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Rust Contract Jobs in Berkeley, CA (NOW HIRING)

Pwc

Digital Assets_ Crypto_ Manager

San Francisco, CA

$99K - $232K/yr

... smart contract solutions using Solidity and Rust programming languages - Embracing change and innovation in blockchain regulatory and compliance environments - Leading enterprise architecture ...

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Rust Contract information

What is a Rust contract developer?

Rust contract developers are programmers who specialize in writing smart contracts using the Rust programming language, commonly for blockchain platforms like Solana, NEAR, and Polkadot. These developers use Rust's safety and performance features to create secure and efficient decentralized applications (dApps) and protocols. Their work involves designing, coding, testing, and deploying smart contracts, ensuring that they function correctly and securely on the blockchain.

What types of projects and teams do Rust contract developers typically work on, and how is collaboration managed in these environments?

Rust contract developers are often brought on to contribute to high-performance systems, such as blockchain infrastructure, network services, or embedded applications. They usually join agile, cross-functional teams comprising other engineers, product managers, and sometimes DevOps professionals. Collaboration is managed through daily standups, code reviews, and regular communication via tools like Slack or GitHub. Contractors are expected to quickly familiarize themselves with project-specific codebases and processes, contributing clean, maintainable code while adhering to established development standards.

What are the key skills and qualifications needed to thrive as a Rust smart contract developer, and why are they important?

To thrive as a Rust Smart Contract Developer, you need strong proficiency in Rust programming, blockchain fundamentals, and experience with smart contract development, often supported by a relevant degree or certifications. Familiarity with tools like Cargo, testing frameworks, and blockchain platforms such as Solana or NEAR is essential. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for collaborating with teams and ensuring secure code. These skills are vital to building reliable, efficient, and secure smart contracts that meet project requirements and industry standards.

What is the difference between Rust Contract vs Rust Developer?

AspectRust ContractRust Developer
Required CredentialsExperience with Rust, contract law knowledge (if applicable)Proficiency in Rust programming, coding certifications
Work EnvironmentProject-based, freelance or consultingFull-time or part-time employment, in-house or remote
Industry UsageUsed in blockchain, smart contracts, and software projectsDevelops software applications, systems, or tools

The main difference is that a Rust Contract typically refers to a contractual role involving Rust skills, often project-based or freelance, focusing on specific deliverables. A Rust Developer is a full-time or part-time professional who writes and maintains Rust code within a company or organization. Both roles require Rust proficiency, but their work settings and responsibilities differ.

What are popular job titles related to Rust Contract jobs in Berkeley, CA?

For Rust Contract jobs in Berkeley, CA, the most frequently searched job titles are:

What cities near Berkeley, CA are hiring for Rust Contract jobs?

Cities near Berkeley, CA with the most Rust Contract job openings:

Rust Contract jobs near you

AI Engineer - Reinforcement Learning

Logical Intelligence

San Francisco, CA

Full-time

Posted 28 days ago

Job description

Who we are

At Logical Intelligence, we're revolutionizing software development with AI-powered formal verification. We've developed groundbreaking agents that provide mathematical guarantees of code correctness, ensuring that software behaves exactly as intended while proactively identifying bugs and security vulnerabilities. Our novel foundation model enables scalable, precise reasoning for formally verifiable code across Rust, Golang, and smart contract VMs. We've won ​​a well-known formal verification benchmark called PutnamBench, which consists of 672 hard math problems from the William Lowell Putnam Exam, the oldest collegiate mathematics competition in North America. Backed by a world-class team – including ICPC champions, a Fields Medalist and an ACM Turing Award winner – we're building the future where all code is provably correct.

About the role

Join our team as an AI Engineer and help us push the boundaries of what's possible in logical reasoning! We're looking for a motivated individual to design, implement, and refine efficient Large Language Models (LLMs) pipelines for scaled distributed training. You'll be at the forefront of designing and refining algorithms that go beyond the capabilities of traditional LLMs. You'll work closely with a talented team of AI experts, EBM specialists, formal verification engineers, and software developers to create groundbreaking solutions.

What you'll do
  • Implement new reasoning algorithms and models
  • Evaluate reasoning approaches, including latent space reasoning
  • Pre-train, fine-tune, and modify the State-of-the-Art LLMs
  • Optimizing and scaling LLM pipelines
  • Adjust frameworks and interfaces to accelerate machine learning development
  • Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution
Qualifications
  • Deep understanding of transformers' internals, and ability to make radical changes to the architecture and handle higher-order derivatives
  • Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like PyTorch /TensorFlow/JAX
  • Expertise in optimizing machine learning systems, including general techniques and LLM-specific optimizations
  • Understanding state-of-the-art approaches in LLM reasoning
  • Ability to understand complex learning approaches, such as energy-based models
  • Experience with basic distributed optimization techniques
  • Familiarity with torch.compile or similar performance optimization tools
  • Understanding of LLM architectures and LLM fine tuning internals
  • 3+ years of production experience in ML Infra, DataOps, distributed training. Proficiency with Kubernetes clusters and distributed compute assets
  • Strong communication and teamwork skills
  • Readiness to explore and promote cutting edge technologies in ML Infrastructure domain and beyond

Bonus Points:

  • Demonstrated publications in any of the major conferences
  • Experience in EBM or latent reasoning
  • Demonstrated publications in any of the major conferences
  • Mathematical Reasoning – discrete math and logic

logicalintelligence.com