Intern working on avionics hardware and software for Blue Origin. Gaining hands - on experience while contributing to space development projects.
About the role
- Senior Machine Learning Engineer developing predictive solutions for business challenges within healthcare. Leveraging GCP and Vertex AI to bridge data science and engineering.
Responsibilities
- Design, develop, and implement predictive models, machine learning algorithms, and decision engines to address complex business challenges
- Conduct experiments, tune hyperparameters, and apply advanced modeling techniques to improve the accuracy, scalability, and efficiency of new and existing models
- Partner with cross-functional stakeholders to translate business requirements into technical specifications for ML solutions
- Execute full-stack engineering tasks including data preprocessing, feature engineering, model deployment, API development, and integration with enterprise systems
- Engineer scalable, secure, compliant, and production-grade ML pipelines with modern cloud-native technologies
- Design and implement distributed training workflows, online inference systems, and low-latency serving architectures
- Propose new platform solutions and enhancements that improve capabilities and performance of existing scheduling systems and decision engines
- Partner with system architects to ensure adequate hardware, compute resources, and platform configurations (Kubernetes, Cloud Run) to support machine learning applications
- Define key metrics, monitoring frameworks, and automated alerts to continuously evaluate the performance and drift of deployed models
- Create clear, comprehensive documentation and support guides for newly implemented tools
- Provide technical guidance and mentorship to junior engineers and data scientists
Requirements
- 5+ years of experience in machine learning engineering, data science, or related technical role
- Strong proficiency with Python and AI/ML frameworks (LLMs, TensorFlow, PyTorch, Scikit-learn, etc.)
- Strong hands-on expertise with Google Cloud Platform (GCP), training, pipelines, deployment, BigQuery, and Airflow
- Solid understanding of software engineering principles, and API development
- Proven track record of building and deploying ML models into production systems at scale
- Bachelor's degree in Computer Science, Data Science, Engineering, or related technical field
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- 401(k) savings plan with match
- Paid time off
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