Referso Jobs

Lead and execute the direct sales strategy for your segment, focused on acquiring, growing, and retaining customers across startups, SaaS, generative AI, Web3, and other digital-native verticals.
Own pipeline and revenue attainment for your team, from lead to close.
Coach and support the team on negotiations, deal structuring, and closing key accounts.
Enable the team to articulate the value of DigitalOcean’s platform, including Droplets, Kubernetes, App Platform, and GPU offerings.
Build relationships with key customers, prospects, and ecosystem influencers.

Skills

technical sales business development cloud infrastructure SaaS AI/ML sales leadership

Technical Support Engineer - APAC

Hyperbolic Labs · Posted Nov 6, 2026

Open

Remote
Remote

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Technical Support Engineer responsible for first‑line GPU cluster issue resolution across APAC, owning tickets end‑to‑end and ensuring SLA compliance.

Responsibilities

Own customer tickets from first response to resolution
Manage SLA clock and severity classification
Reproduce issues, gather logs, and determine fault source
Provide remote access and configuration support (SSH, NFS, security groups)
Execute and author runbooks

Requirements

Nice to have: Zendesk
Nice to have: Linear
Nice to have: PagerDuty
Nice to have: Slurm
Nice to have: Kubernetes

Skills

Linux CLI SSH NFS DNS firewalls security groups GPU workloads nvidia-smi

Backend Software Engineer (ML Infra)

Rockstar · Posted Nov 4, 2026

Open

San Francisco, California, United States
On-site
Entry
1–3 years

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Design, build, and scale core systems for large-scale ML workloads, including distributed training, inference, and logging pipelines, while collaborating with ML scientists and customers.

Responsibilities

Design and implement systems that support large-scale ML workloads, including fine-tuning and reinforcement learning.
Build distributed training, inference, and logging pipelines that are efficient, fault-tolerant, and observable.
Work on cloud-native systems using containers and orchestration such as Kubernetes.
Optimize systems for performance, reliability, and cost efficiency, especially for GPU-heavy workloads.
Implement monitoring, logging, and observability for long-running training jobs and production services.

Skills

distributed systems networking backend architecture cloud-native infrastructure containers Kubernetes GPU workloads

Platform Engineer, AI Infrastructure

Focused · Posted Nov 3, 2026

Open

Chicago, Illinois, United States
On-site
Full-time
$145K–$175K per year
5+ years

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Build and operate an enterprise AI platform on Kubernetes and cloud, deploying LLM workloads and supporting AI/ML services.

Compensation

The Chicago base salary range for this role is $145,000 - $175,000.

Responsibilities

Build and operate Kubernetes clusters on Azure AKS and GCP GKE
Write and maintain Terraform modules for cloud resources and environments
Build CI/CD and GitOps pipelines for platform and application deployments
Monitor, troubleshoot, and improve the reliability of AI/ML platform services
Deploy and operate supporting services for LLM applications: model gateways, vector databases, tracing, and evaluation

Requirements

Nice to have: LangChain
Nice to have: LangGraph
Nice to have: LlamaIndex
Nice to have: Azure OpenAI
Nice to have: Vertex AI

Skills

Kubernetes Azure AKS GCP GKE Terraform CI/CD GitOps

AI Software Engineer (TS/SCI)

Vantor · Posted Nov 3, 2026

Open

Herndon, Virginia, United States
On-site
Senior
$140K–$200K per year
8+ years

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Senior AI/ML Software Engineer integrating secure chatbot and AI assistant capabilities into geospatial intelligence tools.

Compensation

$140,000.00 - $200,000.00

Responsibilities

Integrate AI chatbots and assistants into existing geospatial, analytics, visualization, and mission applications.
Build natural-language workflows for data discovery, application navigation, visualization generation, and approved actions.
Implement LLM patterns such as prompt orchestration, retrieval-augmented generation, tool calling, and conversation context.
Connect AI services to REST APIs, data catalogs, search platforms, knowledge graphs, geospatial services, notebooks, and dashboards.
Develop reusable backend services and frontend components that make AI assistance simple for analysts to use.

Requirements

Bachelor's degree in computer science, software engineering, data science, artificial intelligence, or a related field
Nice to have: React
Nice to have: AI orchestration frameworks
Nice to have: MCP-compatible services
Nice to have: agent-to-tool integration

Skills

Python JavaScript

Platform Engineer - Self Hosting LLMs built with GO

PhysicsX · Posted Nov 3, 2026

Open

London

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Build and maintain the LLM access layer for the PhysicsX platform, enabling self-hosted and external model serving, routing, and observability.

Responsibilities

Build self-hosted serving and model routing for air-gapped deployments
Own LLM packaging, registration, deployment, health checks, upgrades, rollback and retirement
Evaluate and integrate serving platforms such as KServe
Define service levels for availability, quality, and performance metrics
Measure and improve throughput, GPU utilisation, memory use and cost per token

Requirements

Nice to have: contributions to KServe
Nice to have: contributions to vLLM
Nice to have: contributions to SGLang
Nice to have: modifying engine internals
Nice to have: profiling kernels

Skills

vLLM SGLang KServe Python Go Rust C++

Solutions Architect, NPN

NVIDIA · Posted Nov 2, 2026

Open

Remote, Canada
Remote
Full-time
CA$135K–CA$220K per year
5+ years

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Design, build, and maintain large‑scale HPC and AI hybrid computing solutions for NVIDIA Partner Network customers.

Compensation

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 135,000 CAD – 185,000 CAD for Level 3; and 170,000 CAD – 220,000 CAD for Level 4.

Responsibilities

Guide partners in adopting end‑to‑end Agentic AI solutions
Deliver demos, proof‑of‑concepts, and developer blogs
Collaborate with executives and engineering to solve complex problems
Help deploy and operationalize AI solutions at scale

Requirements

BS, MS, or PhD in Engineering, Computer Science, or a related field (or equivalent experience)
Nice to have: Channel sales knowledge
Nice to have: Partner co‑selling experience
Nice to have: Open Source contributions involving GPU workloads

Skills

Docker Containers Slurm Kubernetes Ansible Python C/C++

Senior Lead Software Engineer - AI/ML Deep Learning & GPU ML Serving

Senior Lead Software Engineer - AI/ML Deep Learning & GPU ML Serving

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Director, Sales

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Technical Support Engineer - APAC

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Backend Software Engineer (ML Infra)

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Platform Engineer, AI Infrastructure

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AI Software Engineer (TS/SCI)

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Platform Engineer - Self Hosting LLMs built with GO

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Solutions Architect, NPN

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GPU workloads jobs

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