Career at Pramaana
Career at Pramaana
Research Engineer, AI Systems and Scaling
Location
Location
San Jose, California
San Jose, California
Employment Type
Employment Type
Full Time
Full Time
Location Type
Location Type
Onsite
Onsite
Department
Department
Technology
Technology
Location Type
Onsite
Department
Technology
Overview
Application
About Pramaana
Pramaana is on a mission to define the gold standard for verification. We are building the future of trustworthy AI by moving beyond probabilistic models to deterministic systems. Our core focus is on formal verification and proof-based reasoning, enabling us to mathematically validate the correctness of AI-generated information. We are solving the "trust" problem in AI for high-stakes environments where accuracy is non-negotiable.
About the Role
This role is critical to Pramaana’s mission of creating trustworthy AI through formal verification and proof-based reasoning. As a key member of the engineering team, you will drive the development of the company’s core artificial intelligence technologies. Your primary focus will be designing scalable AI systems that generate accurate, verifiable outputs and developing methods to mathematically validate the correctness of AI-generated information. You will also be responsible for advancing research and ensuring that all of Pramaana’s AI systems strictly adhere to rigorous scientific and ethical standards.
Key Responsibilities
Design and implement high-performance infrastructure for large language model training and inference
Design and test new methods that convert AI-generated responses into machine-checkable proofs
Implement comprehensive monitoring systems for model training and inference infrastructure
Create and optimize distributed computing systems for processing web-scale datasets
Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability
Collaborate with engineering teams to implement scalable systems on cloud platforms such as Google Cloud (GCP) and Kubernetes
Build and maintain documentation for infrastructure components and systems
Contribute to the development of the company’s research strategy in artificial intelligence, formal verification, and proof-based reasoning
Qualifications
PhD or Master’s in Computer Science, AI, or Mathematics, related technical fields, or equivalent industry experience.
Having 4+ years of experience in ML infrastructure or distributed systems.
Expert knowledge of Python, C++, and frameworks like PyTorch or JAX.
Hands-on experience scaling AI systems using GCP, Kubernetes, and distributed training tools.
Familiarity with formal verification, theorem provers (e.g., Lean, Coq), or mathematical logic is strongly preferred.
Knowledge of reinforcement learning techniques.
Overview
Application
About Pramaana
Pramaana is on a mission to define the gold standard for verification. We are building the future of trustworthy AI by moving beyond probabilistic models to deterministic systems. Our core focus is on formal verification and proof-based reasoning, enabling us to mathematically validate the correctness of AI-generated information. We are solving the "trust" problem in AI for high-stakes environments where accuracy is non-negotiable.
About the Role
This role is critical to Pramaana’s mission of creating trustworthy AI through formal verification and proof-based reasoning. As a key member of the engineering team, you will drive the development of the company’s core artificial intelligence technologies. Your primary focus will be designing scalable AI systems that generate accurate, verifiable outputs and developing methods to mathematically validate the correctness of AI-generated information. You will also be responsible for advancing research and ensuring that all of Pramaana’s AI systems strictly adhere to rigorous scientific and ethical standards.
Key Responsibilities
Design and implement high-performance infrastructure for large language model training and inference
Design and test new methods that convert AI-generated responses into machine-checkable proofs
Implement comprehensive monitoring systems for model training and inference infrastructure
Create and optimize distributed computing systems for processing web-scale datasets
Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability
Collaborate with engineering teams to implement scalable systems on cloud platforms such as Google Cloud (GCP) and Kubernetes
Build and maintain documentation for infrastructure components and systems
Contribute to the development of the company’s research strategy in artificial intelligence, formal verification, and proof-based reasoning
Qualifications
PhD or Master’s in Computer Science, AI, or Mathematics, related technical fields, or equivalent industry experience.
Having 4+ years of experience in ML infrastructure or distributed systems.
Expert knowledge of Python, C++, and frameworks like PyTorch or JAX.
Hands-on experience scaling AI systems using GCP, Kubernetes, and distributed training tools.
Familiarity with formal verification, theorem provers (e.g., Lean, Coq), or mathematical logic is strongly preferred.
Knowledge of reinforcement learning techniques.
Overview
Application
About Pramaana
Pramaana is on a mission to define the gold standard for verification. We are building the future of trustworthy AI by moving beyond probabilistic models to deterministic systems. Our core focus is on formal verification and proof-based reasoning, enabling us to mathematically validate the correctness of AI-generated information. We are solving the "trust" problem in AI for high-stakes environments where accuracy is non-negotiable.
About the Role
This role is critical to Pramaana’s mission of creating trustworthy AI through formal verification and proof-based reasoning. As a key member of the engineering team, you will drive the development of the company’s core artificial intelligence technologies. Your primary focus will be designing scalable AI systems that generate accurate, verifiable outputs and developing methods to mathematically validate the correctness of AI-generated information. You will also be responsible for advancing research and ensuring that all of Pramaana’s AI systems strictly adhere to rigorous scientific and ethical standards.
Key Responsibilities
Design and implement high-performance infrastructure for large language model training and inference
Design and test new methods that convert AI-generated responses into machine-checkable proofs
Implement comprehensive monitoring systems for model training and inference infrastructure
Create and optimize distributed computing systems for processing web-scale datasets
Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability
Collaborate with engineering teams to implement scalable systems on cloud platforms such as Google Cloud (GCP) and Kubernetes
Build and maintain documentation for infrastructure components and systems
Contribute to the development of the company’s research strategy in artificial intelligence, formal verification, and proof-based reasoning
Qualifications
PhD or Master’s in Computer Science, AI, or Mathematics, related technical fields, or equivalent industry experience.
Having 4+ years of experience in ML infrastructure or distributed systems.
Expert knowledge of Python, C++, and frameworks like PyTorch or JAX.
Hands-on experience scaling AI systems using GCP, Kubernetes, and distributed training tools.
Familiarity with formal verification, theorem provers (e.g., Lean, Coq), or mathematical logic is strongly preferred.
Knowledge of reinforcement learning techniques.
