JOB DUTIES AND RESPONSIBILITIES
- Design, develop, and maintain deep learning pipelines for real-time data processing.
- Evaluate and curate relevant datasets; establish model benchmarks to measure performance.
- Improve observability and monitoring for deployed ML systems.
- Develop, deploy, and maintain microservices that deliver ML capabilities to production systems.
- Enhance tooling and orchestration for tuning, deployment, and scaling of ML pipelines.
- Collaborate in research and development initiatives, contributing to new ML capabilities for aerospace and defense applications.
- Document designs, workflows, and operational best practices to ensure maintainable and resilient ML systems.
JOB REQUIREMENTS AND MINIMUM QUALIFICATIONS
- Bachelor’s or higher degree in Computer Science, Engineering, or related technical field.
- 6+ years of professional experience developing production-ready ML systems in small to medium-sized organizations (additional experience required for larger organizations).
- Proficiency in Python with demonstrated experience implementing ML algorithms in production environments.
- Experience designing and maintaining APIs for ML services.
- Hands-on experience deploying and managing ML workflows in Kubernetes environments.
- Strong communication skills with the ability to clearly articulate complex technical ideas.
- Ability to work effectively in a collaborative, Agile engineering team.
PREFERRED EXPERIENCE
- Knowledge of microservice architectures and distributed data systems.
- Familiarity with aerospace or defense applications of ML systems.
- Track record of contributing to early-stage or rapidly scaling teams.
Skills Required
- U.S. citizen, lawful permanent resident, conditional resident, asylee/refugee, or eligible to obtain required U.S. Department of State authorizations
- Bachelor's or higher degree in Computer Science, Engineering, or related technical field
- 6+ years professional experience developing production-ready ML systems
- Proficiency in Python with experience implementing ML algorithms in production
- Experience designing and maintaining APIs for ML services
- Hands-on experience deploying and managing ML workflows in Kubernetes environments
- Strong communication skills and ability to articulate complex technical ideas
- Ability to work effectively in a collaborative, Agile engineering team
CesiumAstro Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about CesiumAstro and has not been reviewed or approved by CesiumAstro.
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Healthcare Strength — Health coverage includes medical, dental, vision, life and disability insurance, plus FSAs and mental health benefits. Feedback suggests the health package is comprehensive for a growth-stage aerospace firm.
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Retirement Support — Offerings include a 401(k) with company matching and other retirement-plan elements. Feedback suggests core retirement mechanisms are in place alongside standard financial benefits.
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Leave & Time Off Breadth — Generous PTO, paid holidays, paid sick days, and bereavement leave are included. Feedback suggests time-off options are broad on paper across multiple leave types.
CesiumAstro Insights
What We Do
We build high-throughput, plug-and-play phased array communication payloads for space and airborne platforms. CesiumAstro’s full-stack, multi-mission hardware and software products enable a diverse range of commercial and defense objectives. Full-system engineering design is at the heart of every CesiumAstro product. We deliver high-performance solutions under rapid development timelines.
Why Work With Us
At CesiumAstro, we’re a team. We’re passionate, respectful, and determined colleagues ready to help at a moment’s notice. We’re mentors excited to enable our peers with the knowledge they need to succeed. Together, we’re visionaries committing to building memories that will last a lifetime.
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