Member of Technical Staff - Research Engineering (Remote)
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Key skills for this role
About the Role
We are hiring a Member of Technical Staff for Research Engineering to advance research engineering initiatives within the Micro1 platform, focusing on scalable AI solutions and infrastructure optimization.
Key Skills for This Role
Responsibilities
- Design, prototype, and implement research engineering solutions to enhance AI model performance and scalability
- Optimize existing research pipelines to improve computational efficiency and reduce latency in distributed systems
- Collaborate with data science and engineering teams to integrate research findings into production grade systems
- Conduct performance benchmarking and analyze system bottlenecks to inform architectural decisions
- Document research methodologies, experimental results, and technical specifications for internal stakeholders
Requirements
- Proficiency in Python, C++, or Rust for high performance computing and algorithm development
- Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray
- Strong background in machine learning systems, including model optimization and inference acceleration
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes)
- Knowledge of linear algebra, optimization techniques, and numerical computing libraries (NumPy, SciPy)
- Ability to write clean, maintainable, and well documented code for research and production environments
- Experience with version control systems (Git) and collaborative software development workflows
- Understanding of data structures, algorithms, and complexity analysis for scalable system design
Full Job Posting
Role Overview
- We are hiring for one of our clients, seeking a Member of Technical Staff, Research Engineering to work on a full time basis.
- The role involves advancing research engineering initiatives within the Micro1 platform, focusing on scalable AI solutions and infrastructure optimization.
- Collaboration with cross functional teams will drive the development of next generation research tools.
Key Responsibilities
- Design, prototype, and implement research engineering solutions to enhance AI model performance and scalability.
- Optimize existing research pipelines to improve computational efficiency and reduce latency in distributed systems.
- Collaborate with data science and engineering teams to integrate research findings into production grade systems.
- Conduct performance benchmarking and analyze system bottlenecks to inform architectural decisions.
- Document research methodologies, experimental results, and technical specifications for internal stakeholders.
Required Skills & Qualifications
- Proficiency in Python, C++, or Rust for high performance computing and algorithm development.
- Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
- Strong background in machine learning systems, including model optimization and inference acceleration.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Knowledge of linear algebra, optimization techniques, and numerical computing libraries (NumPy, SciPy).
- Ability to write clean, maintainable, and well documented code for research and production environments.
- Experience with version control systems (Git) and collaborative software development workflows.
- Understanding of data structures, algorithms, and complexity analysis for scalable system design.
Payout
- $220K $500K/yr
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