Software/ML Engineer
New York, New York, United States
Applications have closed
As a member of Inpher, you collaborate to design and develop algorithms in the context of large scale privacy-preserving computations.
What You Will Do
- Contribute to our privacy-preserving machine learning library by adapting and implementing toolkits and models that are widely used in industry
- Analyze and report algorithm performance in terms of correctness, precision, execution time, memory usage, and network communication. Identify precision cliffs, performance bottlenecks, and high resource usage. Implement improvements upon the identified issues.
- Benchmark our privacy preserving-algorithms against the state-of-the-art, both privacy-preserving and plaintext
- Apply software engineering best practices. Write production grade code targeted to customers
- Develop demo use cases to demonstrate and educate about the possibilities and potential of privacy preserving algorithms
- Participate in the design and development of additional privacy-preserving techniques and backends
- Research and prototype new ideas to improve algorithm performance, expand our product portfolio, and enhance the user experience
Requirements
What You Have Done
- MS or PhD in Computer Science, Mathematics, Statistics, or equivalent
- 2+ years of implementation or research experience in data science
- 2+ years of experience developing software
- Solid experience in Software Engineering (software design, debugging, testing, documentation, version control)
- Experience implementing machine learning or AI solutions in industry or research
- Proficiency in Python, Scala, or C/C++ (other languages are a plus)
- Strong interpersonal skills, able to work independently as well as in a team
- Self-direction, creativity, and high attention to detail
Location
There is currently one opening. Candidates must have authorization to work in either Switzerland or the United States.
About Inpher
Inpher has pioneered cryptographic Secret Computing® that enables advanced analytics and machine learning models while keeping data private, secure, and distributed. At Inpher, we believe that privacy and security are foundational to the future of computing and have built enterprise products to make this vision a reality. Our world-class cryptographers have won numerous international encrypted data competitions, regulatory techsprints, and Gartner Cool Vendor awards. We are headquartered in New York City, with satellite offices in San Francisco and Lausanne, Switzerland, and have raised over $14M in funding.
Tags: C++ Computer Science Engineering Machine Learning Mathematics ML models PhD Privacy Python Research Scala Security Statistics Testing
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