Machine Learning Engineer

Rebel Space is seeking a talented and experienced Machine Learning Engineer to join our growing technical team. 

About Rebel Space: 

At Rebel Space, our mission is to protect critical space infrastructure through enhanced observability and space system cybersecurity.  We believe that as space infrastructure expands, it will be increasingly difficult to secure and monitor these systems against critical failures or evolving cyber threats.  To address this, we are building software that empowers developers and operators to rigorously evaluate and secure their systems from conception through to operations.  We supercharge the way space infrastructure is tested, monitored, and secured, ensuring systems are safeguarded in an increasingly complex space environment.  Join us in building the space security infrastructure of the future. 

Our view is that the convergence of artificial intelligence, software, robotics, and communications will significantly improve how we connect with physical hardware and digital systems.  By focusing on the integration of autonomy with space system cybersecurity, we hope to make physical and digital infrastructure more resilient in the face of a rapidly changing world. 

We value experimentation and seek to actively create a positive change through technological innovation.  We work in a collaborative environment where new ideas can be shared and explored respectfully and promote a workplace that enhances, not overwhelms, the lives of our team members.  We are based out of Long Beach, California and operate on a hybrid schedule. 

The Role: 

As a Machine Learning Engineer at Rebel Space, you will work with our engineering team to develop high quality prototypes by applying research, design, and engineering best practices. 

Responsibilities:

• Define and own system-wide data architecture that integrates data components across the Rebel Space autonomy stack for enhanced analysis and insights. 
• Research, prototype, and survey different ML architecture and workflow optimization techniques (e.g., Neural Architecture Search, Auto-ML) 
• Develop proofs-of-concept of customized optimizations that demonstrate the benefit of your optimizations on real-world models using real-world datasets. 
• Develop data collections, labeling pipelines, and evaluation pipelines.  Research and develop machine learning models for environmental and RF sensor resources. 
• Extend existing ML libraries and frameworks. 
• Create and deliver reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews. 
• Own technical projects from start to finish and be responsible for major technical decisions and tradeoffs.  Effectively participate in team planning, code reviews, and design discussions. 

Requirements

Basic Qualifications:

• Bachelor's degree in Computer Science, Electrical Engineer, Physics or related technical discipline with 5+ total years of industry experience 
• Strong expertise with machine learning (ML) frameworks such as Tensorflow, PyTorch, Scikit Learn, or Spark MLlib 
• Demonstrated experience working with programming languages such as Python, C/C++, or Go 
• Familiarity with overall big data analysis, system backend integration with new ML systems, and large-scale data processing 
• Excellent understanding of algorithms, data structures, and coding standards 
• Strong communication and behavioral skills 
• Motivated self-starter that can work autonomously and as part of a team 

Preferred Qualifications:

• PhD, Masters, or equivalent in Computer Science, Electrical Engineer, Physics or related field with 3+ years of professional experience in machine learning engineering 

• Experience developing highly performant, multi-threaded software 

• Experience with CI/CD, devops, and build systems 

• Familiarity working with containerized applications (Docker, Kubernetes, etc.) 

• Experience designing reliable software through requirements generation, continuous integration, automated testing, issue tracking, and code reviews 

• Experience with big-data architecture, ETL Frameworks such as Spark, MapReduce, Hive, etc. 

• Passionate about building autonomous systems 

Benefits

• Stock Option Plan – Equity in Rebel Space 
• Generous PTO including flexible vacation, sick and company paid holidays 
• Premium healthcare including Medical, Dental and Vision insurance 
• Life Insurance 
• Maternity/Paternity Leave 
• Flexible hybrid in-person and remote work schedule 
• Professional growth opportunities 

In addition to stock options, the estimated salary range for this role is $110,000-$170,000, inclusive of all levels/seniority within this discipline.

As a growing company, the salary range is intentionally wide as we determine the most appropriate package for each individual taking into consideration years of experience, location, educational background, and unique skills and abilities as demonstrated throughout the interview process.

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ITAR Requirements:

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), applicants must be a US citizen, lawful permanent resident of the U.S., protected individual as defined by 8 USC 1324b(a)(3), or eligible to obtain the required authorization from the US Department of State. Learn more about the ITAR here.

Rebel Space Technologies is an equal-opportunity employer, and we encourage candidates from all backgrounds to apply. If you are someone passionate to work on problems that matter, we’d love to hear from you.