Senior embedded engineer developing safety - critical ECU firmware for Hexagon Mining’s digital mining and vehicle - control technologies. Designing, testing, and commissioning embedded systems.
About the role
- Principal Software Engineer developing machine learning features for Workday's HR & Talent platform. Collaborating with engineers to deliver infrastructure and APIs for ML capabilities at scale.
Responsibilities
- Lead the design and implementation of high-throughput microservices and APIs (Python/Go) that serve as the backbone for Workday’s ML ecosystem
- Build and optimize a unified ML development experience using Kubeflow, Kubernetes (EKS/GKE), and specialized compute orchestration (CPUs/GPUs)
- Own the end-to-end lifecycle of cloud-based services, utilizing Infrastructure as Code (Terraform) to build resilient, self-healing environments
- Lead architecture reviews, code reviews, and technology evaluations to ensure our systems meet 99.99% reliability standards
- Design the architectural patterns and observability frameworks required to support emerging Agentic AI systems and LLM-based applications
- Partner with data scientists, ML engineers, and architects to translate complex data needs into elegant, maintainable software solutions
- Research and drive adoption of new infrastructure tools with a focus on reliability, security, and enterprise-grade scale
Requirements
- 6 or more years of validated industry experience
- Bachelor’s and/or Master’s degree in Computer Science or Computer Engineering
- Strong software engineering experience with designing and building scalable, distributed systems
- Deep understanding of cloud computing, cloud infrastructure, and distributed systems; experience with AWS and GCP
- Experience developing microservices, APIs, robust cloud service, large-scale web applications, managing CI/CD workflows
- Proficiency with Python, Go, and infrastructure-as-code tools like Terraform
- Experience running and maintaining Kubernetes clusters in production
- Ensure security and compliance of cloud platforms, implementing best practices for encryption, data protection, and access control
- Experience with large-scale ML data pipelines and data lakes
- Ability to think across layers of the ML stack, from infrastructure to model deployment
- Experience developing monitoring and alerting systems for ML infrastructure
- Understanding of agentic AI concepts; experience with LangChain and LangSmith is preferred.
- Proven leadership or mentoring experience.
Benefits
- Workday Bonus Plan
- role-specific commission/bonus
- annual refresh stock grants
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