Slurm Experts in Germany
in minutes with vetted specialists and AI matchingHire experts who tune Slurm queues, job arrays, GPU scheduling, and cluster policies for HPC and research systems. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Germany, who have recently used Slurm
Amr Amer
Last position:
Machine Learning Engineer at German Research Center for Artificial Intelligence (DFKI)
- Developed end-to-end reproducible ML pipelines (PyTorch) with data versioning (DVC), experiment tracking (MLflow), automated testing (PyTest), and CI/CD across all training workflows.
- Scaled Vision Transformer and CNN training across NVIDIA A100 GPU clusters (CUDA, DDP, SLURM); applied hyperparameter optimization (W&B Sweeps) to reduce training overhead and identify optimal configurations.
- Developed a real-time 3D human motion generation system (ViT, VQ-VAE, SMPL-X/PIXIE) for personality-conditioned avatar synthesis; achieved state-of-the-art FID = 6.15 and P-FID = 10.31 on the UDIVA benchmark.
- Validated model expressiveness through structured user studies, achieving 86% accuracy in distinguishing extroverted vs. introverted avatar behaviors.
- Optimized inference pipelines by deploying PyTorch models via TensorRT and ONNX Runtime into native C++ code; benchmarked performance.
Ebenezer Ntiriakwa
Last position:
Applied Data Science & AI Bootcamp
- Prototyped LLM/RAG document assistant; trained transcriptomics and proteomic data; used Git/Docker for reproducibility.
- Strengthened ML fundamentals applicable to omics (feature engineering, validation, leakage control).
Noushiq Mohammed K A N
Last position:
Projects at Institute for Intelligent Systems
- Evaluation and analysis of camera-based traffic light and sign recognition system on various LLM-based autonomous driving systems (LMDrive, BEVDriver)
- Implemented VLM based traffic notice instruction generation unit for closed-loop autonomous driving system which alerts driver in unforeseen driving incidents
- Developed independent LLM-based local chatbot with Llama, DeepSeek and Qwen including MLflow evaluation framework
Yasaman Najafi Jozani
Last position:
Research Data Scientist at RWTH Aachen University
- Led large-scale data analysis on high-volume event data, applying statistical modeling and time-series methods to detect weak signals in noisy environments
- Designed and maintained scalable Python data pipelines for real and simulated datasets, optimizing signal detection and background estimation at scale
- Applied advanced statistical inference techniques (likelihood-based modeling, hypothesis testing) to support quantitative decision-making
- Deployed data-processing workflows on HPC clusters using Slurm, enabling parallelized analysis and large-scale batch execution
- Built reproducible, version-controlled data workflows using Python, Bash, and Git to ensure reliability and traceability of results
- Translated complex experimental data into actionable insights, enabling quantitative decision-making
Evangelia Charvati
Last position:
Postdoctoral Researcher & Data Steward at Technical University Darmstadt (Müller-Plathe group)
- Developed and applied a symbolic regression scheme to explore and model complex relationships in liquid viscosities across their phase space, providing predictive insights into material properties.
- Contributed to the improvement of hybrid Particle-Field models through data-driven diagnostics and model enhancement strategies.
- Lead interdisciplinary collaboration with experimental physicists for the investigation of the molecular mechanisms behind water-based inks.
- Managed research data workflows to ensure public accessibility and institutional archiving of simulation data, code scripts, and inputs, directly supporting research transparency and reproducibility.
Talha Tariq
Last position:
API Development for Advanced CDS Analytics at Academic Project
- Developed APIs for advanced credit default swap analytics supporting both MongoDB and file-based workflows
Nhu Loc Thuy Tran
Last position:
Ph.D. Researcher in Quantitative Genetics & Computational Biology at University of Cologne (CEPLAS – Cluster of Excellence in Plant Sciences)
- Generated and analysed large-scale RNA-seq data (>800 samples) using R, Python, and high-performance computing (HPC/Linux) systems.
- Integrated multi-omics data (genomic, transcriptomic, and phenotypic); applied Bayesian approaches and machine learning to study gene expression variation and inheritance of complex traits.
- Mentored B.Sc. and M.Sc. students in experimental design, programming in R/Python/Bash, biostatistics, data visualisation and scientific presentations.
Emre Ates
Last position:
Development of a software solution for archiving and a GenAI-based Q&A tool
- Banking industry
- Configuration and setup of a Google Cloud project with the Vertex AI API, Vertex AI Matching Engine, and Google Cloud Storage
- Development of Python services for ingesting and analyzing data in various formats using the Q&A API
- Containerization of components and implementation of Kubernetes configurations
- Development of a .NET service and a React frontend for data-driven capture with dynamic process steps
- Refactoring and functional extension of existing code to meet new requirements in ingestion and reconciliation
- Technologies: .NET Core, Moq, C#, PostgreSQL, Entity Framework, Avro, Python, Flask, Flask unittest, Pip, LangChain, RabbitMQ, REST, Jupyter, Docker, GitHub, kubectl, Google Vertex AI, Google Vertex AI Matching Engine, BigQuery, Google Gemini, React, Bootstrap, Vite, Vitest, npm
Subodh Khanger
Last position:
Student Assistant at University of Indore
- Collaborated on a pivotal project involving Quasi-Monte Carlo (QMC) methods for Bayesian optimization in PDEs, contributing to the implementation and focusing on uncertainty quantification.
