GPU Cluster Resource Scheduling and Optimization Engineer
Company: Senior Interior Designer
Location: San Francisco
Posted on: May 8, 2025
Job Description:
GPU Cluster Resource Scheduling and Optimization EngineerAbout
UsTogether.ai is driving innovation in AI infrastructure by
creating cutting-edge systems that enable scalable and efficient
machine learning workloads. Our team tackles the unique challenges
of resource scheduling, optimization, and orchestration for
large-scale AI training and inference systems.We are looking for a
talented AI Workload Resource Scheduling and Optimization Engineer
to join our team. This role focuses on designing and implementing
advanced scheduling algorithms, resource management strategies, and
optimization techniques to maximize performance and minimize costs
for large-scale distributed AI workloads.Responsibilities
- Resource Scheduling and Allocation:
- Develop and implement intelligent scheduling algorithms
tailored for distributed AI workloads on multi-cluster and
multi-tenant environments.
- Ensure efficient allocation of GPUs, TPUs, and CPUs across
diverse workloads, balancing resource utilization and job
performance.
- Performance Optimization:
- Design optimization techniques for dynamic resource allocation,
addressing real-time variations in workload demand.
- Implement load balancing, job preemption, and task placement
strategies to maximize throughput and minimize latency.
- Scalability and Efficiency:
- Build systems that efficiently scale to thousands of nodes and
petabytes of data.
- Optimize training and inference pipelines to reduce runtime and
cost while maintaining accuracy and reliability.
- Monitoring and Analytics:
- Build tools for real-time monitoring and diagnostics of
resource utilization, job scheduling efficiency, and
bottlenecks.
- Leverage telemetry data and machine learning models for
predictive analytics and proactive optimization.
- Collaboration and Innovation:
- Collaborate with researchers, data scientists, and platform
engineers to understand workload requirements and align resource
management solutions.
- Stay updated with the latest trends in distributed systems, AI
model training, and cloud-native
technologies.QualificationsMust-Have:
- Experience:
- 5+ years of experience in resource scheduling, distributed
systems, or large-scale machine learning infrastructure.
- Technical Skills:
- Proficiency in distributed computing frameworks (e.g.,
Kubernetes, Slurm, Ray).
- Expertise in designing and implementing resource allocation
algorithms and scheduling frameworks.
- Hands-on experience with cloud platforms (e.g., AWS, GCP,
Azure) and GPU orchestration.
- Programming:
- Proficient in Python, C++, or Go for building high-performance
systems.
- Optimization Skills:
- Strong understanding of operational research techniques, such
as linear programming, graph algorithms, or evolutionary
strategies.
- Soft Skills:
- Analytical mindset with a focus on problem-solving and
performance tuning.
- Excellent collaboration and communication skills across
teams.Nice-to-Have:
- Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch,
JAX).
- Familiarity with AI-specific workloads like DDP, sharded
training, or reinforcement learning.
- Knowledge of auto-scaling and cost-optimization strategies in
cloud environments.
- Contributions to open-source scheduling or orchestration
projects.About Together AITogether AI is a research-driven
artificial intelligence company. We believe open and transparent AI
systems will drive innovation and create the best outcomes for
society, and together we are on a mission to significantly lower
the cost of modern AI systems by co-designing software, hardware,
algorithms, and models. We have contributed to leading open-source
research, models, and datasets to advance the frontier of AI, and
our team has been behind technological advancement such as
FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to
join a passionate group of researchers in our journey in building
the next generation AI infrastructure.CompensationWe offer
competitive compensation, startup equity, health insurance and
other competitive benefits. The US base salary range for this
full-time position is: $160,000 - $230,000 + equity + benefits. Our
salary ranges are determined by location, level and role.
Individual compensation will be determined by experience, skills,
and job-related knowledge.Together AI is an Equal Opportunity
Employer and is proud to offer equal employment opportunity to
everyone regardless of race, color, ancestry, religion, sex,
national origin, sexual orientation, age, citizenship, marital
status, disability, gender identity, veteran status, and more.
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Keywords: Senior Interior Designer, Redwood City , GPU Cluster Resource Scheduling and Optimization Engineer, Engineering , San Francisco, California
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