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Requirements:
2+ years of experience working in a production data center environment.
Experience supporting GPU-based servers or high-performance computing (HPC) environments - advantage.
Familiarity with GPU technologies, hardware architectures, and accelerated computing platforms - advantage.
Willingness to travel abroad 4-5 times a year for maintenance work during weekends.
Excellent analytical and problem-solving skills with strong attention to detail.
Fluent written and spoken English at a professional level.
Good Linux knowledge for troubleshooting server and hardware-related issues.
Hands-on experience with IT infrastructure hardware support (e.g., servers, HDDs/SSDs, hardware replacement, etc.).
Experience with DC monitoring and infrastructure management tools - advantage.
Comfortable working in hands-on environments, including lifting and racking equipment.

Requirements:
What should you have:
B.Sc. or Engineering degree.
At least 3 years of experience as a Systems Engineer for multidisciplinary development - a must.
Experience from a printing or capital equipment company - an advantage.
Master's in systems engineering - an advantage.
Background of physical modeling - an advantage.
Experience in building systems architecture - an advantage.
Experience in motion control systems - an advantage.
Knowledge of statistical tools - an advantage.
Experience in team lead - an advantage.
Proven experience applying advanced AI capabilities in systems engineering practices- an advantage.
Familiarity with defining, evaluating, and integrating AI/ML solutions into complex, multidisciplinary systems-including translating operational requirements into practical use cases and architectures, working with LLMs (fine-tuning, RAG, model evaluation), and deploying/maintaining on-premises or private-cloud AI infrastructure (open-source LLMs, GPU environments, MLOps, and model lifecycle management)- an advantage.


Personal Skills:
Self-motivated, creative, and innovative.
Team player with Excellent communication skills.
High learning and development ability, wide systemic vision, ability to work Independently with a can-do attitude.
Able to work effectively as a part of a team in a multi-disciplinary environment and interact effectively with people with a variety of expertise.
Demonstrated ability to plan and organize assignments according to planned schedules.

Requirements:
5+ Years of experience developing backend systems and/or services, in Python or Rust, with a strong preference to distributed systems and database-backed applications and services
Familiarity with cloud deployment schemes, especially with Kubernetes (AWS/EKS background a plus)
Familiarity with front-end tools and techniques - Advantage

Requirements:
Bachelor degree or higher in Computer Engineering / Computer Science or equivalent
5+ years of experience in software development in Linux environment
5+ years of experience in storage / memory tiering / caching or prefetching domains
5+ years of hands-on experience in Linux kernel development / hacking / research
Proficiency in C / C++ programming language
Proven experience in Linux kernel memory management sub-system
Working in Linux kernel open-source environment
Deep system understanding and capability to enhance existing code
Open-minded team player with a can-do attitude
Fast learner, highly organized and detail-oriented, able to work on multiple deadlines in a fast-paced atmosphere
Ways to stand out from the crowd:
M.Sc. or Ph.D. degree with expertise in fields related to OS and virtualization technology
Papers and/or proven innovation in virtualization, storage/memory tiering or caching domains
2+ years of experience in optimizing applications performance
Proficiency in additional low-level programming languages
Proficiency in high-level programming languages: Python
Familiarity with Agentic-AI workloads, their characteristics and bottlenecks

Requirements:
Experience

Strong hands-on experience with REST APIs and system integrations.

Proven experience in AI/ML or software engineering with a focus on integrations and automation.

Experience building AI agents or automated workflows.

Experience with AI development frameworks and LLM-based applications.

Practical experience with RAG architecture and vector databases.

1-3 years of relevant experience.


Skills

Strong programming skills (Python preferred).

Ability to work across both technical and business domains.


Preferred Qualifications

Experience with business application and integration development.

Familiarity with Microsoft Azure (Azure AI Search, Microsoft Foundry, Logic Apps, etc.).

Understanding of business processes and enterprise systems.

Experience with workflow orchestration tools or automation platforms.

Requirements:
BSc / MSc/ PhD in Electrical engineering from a leading institute.
5+ years pf experience in Physical Design (back-end) digital implementation: floor planning, place and route, clockTree, STA
Experience in the Synthesis, Formal verification and DFT is an advantage.
Experience in microelectronics/ EDA industry.
High level of English.
Strong presentation and communication skills.

Requirements:
7+ years building production backend systems, including at least 2 years owning a distributed/async runtime (workflow engine, task queue, event-driven system, stream processor - Temporal.io, Celery, Kafka Streams, AWS Step Functions, or equivalent).
Deep hands-on Python (the player and workflow runtime are Python), plus working JavaScript.
Production scale experience and mindset. You've operated systems where throughput, tail latency, and blast radius are first-class design constraints, not afterthoughts.
Production experience operating self-hosted infrastructure on Kubernetes (EKS preferred). Comfortable reading helm charts, debugging pod resource issues, and reasoning about autoscaling.
Comfortable with CI/CD pipelines, infra-as-code, and being on-call for systems you ship.
AI fluency on both sides of the product. You use Claude Code or an equivalent agentic coding tool for real SDLC work (design docs, refactors, on-call triage) and have shipped LLM-backed features in production - agentic workflows, retrieval, tool-use, structured output, with an eval loop and a real opinion on latency, cost, and safety.
Strongly preferred (any one of these moves you up the stack):