- Addressed Bayesian inverse problems governed by PDEs, conducting detailed analysis for double integration problems using two approaches: a full tensor product and a sparse tensor product.
- Improved computational efficiency by developing and optimizing QMC-based algorithms, resulting in significant enhancements in the robustness of uncertainty quantification processes.
- Conducted extensive optimization and validation of algorithms, leading to more reliable and precise predictions in PDE models.
Discover over 15,000 top freelancers
Statistics of experts using Slurm
Aggregated from the professional profiles of matched freelancers.
Experience
9 years
Position duration
2.3 years
Positions per freelancer
7
Top business areas
Research and Development, Information Technology, Product Development
Top industries
Education, Agriculture, Aerospace and Defense
Certification focus areas
Research and Development, Business Intelligence, Information Technology
Bachelor's degree or higher
100%
Master's degree or higher
100%
Doctorate
38%
Certifications per freelancer
1
Most common languages
German, English, Arabic
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Germany using Slurm
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Cluster scheduling
Slurm is a workload manager for Linux clusters. It decides where jobs run, how resources are shared, and when workloads start. Companies use it for HPC, batch processing, simulations, and research systems that need stable queue control.
What specialists deliver
- Queue and partition design
- Job arrays and dependency flows
- GPU and multi-node scheduling
- Fairshare, limits, and accounting
- Slurmctld and slurmd setup
Strong specialists understand how Slurm fits into MPI, storage, and network design. They also know how to keep batch throughput high without blocking urgent work.
Common ecosystem
Slurm often sits beside MPI, Prolog and Epilog scripts, cgroups, LDAP, and monitoring tools. In many environments it also works with containers, shared filesystems, and identity systems. A good setup keeps submission simple while making node use predictable.
When companies bring help
Companies usually look for outside expertise when cluster growth starts causing long queues, idle nodes, or job failures. That often happens during platform changes, new GPU rollout, or a move to a mixed on-site and remote support model in Germany.
What strong experts do
A strong Slurm specialist reads logs, traces scheduler behavior, and knows how to explain tradeoffs in plain language. They can tune priority rules, diagnose node issues, and document operating steps for research teams and IT staff.
Where it fits
Slurm is common in universities, labs, engineering groups, and compute-heavy product teams. It is also used for genomics, physics, rendering, and large simulation jobs. The best specialists think about both user experience and cluster stability.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Slurm.
Slurm is used to submit, schedule, and control batch jobs across Linux compute nodes. It is a standard choice for HPC workloads, simulation runs, GPU jobs, and research pipelines that need predictable access to shared hardware.
Yes. Slurm is commonly called Slurm Workload Manager, and the older full name is Simple Linux Utility for Resource Management. In practice, people use the short name far more often.
Slurm is built for batch scheduling and cluster fairness, while Kubernetes is built around services, containers, and orchestration. If your core need is queued compute on CPUs or GPUs, Slurm is usually the better fit. If you need long-running application services, Kubernetes may fit better.
A good Slurm specialist often brings Linux admin skills, shell scripting, MPI knowledge, and familiarity with storage and network performance. Experience with cgroups, LDAP, monitoring, and GPU nodes is also valuable in real cluster work.
A Slurm freelancer can start with the scheduler config, node layout, and the main pain points. The more useful detail you share, the faster they can tune priorities, troubleshoot queues, or redesign partitions. For larger environments, access to logs and job patterns helps a lot.
Yes. Slurm can be supported remotely if the team can share cluster access, logs, and change windows. In Germany, many companies combine local IT ownership with remote specialist help for tuning, upgrades, and incident analysis.
If Slurm queues are growing, nodes sit idle, or jobs fail without a clear reason, it is time to bring in help. Other signs are messy partition rules, unclear accounting, GPU contention, or users bypassing the scheduler to get work done.
Look for someone who can explain Slurm decisions clearly and show how they would verify the change after rollout. Strong experts talk about scheduler policy, node health, job traces, and rollback plans, not just config files.
The average hourly rate of freelancers in Germany who have used Slurm in their recent projects is 60 €, which corresponds to a daily rate of about 477 € based on an 8-hour working day.
Of the freelancers in Germany who have used Slurm in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 38% hold a doctorate.
On average, freelancers in Germany who have used Slurm in their recent projects have 9 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Germany who have used Slurm in their recent projects are German (100%), English (100%), and Arabic (22%).
The most common industries among freelancers in Germany who have used Slurm in their recent projects are Education (89%), Agriculture (33%), and Aerospace and Defense (22%).
The most common business areas among freelancers in Germany who have used Slurm in their recent projects are Research and Development (100%), Information Technology (44%), and Product Development (44%).
Main locations of FRATCH Experts, who have recently used Slurm
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
