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Rust Library Jobs in New York (NOW HIRING)

Adaptive ML

Performance Engineer, Rust

Manhattan, NY · On-site

You will write high-quality Rust, diagnose complex bugs at the hardware-software boundary, and ... libraries;Passionate about the future of generative AI, and eager to build foundational technology ...

Adaptive ML

Performance Engineer, Rust

New York, NY · On-site

You will write high-quality Rust, diagnose complex bugs at the hardware-software boundary, and ... libraries; * Passionate about the future of generative AI, and eager to build foundational ...

BNY

Director, Cyber Security Engineer

Manhattan, NY · On-site +1

$127K - $225K/yr

Proficiency in secure coding practices with C/C++, Go, or Rust, and familiarity with cryptographic libraries such as OpenSSL or MPC-specific libraries. * Strong knowledge of hardware security ...

Braintrust

Application Security Engineer

New York, NY · On-site

$64.25 - $86/hr

You'll review code, build threat models, ship paved-road libraries, and lead AI-specific security ... Strong code reading and writing skills in at least two of TypeScript/Node.js, Python, Go, or Rust

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What is the difference between Rust Library vs Rust Developer?

AspectRust LibraryRust Developer
Required CredentialsKnowledge of Rust programming, library development experienceProficiency in Rust, software development skills, possibly a degree in computer science
Work EnvironmentTypically works on creating, maintaining, or documenting Rust librariesDevelops software applications using Rust, may work on libraries as part of projects
Employer & Industry UsageOpen-source projects, tech companies, software firmsTech companies, startups, software development firms
Search & Comparison IntentLooking for roles related to creating or maintaining Rust librariesSeeking software development roles involving Rust programming

In summary, a Rust Library focuses on developing and maintaining reusable code components in Rust, often within open-source or collaborative projects. A Rust Developer, however, is a broader role involving designing, coding, and deploying software applications using Rust, which may include working with or creating libraries as part of their responsibilities.

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Rust Library jobs near you

Rust AI Platform Engineer Director

Resource Consultings Services Inc

New York, NY • On-site

Full-time

Posted 14 days ago

Job description

Role: Rust AI Platform Engineer Director

Duration: Full Time

Location: New York, NY – Hybrid (4 days a week onsite)

 

Top Skills:

Rust, k8's, cloud infra, CI/CD tools, API and Microservices design/dev

Requirements: 

  • B.S./M.S. degree in Computer Science, Engineering, or a related subject area. 
  • 10+ years of experience in software and platform engineering. 
  • Proficiency in designing and building scalable APIs and microservices. 
  • Strong proficiency in Kubernetes, including Helm charts, Kustomize, and custom resource definitions (CRDs). 
  • Hands-on experience with cloud platforms such as AWS, GCP, or Azure. 
  • Expertise in containerization technologies (Docker, containerd). 
  • Experience in CI/CD tools (Jenkins, GitHub Actions, ArgoCD). 
  • Knowledge of infrastructure such as code (IaC) tools like Terraform or CloudFormation. 
  • Solid understanding of networking concepts, security policies, and API gateways in cloud environments. 
  • Proficiency in production-grade programming languages such as Rust and C++. 
  • Decent understanding of distributed systems, cluster orchestration and management. 
  • Good knowledge of data science tools (e.g PyTorch, Jax, Numpy) and programming languages such as Python. 
  • Experience with monitoring tools (Prometheus, Grafana). 
  • Experience working in Agile development teams with excellent collaboration skills. 
  • Grit in the face of technical obstacles. 

Nice to have: 

  • Building SDKs or client libraries to support API consumption. 
  • Knowledge of distributed data processing frameworks (Spark, Dask). 
  • Understanding of GPU orchestration and optimization in Kubernetes. 
  • Familiarity with MLOps and ML model lifecycle pipelines. 
  • Experience with AI model training and fine-tuning. 
  • Familiarity with event-driven architecture and messaging frameworks like Kafka. 
  • Experience with NoSQL datastores like Cassandra.