About Fluidstack

At Fluidstack, we’re building the infrastructure for abundant intelligence. We partner with top AI labs, governments, and enterprises - including Mistral, Poolside, Black Forest Labs, Meta, and more - to unlock compute at the speed of light.

We’re working with urgency to make AGI a reality. As such, our team is highly motivated and committed to delivering world-class infrastructure. We treat our customers’ outcomes as our own, taking pride in the systems we build and the trust we earn. If you’re motivated by purpose, obsessed with excellence, and ready to work very hard to accelerate the future of intelligence, join us in building what's next.

About the Role

As a Member of Technical Staff at Fluidstack, you will design, develop, and maintain software solutions that power our AI infrastructure and enable our customers to run complex ML workloads efficiently at scale.

Your responsibilities are aligned with the success of our customers and your teammates, and you'll work side-by-side with them to push forward the state of the art in AI/ML. A day's work may include:

• Developing and optimizing job scheduling systems to maximize GPU utilization and throughput for ML workloads

• Building and improving software interfaces for cluster management that support PyTorch, JAX, and other ML frameworks

• Creating monitoring and observability tools for tracking training progress, resource usage, and system performance

• Implementing data pipeline optimizations to accelerate training and inference workflows

• Designing and developing APIs and services to integrate with MLflow, Kubeflow, Weights & Biases, and other ML tooling

• Writing libraries and utilities to simplify the deployment and management of distributed training jobs

Focus

We are looking for candidates who are customer-centric, with a bias to action, and an ability to thrive in ambiguity. We expect communication skills, a low ego, and a positive attitude.

In terms of skills, if any of the below bullet points sound like you, please reach out!

1. You have developed software for training or serving large-scale ML models (1000+ GPU scale)

2. You have optimized distributed training performance across multiple nodes and accelerators

3. You have implemented APIs and interfaces for ML platforms that prioritize developer experience

4. You have experience with orchestration systems like Kubernetes or SLURM in the context of large scale ML workloads

5. You have built or contributed to ML infrastructure tools (e.g., Ray, Horovod, DeepSpeed), and have experience with ML experiment tracking and workflow systems (MLflow, Kubeflow, W&B)

Interview Process

After submitting your application, the team will review your resume. If your application passes this stage, you will be invited to a 30 minute screen. If you clear this initial phone interview, you will enter the main process, which consists of three 45 minute interviews: a technical deep dive, customer communications and debugging session, and a culture fit interview.

Our goal is to finish the main process within one week. All interviews will be conducted virtually.

Salary & Benefits

• Competitive total compensation package (salary + equity).

• Retirement or pension plan, in line with local norms.

• Health, dental, and vision insurance.

• Generous PTO policy, in line with local norms.

The base salary range for this position is $150,000 - $250,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.

We are committed to pay equity and transparency.

Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.