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What you’ll be doing:
Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding,data/tensor/expert/pipeline-parallelism,prefill-decode disaggregation.
Develop, optimize, and benchmark GPU kernels (hand-tuned and compiler-generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high-level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization.
Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry-leading MLPerf Inference benchmarking suite.
Architect the scheduling and orchestration of containerized large-scale inference deployments on GPU clusters across clouds.
Conduct and publish original research that pushes the pareto frontier for the field of ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into NVIDIA’s software products.
What we need to see:
Bachelor’s degree (or equivalent expeience) in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE) with 7+ years of experience; alternatively, Master’s degree in CS/CE/SE with 5+ years of experience; or PhD degree with the thesis and top-tier publications in ML Systems, GPU architecture, or high-performance computing.
Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories.
Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang).
Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).
Experience with containers and orchestration (Docker, Kubernetes, Slurm); familiarity with Linux namespaces and cgroups.
Excellent debugging, problem-solving, and communication skills; ability to excel in a fast-paced, multi-functional setting.
Ways to stand out from the crowd
Experience building and optimizing LLM inference engines (e.g., vLLM, SGLang).
Hands-on work with ML compilers and DSLs (e.g., Triton,TorchDynamo/Inductor,MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores).
Experience contributing tocontainerization/virtualizationtechnologies such ascontainerd/CRI-O/CRIU.
Experience with cloud platforms (AWS/GCP/Azure), infrastructure as code, CI/CD, and production observability.
Contributions to open-source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts.
You will also be eligible for equity and .
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Opis stanowiska:
Poszukujemy Stażysty ds. Wsparcia Administracyjnego, który dołączy do naszych zespołów Payroll oraz Global Business Services (GBS), wspierając działania w krajach regionu EMEA. To idealna rola dla osoby, która lubi pracować z danymi, systemami i różnymi działami, zapewniając płynność procesów biznesowych. Będziesz zajmować się koordynacją informacji, dbaniem o spójność danych oraz wspieraniem narzędzi cyfrowych usprawniających pracę organizacji.
Twoje obowiązki:
· Wsparcie działań GBS i Payroll w zadaniach administracyjnych w regionie EMEA.
· Utrzymywanie i aktualizacja treści wewnętrznych (np. FAQ) na portalu firmowym.
· Przygotowywanie i dostarczanie raportów zespołom wewnętrznym i interesariuszom.
· Organizowanie i uzgadnianie danych na potrzeby raportowania i operacji.
· Weryfikacja i kontrola danych pracowników w systemach.
· Wsparcie testów i dokumentacji w ramach inicjatyw automatyzacji procesów.
Szukamy osoby, która:
· Jest w trakcie studiów licencjackich lub ukończyła kierunek administracja, języki lub pokrewne.
· Biegle posługuje się językiem angielskim i niemieckim (min. B2+). Znajomość innych języków będzie atutem.
· Posiada silne umiejętności organizacyjne i administracyjne.
· Dobrze zna pakiet Microsoft Office i szybko uczy się nowych systemów.
· Jest skrupulatna, analityczna i potrafi rozwiązywać problemy.
· Potrafi pracować samodzielnie oraz w zróżnicowanym, międzynarodowym środowisku.
· Dobrze zarządza czasem i priorytetami.
Oferujemy:
· Umowę stażową do 12 miesięcy, elastyczne godziny (30–40 godz./tyg.).
· Model hybrydowy (3 dni w biurze).
· Międzynarodowe środowisko pracy i wspierających współpracowników.
· Możliwość rozwoju umiejętności administracyjnych i koordynacyjnych w globalnej organizacji.
· Nowoczesne biuro w centrum Warszawy.
Lokalizacja: Warszawa (Hybrydowo)
Start: Grudzień/Styczeń 2025
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About the role:
We are seeking an experienced and strategicto lead and scale our North American technical support organization. This is a critical role that requires a blend of people management, operational excellence, and forward-thinking program management.
