Research Engineer in Massachusetts

About the Role:
CloudZero is seeking a highly skilled, innovative, and collaborative Lead Data Engineer to join the newly formed and dynamic research team under the Office of the CTO. In this role, you will partner closely with teams across the organization and play a leading and pivotal role in researching and developing our data infrastructure as the company goes through incredible growth. In this role you will help enable clean, reliable, and organized data models that empower the organization to make informed, data-driven decisions. 

You will also be instrumental in providing high-quality data to support our AI/ML data scientists and other data-driven initiatives. Using tools like Snowflake, Looker, AWS Aurora, and other modern data engineering technologies, you will lead the research, design and implementation of innovative data solutions. Additionally, you will have the opportunity to grow and manage a team of talented data engineers,...

Role Description:

Our mission is to enable hardware innovation at the speed of software development! We are working towards automatic code transpilation and optimization for any hardware application. Our work integrates cutting-edge methods in AI, formal verification, compilers, and much more.

In this role, you will collaborate with a small team of talented researchers on ambitious, greenfield projects in GenAI and RL.

Research Areas of Interest:

An incomplete list of ongoing and near-term research directions:

• Large-scale LLM post-training / finetuning
• RLHF, RLAIF, etc
• Decoding-time techniques for self-correction and repair
• Steerability, guided decoding, and constraint enforcement
• Code representations and similarity

Core Responsibilities:

• Help build robust, scalable infrastructure and tooling
• Contribute...

Description: We’re looking for passionate and experienced Research Engineers to become an integral part of our research team. The ideal candidate will have a strong background in machine learning, programming, and applied research. This is an incredible opportunity to join an experienced founding team who have collectively raised $1bn+ in capital across several previously successful ventures and lead AI Research within the business.

In this role, you will collaborate with a small team of talented researchers and engineers on exciting new projects in program synthesis and code transpilation, blending formal methods and modern deep learning architectures like graph neural networks and large language models.

Core Responsibilities:

• Design methods, tools, and infrastructure to push forward the state of the art in program synthesis.
• Define research goals informed by practical engineering concerns.
• Contribute to...

We’re looking for passionate, experienced Software Engineers to become an integral part of our engineering team. The ideal candidate would possess a strong technical background and practical experience in software development, particularly in complex environments where formal methods and program synthesis play a significant role.

In this role, you will collaborate with a small team of talented researchers and engineers on exciting new projects in program synthesis and code transpilation, by blending formal methods and modern deep learning architectures like graph neural networks and large language models. 

Core Responsibilities:

• Work closely with a team of researchers and engineers to support the development of new technologies. This includes designing and testing new software tools, developing algorithms, and implementing prototypes that push the boundaries of what's possible in program synthesis and code transpilation.
...

We’re looking for passionate and experienced Research Engineers to become an integral part of our research team. The ideal candidate will have a strong background in machine learning, programming and applied research.

In this role, you will collaborate with a small team of talented researchers and engineers on exciting new projects in program synthesis and code transpilation, by blending formal methods and modern deep learning architectures like graph neural networks and large language models.

Core Responsibilities:

• Design methods, tools, and infrastructure to push forward the state of the art in program synthesis.
• Define research goals informed by practical engineering concerns.
• Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g....