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Intern Distributed Systems Engineer Jobs in New York

Yext

Systems Engineer

Manhattan, NY · On-site

... distributed systems and networks. • Possesses an automation-first mindset when developing and testing infrastructure. • Strong interest in Platform Engineering, applying a customer and product ...

AVTC Group

Mechanical Systems Engineer

Bridgewater, NJ · On-site +1

Mechanical Systems Engineer * Plant design, preparation of process and instrument drawings (P&ID ... piping and distribution systems. * Prepare preliminary and detailed design documents for the ...

CoreWeave

Systems Engineer, Kernel

Livingston, NJ · On-site

$165K - $242K/yr

Experience in HPC or large-scale distributed systems. * Familiarity with QA/QE best practices * Experience working in Cloud environments * Experience as a software engineer writing large-scale ...

CoreWeave

Systems Engineer, Kernel

New York, NY

$165K - $242K/yr

Experience in HPC or large-scale distributed systems. * Familiarity with QA/QE best practices * Experience working in Cloud environments * Experience as a software engineer writing large-scale ...

Collabera

Systems Engineer

Babylon, NY

Systems Engineer Duration: 12 + Months (Could go beyond) Details: * This is a hands on technical ... and operations of large-scale, distributed applications and solutions across a global ...

Collabera

Systems Engineer

Babylon, NY · On-site

Systems Engineer Duration: 12 + Months (Very high possibility of Extension) Details: * This is a ... and operations of large-scale, distributed applications and solutions across a global ...

Yext

Systems Engineer

New York, NY · On-site

The Systems & Networking team is responsible for designing and maintaining the foundational ... Proven experience in designing, building, testing, monitoring, and automating secure distributed ...

Yext

Systems Engineer

New York, NY · On-site

$136K - $163K/yr

The Systems & Networking team is responsible for designing and maintaining the foundational ... Proven experience in designing, building, testing, monitoring, and automating secure distributed ...

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Intern Distributed Systems Engineer information

What are the key skills and qualifications needed to thrive as an Intern Distributed Systems Engineer, and why are they important?

To thrive as an Intern Distributed Systems Engineer, you typically need a strong background in computer science fundamentals, programming (often in languages like Java, C++, or Go), and an understanding of distributed computing concepts. Familiarity with technical tools such as Docker, Kubernetes, cloud platforms (AWS, GCP, Azure), and version control systems like Git is commonly expected. Strong analytical thinking, effective communication, and a willingness to learn make candidates stand out in this role. These skills and qualities are crucial for solving complex distributed problems, collaborating with teams, and adapting to rapidly evolving technology environments.

What is the difference between Intern Distributed Systems Engineer vs Intern Software Engineer?

AspectIntern Distributed Systems EngineerIntern Software Engineer
Required CredentialsTypically pursuing a degree in Computer Science or related field, familiarity with distributed systems conceptsSimilar educational background, focus on general software development skills
Work EnvironmentFocus on designing, implementing, and testing distributed systems and networked applicationsDeveloping various software applications, often in different domains
Employer & Industry UsageUsed in tech companies working on cloud, big data, or scalable systemsCommon across many industries including tech, finance, and startups
Search & Comparison IntentPeople comparing internship roles in distributed systems and software development

Intern Distributed Systems Engineers focus on distributed architectures and networked systems, while Intern Software Engineers work on a broader range of software projects. Both roles require similar educational backgrounds but differ in specific technical focus and project types.

What types of projects and tasks can an Intern Distributed Systems Engineer expect to work on, and how does this support their learning and growth?

As an Intern Distributed Systems Engineer, you can expect to work on collaborative projects involving the design, implementation, and testing of scalable, fault-tolerant systems. Your tasks may include optimizing data pipelines, contributing to microservices architecture, or participating in performance benchmarking. Interns often work closely with senior engineers, gaining exposure to cutting-edge technologies such as cloud platforms, container orchestration, and distributed databases. This hands-on experience, combined with mentorship and code reviews, provides valuable insights into best practices and industry standards, supporting both your technical and professional growth.

What does an Intern Distributed Systems Engineer do?