Direct experience with Temporal.io in production - workflow versioning, replayer-based regression detection, signal/query/update patterns, codec authoring, per-namespace operational concerns.
Strong grasp of distributed-systems failure modes: idempotency, retries, timeouts, partial failures, non-determinism, exactly-once vs at-least-once semantics. You can debug a "stuck workflow" without a runbook.
Performance optimization in Python at the deserialization/interpreter / JIT layer (cython, mypyc, alternative JS engines, profiling tooling).
Operating modern self-hosted infrastructure at scale. Hands-on with multi-cluster EKS, a metrics + logs stack (Prometheus / Grafana / centralized log aggregation), IaC, and GitOps workflows. You've owned the dashboards and alerts you're on-call against - not just consumed someone else's.

Requirements:
At least 5 years of hands-on experience with networking and routing protocols such as, TCP/IP, UDP, Multicast, OSPF, BGP, etc.
Expert knowledge in the operation of Ethernet LAN switching protocols and standards
Deep Understanding of Next Generation Firewall deployments
Understanding of Zero Trust technologies
Understanding and experience with NetOps tools and Best Practices.
Familiarity with IaaC and GitOps deployment methods
Experience in planning and designing projects and analyzing existing network systems and procedures for efficiency and effectiveness
Ability to analyze network packet traces
Excellent communication skills and team player.
Advantage:
Experience with AWS Network Services and Topologies
Experience with Network observability systems.
Knowledge with InfiniBand/High performance networks deployment.
CCNP, JNCIS/P - preferred

Requirements:
At least 10 years of hands-on experience in system architecture design, or equivalent research experience
Demonstrated experience in leading R&D team
Familiarity with high-performance computing cluster services and system architectures, such as AI, HPC and big data.
In-depth understanding of computer networks, communication libraries, and design of AI or HPC cluster networks
Key qualifications you hold include:
Ability to work in a team environment; actively seek out resolution to issues with the team and work co-operatively to build a coherent system; Team-working and excellent inter-personal communication skills.
High level of self-reliance and an autonomous target-oriented work style, can do attitude, eager to learn new things and ready to think outside the box
Ability to work on a schedule, even for un-schedule-able issues such as inventiveness
Experience with network system of AI, HPC or big data cluster
Demonstrated capability in several items from the list below:
o Deep understanding of computer network protocol and network topology of computing cluster
o Familiarity with communication library, such as OpenMPI/NCCL
o Extensive experience in leading the network architecture design of computing cluster
o Experience with implementing routing algorithm
o Familiarity with network specifications of CPU/Network Processing Unit/ Neural Processing Unit/Switch chip
Fluent in written and spoken English

Requirements:
B.Sc. in Computer Engineering or Computer Science (preferably cum laude, from a leading university)
5+ years of experience as a software engineer
Result oriented and experience in working on complex and large-scale systems
Passionate about code, self-motivated, fast learner, can do attitude and a great team player
Experience in working with Rust is a great advantage

Requirements:
B.Sc. with honors in CS/EE/Math/Physics, or a related field from a top-tier university
5+ years of hands-on experience building and deploying large-scale deep learning systems in production
Preferred Qualifications :
M.Sc. or Ph.D. in a relevant quantitative field - Advantage
Proficiency in Python/C/C++
Deep, working knowledge of PyTorch internals
Strong experience in several of the following areas:
Performance profiling and optimization of deep learning workloads
Orchestrating and optimizing large-scale distributed training (hundreds to thousands of GPUs)
Optimizing model serving and inference pipelines (quantization, distillation, compilation, memory optimization, etc.)
Training and scaling state-of-the-art vision, language, or diffusion models
Implementing custom CUDA/Triton kernels

Requirements:
B.Sc. or higher in Electrical Engineering, Computer Science, or related discipline
10+ years of experience in VLSI/processor architecture (exceptional candidates with less experience will be considered)
Strong hands-on experience with SystemC modeling
Solid background in AI workloads and AI hardware architecture
Experience in HW/SW co-design and architectural trade-off analysis
Ability to operate at high levels of abstraction and drive architectural decisions from simulation data

Requirements:
10-year experience in power-management architecture.
Experience in technical leading of cross disciplines (or HW-SW) development
Lead systemic changes across the organization
CPU core micro architecture knowledge is an advantage
Co-operate and communicate well with the architecture team and other members of development team
Interact with the Product System architects, software teams and ASIC chip teams to define the overall architecture of the power-management solution

Requirements:
Masters or PhD in Computer Science, Physics, EE, Mathematics, Statistics, or a related field.
5+ Years of experience of ML research/Deep Learning etc.
Experience with software engineering in Python (must) , C++/Rust is a plus.
Strong statistical analysis and mathematical skill.
A great team player eager to share/learn/teach other team members.
Creative, self-motivated, love complex problems, determined.