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Remote Intersystems Cache Developer Jobs in San Francisco, CA

Mercor

CUDA Engineer - Kernel Optimization

San Francisco, CA · Remote

$241K/yr

Remote Role Responsibilities * Analyze and optimize GPU kernels for performance, efficiency, and ... Use profiler metrics like L2 cache hit rate and occupancy to guide kernel improvements. * Review ...

New

Vercel

Software Engineer, CDN Content

San Francisco, CA · On-site +1

$172K - $258K/yr

... developer experience. Now, software is entering a new era, and the next generation of products will ... If you're located beyond that distance, the role is fully remote. For location-specific details ...

Vercel

Software Engineer, CDN Content

San Francisco, CA · On-site +1

$172K - $258K/yr

... cache services, and object storage across 20+ regions. As a Software Engineer on the team, you'll ... If you're located beyond that distance, the role is fully remote. For location-specific details ...

All JobsIntersystems Cache Developer JobsRemote Intersystems Cache Developer JobsRemote Intersystems Cache Developer Jobs in San Francisco, CA

Remote Intersystems Cache Developer information

See San Francisco, CA salary details

$25.9K

$116.1K

$180.3K

How much do remote intersystems cache developer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote intersystems cache developer in San Francisco, CA is $116,066.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,100.00 and $140,800.00 per year, depending on experience, location, and employer.

What is a remote Intersystems Cache developer?

Remote Intersystems Cache Developers are software professionals who specialize in designing, developing, and maintaining applications using the InterSystems Caché database platform, all while working remotely. They leverage their expertise in Caché's object-oriented and SQL database features to build high-performance, scalable solutions, often in healthcare or financial industries. These developers collaborate with teams using online tools, troubleshoot issues, and ensure the security and efficiency of database-driven applications from remote locations.

How do remote Intersystems Cache developers typically collaborate with team members across different locations?

Remote Intersystems Cache Developers frequently work with distributed teams, using collaboration tools like Slack, Microsoft Teams, or Jira to maintain communication and project tracking. Regular virtual meetings are common for discussing requirements, code reviews, and troubleshooting. Developers often interact closely with database administrators, front-end developers, and project managers to ensure seamless integration and performance optimization. Effective remote collaboration requires strong communication skills, self-motivation, and the ability to document code and processes clearly for team visibility.

What are the key skills and qualifications needed to thrive as a remote Intersystems Cache developer?

To thrive as a Remote Intersystems Cache Developer, you need strong programming skills in ObjectScript, experience with database design, and a solid understanding of healthcare data standards, typically supported by a degree in computer science or a related field. Familiarity with Intersystems Cache/IRIS, HL7 or FHIR integrations, and certifications like Intersystems Certified Developer are highly beneficial. Excellent problem-solving abilities, attention to detail, and effective remote communication skills help developers excel in distributed teams. These skills ensure robust, secure, and efficient healthcare application development and seamless collaboration in a remote work environment.

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Remote Intersystems Cache Developer jobs near you
Infographic showing various Remote Intersystems Cache Developer job openings in San Francisco, CA as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $116,066 per year, or $55.8 per hour.

Golang Developer with Devops/LLM exp

Noblesoft Technologies

San Francisco, CA • Remote

Contractor

Re-posted 14 days ago

Job description

Job Title: Golang Developer with Devops/LLM exp
Location: California (Remote)
 
Job Description:
We are looking for devs with general cloud services / distributed services experience, with LLM experience as a secondary skill. GPU experience is now low on the list of preferred skills: Dedicated Inference Service
Required Skills-
  • Deep experience building services in modern cloud environments on distributed systems (i.e., containerization (Kubernetes, Docker), infrastructure as code, CI/CD pipelines, APIs, authentication and authorization, data storage, deployment, logging, monitoring, alerting, etc.)
  • Experience working with Large Language Models (LLMs), particularly hosting them to run inference
  • Strong verbal and written communication skills. Your job will involve communicating with local and remote colleagues about technical subjects and writing detailed documentation.
  • Experience with building or using benchmarking tools for evaluating LLM inference for various models, engine, and GPU combinations.
  • Familiarity with various LLM performance metrics such as prefill throughput, decode throughput, TPOT, and TTFT
  • Experience with one or more inference engines: e.g., vLLM, SGLang, and Modular Max
  • Familiarity with one or more distributed inference serving frameworks: e.g., llm-d, NVIDIA Dynamo, and Ray Serve etc.
  • Experience with AMD and NVIDIA GPUs, using software like CUDA, ROCm, AITER, NCCL, RCCL, etc.
  • Knowledge of distributed inference optimization techniques - tensor/data parallelism, KV cache optimizations, smart routing etc.
What You'll Be Working On-
  • Develop and maintain an inference platform for serving large language models optimized for the various GPU platforms they will be run on.
  • Work on complex AI and cloud engineering projects through the entire product development lifecycle (PDLC) - ideation, product definition, experimentation, prototyping, development, testing, release, and operations.
  • Build tooling and observability to monitor system health, and build auto tuning capabilities.
  • Build benchmarking frameworks to test model serving performance to guide system and infrastructure tuning efforts.
  • Build native cross platform inference support across NVIDIA and AMD GPUs for a variety of model architectures.
  • Contribute to open source inference engines to make them perform better on DigitalOcean cloud.