An Intern Distributed Systems Engineer assists in designing, developing, and maintaining large-scale distributed systems that enable applications to run reliably across multiple computers. Their work often involves writing and testing code, debugging issues, and collaborating with experienced engineers to solve technical challenges related to scalability, efficiency, and data consistency. Interns may also help with system monitoring and performance analysis, learning best practices for building robust and fault-tolerant systems. This role is a valuable opportunity to gain hands-on experience with cutting-edge technologies and real-world distributed computing problems.
What are the most commonly searched types of Distributed Systems Engineer jobs in New York? The most popular types of Distributed Systems Engineer jobs in New York are:
What are popular job titles related to Intern Distributed Systems Engineer jobs in New York? For Intern Distributed Systems Engineer jobs in New York, the most frequently searched job titles are:
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What cities in New York are hiring for Intern Distributed Systems Engineer jobs? Cities in New York with the most Intern Distributed Systems Engineer job openings:
Intern Distributed Systems Engineer jobs near you
Software Engineer - GPU Networking & Distributed Systems

Software Engineer - GPU Networking & Distributed Systems

Baseten

New York, NY • On-site

$165K - $330K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 22 days ago

Job description

ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products.
At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations.
THE OPPORTUNITY
Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed.
In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts.
WHAT YOU'LL DO
  • Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack, helping us move beyond TCP/IP to unlock order-of-magnitude improvements in bandwidth and latency.
  • Optimize Distributed Inference: You will implement and tune the networking layers necessary for efficient Disaggregated KV Cache Offload and WideEP, ensuring seamless communication across NVLink and InfiniBand for our MoE models.
  • Enable Serverless-Grade Startup Speeds for LLMs: You will work deeply with checkpointing and storage mechanisms to enable sub-10-second startup for trillion-parameter models.
  • Deep-Dive into Hardware: You will characterize and validate networking performance on bleeding-edge clusters (H100/H200, B200/B300, GB200/300 NVL72), writing the acceptance tests that ensure our hardware delivers peak achievable throughput and minimal latency.
  • Build Observability: You will design the tools that let us visualize packet flow, congestion, and effective bandwidth across the GPU interconnects, helping us diagnose complex distributed system behaviors.
  • Optimize Kernels: You will work with communication libraries (NCCL, NVSHMEM) and potentially write custom communication kernels to overlap compute and data transfer.

WHO YOU ARE
  • You have deep experience with high-performance networking protocols (InfiniBand, RoCE v2) and understand the physics of data movement.
  • You are fluent in C++ or Python, with the ability to bridge the gap between high-level logic and hardware. You have a deep understanding of the memory hierarchy in modern NVIDIA architectures (H100/Blackwell) and know how to optimize for it.
  • You like going deep. You aren't afraid to dive into TensorRT-LLM source code, write custom C++ / Python bindings, or debug NVLink topology issues.
  • You know when to use an off-the-shelf solution and when we need to build a custom solution because the upstream tools (like standard Kubernetes networking) are too slow for our needs.

HIGHLY PREFERRED:
  • Deep knowledge of NCCL, NVSHMEM, and UCX.
  • Experience with GPUDirect Storage (GDS) or high-performance filesystems like Weka or 3FS.
  • Familiarity with TensorRT-LLM, vLLM, or Sglang.
  • Experience running low-level benchmarks to "qualify" new hardware clusters.

Why join the Model Performance team?
  • Bleeding Edge Hardware: We are preparing to bring Blackwell (B200/B300) and then Rubin architectures online. You will be one of the first engineers in the industry optimizing networking for NVL72/GB300 racks.
  • We go deep: We operate at every depth. Whether it's tuning hardware interconnects, writing custom communication kernels, or designing distributed inference strategies, we work across the entire stack to deliver performance that goes far and beyond.
  • High Impact: The networking optimizations you build will directly enable features that no one else in the industry has fully mastered yet, like seamless multi-node WideEP and instant model hydration.

BENEFITS
  • Competitive compensation, including meaningful equity.
  • 100% coverage of medical, dental, and vision insurance for employee and dependents
  • Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
  • Paid parental leave
  • Fertility and family-building stipend through Carrot
  • Company-facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

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