrating ML capabilities into service-oriented or microservice architectures using APIs and large-scale data pipelines.
- Hands-on production experience with ML workflows, monitoring, incident response, experimentation, and operational improvement.
- Preferred experience architecting distributed ML platforms, high-volume or low-latency prediction systems, batch inference, resilient data models, and versioned API contracts.
- Preferred ability to lead technical designs and make tradeoffs involving modeling complexity, performance, operational cost, and organizational standards.
- Preferred experience with model and data observability, automation, model CI/CD, feature stores, model registries, advanced ML tooling, distributed training, ML platforms, or inference optimization.
Benefits
- Medical, dental, and vision coverage; paid time off; an Employee Assistance Program; wellness and travel reimbursement; travel discounts; and IATAN membership.
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