What you’ll be doing:
What you’ll need:
Trust is backed by data – Forter is a recipient of over 10 workplace and innovation awards, including:
Benefits:
Salary Range:+ bonus + equity + benefits
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This role can be based out of our Toronto office or remotely in the Ontario region.
Our ideal candidate will haveThese jobs might be a good fit

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As our nextProduct Development Engineer / Specialist,you'll beresponsible to support and lead the development and manufacturing implementation of new Powder Metal components and products.
Why You’ll Love Working Here:
Inclusive Workplace : An inclusive and diverse workplace where all employees are valued and respected.
Technological Leadership: Be part of a company that is a leader in its field, driving technological advancements.
Work-Life Balance: Flexible working hours and policies that support a healthy work-life balance.
Recognition Programs: Programs that recognize and reward employee achievements and contributions.
Community Engagement: Opportunities to participate in community service and corporate social responsibility initiatives.
What You’ll Be Doing:
Participate and contribute in product and process Feasibility Reviews
Acquire and analyze process and product data; make recommendations based on the analysis of these results
Create and implement new procedures through verbal and written instruction to Production Staff
Participate in the design and implementation of preventative and corrective actions
Guide other team members as appropriate and required
Develop and update Advanced Product Quality Planning documentation such as Process Flow Diagrams, Process Failure Modes and Effects Analysis, Process Control Plans, Process Sheet documents and others when required.
Verify the accuracy and approve product documents as required
Work with Production and Quality to aid in the troubleshooting of production parts and processes; providing support where needed
Work on multiple product lines where opportunities exist
All other duties as assigned
What We’re Looking For:
Technician or Technologist in a Metallurgical, Materials or Mechanical discipline
C.E.T. designation eligibility considered an asset
Must be an individual with a practical hands-on approach and strong organizational skills
Demonstrated experience working in a fast-paced manufacturing environment such as Automotive
Demonstrated experience in establishing and working with timelines to achieve objectives
Strong Computer Literacy. Good knowledge of MS Excel and similar Microsoft products
Working knowledge in the use of AutoCad
Working knowledge of basic statistical methods for data analysis and comparisons
Basic ability to read technical drawings
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What you’ll be doing:
Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding,data/tensor/expert/pipeline-parallelism,prefill-decode disaggregation.
Develop, optimize, and benchmark GPU kernels (hand-tuned and compiler-generated) using techniques such as fusion, autotuning, and memory/layout optimization; build and extend high-level DSLs and compiler infrastructure to boost kernel developer productivity while approaching peak hardware utilization.
Define and build inference benchmarking methodologies and tools; contribute both new benchmark and NVIDIA’s submissions to the industry-leading MLPerf Inference benchmarking suite.
Architect the scheduling and orchestration of containerized large-scale inference deployments on GPU clusters across clouds.
Conduct and publish original research that pushes the pareto frontier for the field of ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into NVIDIA’s software products.
What we need to see:
Bachelor’s degree (or equivalent expeience) in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE) with 7+ years of experience; alternatively, Master’s degree in CS/CE/SE with 5+ years of experience; or PhD degree with the thesis and top-tier publications in ML Systems, GPU architecture, or high-performance computing.
Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories.
Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang).
Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).
Experience with containers and orchestration (Docker, Kubernetes, Slurm); familiarity with Linux namespaces and cgroups.
Excellent debugging, problem-solving, and communication skills; ability to excel in a fast-paced, multi-functional setting.
Ways to stand out from the crowd
Experience building and optimizing LLM inference engines (e.g., vLLM, SGLang).
Hands-on work with ML compilers and DSLs (e.g., Triton,TorchDynamo/Inductor,MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores).
Experience contributing tocontainerization/virtualizationtechnologies such ascontainerd/CRI-O/CRIU.
Experience with cloud platforms (AWS/GCP/Azure), infrastructure as code, CI/CD, and production observability.
Contributions to open-source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts.
You will also be eligible for equity and .
These jobs might be a good fit