דרושים » הנדסה » Senior Software Engineer

Requirements:
What we need to see:

MS/PhD with expertise in Computer Science, Computer Engineering, Electrical Engineering or related field with a focus on Deep Learning or Machine Learning.

5+ years of experience in deep learning and machine learning in a production environment.

Excellent Python programming skills, strong software design fundamentals, and experience leveraging coding agents in development workflows.

Hands-on experience with deep learning development frameworks and libraries (e.g. TensorFlow, PyTorch).

Experience with large scale production systems and pipelines, with a track record of developing production-grade models

Experience with agentic AI systems, agent frameworks, and evaluation of agent performance and reliability.

Strong algorithm development experience, with knowledge of inference optimization techniques such as model distillation, quantization, pruning.

Background with algorithms including zero/few-shot learning, self-supervised and unsupervised learning and generative AI models for synthetic data creation.

Experience with fine-tune / training LLM models

You are proactive, take full ownership of your deliverables, have a can-do approach, and are excited to learn, explore and apply your skills and creativity to some of the most challenging and rewarding problems in the field.


What will make you stand out from the crowd:

Strong software development experience.

Familiarity with GPU based technologies like CUDA, CuDNN and TensorRT.

Experience with tools for data processing and storage.

Security and networking background, with knowledge of security protocols, network architectures, firewalls, intrusion detection systems, and other relevant security and networking concepts.

Requirements:
What we need to see:

B.A./B.Sc. in Computer Science or equivalent experience.

5+ years of experience of networking product delivery (e.g. switches, routers, NICs) and the software development lifecycle.

Strong programming skills in Python.

Experience of creating and maintaining robust test automation systems, and a desire to automate everything.

Exceptional analytical and problem-solving skills, with a keen attention to detail, particularly in identifying and resolving networking issues.

Good English communication and interpersonal skills.

Good Linux familiarity.


Ways to stand out from the crowd:

Experience of data center network engineering spanning servers, NICs, cabling and switches.

Strong knowledge of ethernet networking, from switch pipelines (e.g. ACLs, forwarding rules) through networking protocols (like TCP/IP and BGP/EVPN-VxLAN) to network operating systems and their automation.

Have a passion for AI and networking.

Experience of NVIDIA networking technology such as Bluefield/ConnectX NICs, Spectrum switches, and the Cumulus Linux and SONiC operating systems.

Networking certification (e.g. CCIE, JNCIE, ACE-E).

Requirements:
What we need to see:

A bachelor's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

8+ years of overall relevant experience.

Proven experience with over 4 years of managing engineering teams of 4 or more members.

Outstanding leadership skills and a proven record of effectively managing complex projects.

Strong knowledge and experience in Ethernet communication, network protocols and real time software.

Experience with C/C++ programming.

Experience with Linux internals.

Strong analytical, creative, debugging, and problem-solving skills, along with a collaborative approach.


Ways to stand out from the crowd:

Python programming experience.

Excellent understanding of embedded SW and real-time programming.

Requirements:
What We Need to See:

BSc/MSc in Computer Science, Communication Engineering, Software Engineering, or equivalent experience.

12+ years of experience in R&D, architecture, and program management, with primary focus on product management leadership in Data Center Networking with proven track record in defining and driving both inbound and outbound product strategy across complex technologies and cross-functional organizations.

MBA or similar experience, with a balance of technical and business knowledge.

Deeply versed in hardware-accelerated networking protocols (RDMA, ETH, and more), technologies (DPDK, OVS, and more), and full Product-solutions in Data Center and Cloud environments.

Strong ability to deliver complex, Linux-based networking software frameworks and SDKs specifically architected for cloud providers, hyperscalers, and large-scale enterprise deployments.

Translate global customer and business insights into high-impact networking solutions, bridging the gap between deep technical requirements and long-term strategic goals.

Proven experience driving vision into reality by navigating complex, global organizational matrices, using exceptional communication to align cross-functional engineering and product teams.

Highly motivated, fast learner, and a team-player.


Ways to Stand Out from the Crowd:

Strong background in Data-Centre clusters and topologies, AI-driven networking, storage, security, and orchestration techniques.

Hands-on experience with networking infrastructure and DPU architecture, programmable networking pipelines, and NVIDIA technologies (CUDA, embedded solutions), with deep platform ecosystem knowledge

Proven leadership in complex hardware/software systems development, Including: SW, embedded SW, and HW. Supplying complete solutions: from the networking infrastructure, through SDKs and services, and into the application-level.

Success in partnering with Tier-1 customers on networking and cloud infrastructure deployments.

Extensive product management experience in international organizations, with a focus on adaptability and cross-cultural collaboration as well as vast experience as a R&D manager, or engineering program manager.

Requirements:
What we need to see:

BSc/MSc in CS/CE or related field (or equivalent experience).

At least 8 years of experience in ML engineering with a track record of deploying LLMs and agents to production at scale (including distributed environments).

Proficiency in Python and/or C++, with a deep understanding of ML/AI frameworks.

Hands-on experience with microservices, container orchestration, and cloud platforms for large-scale training and inference workloads.

Knowledge of ML training and inference optimization techniques.

Understanding of build infrastructure and CI/CD tools and practices (e.g. GitLab, GitHub Actions, Jenkins)

Experience with teaching and mentoring.

You are a proactive owner who takes pride in your work but remains humble and approachable. You believe that "how" we build is just as important as "what" we build.

Excellent collaboration skills, with the ability to explain complex infra concepts to non-technical stakeholders clearly and kindly.



Ways to stand out from the crowd:

Experience deploying and optimizing generative models and multi-agent systems for performance.

Deep systems knowledge (Linux internals, network protocols, or high-performance computing).

A background in security research, including knowledge of firewalls, intrusion detection, or network architectures.

Requirements:
What we need to see:
Bachelors or Masters Degree in Computer Science, Computer Engineering, Data Science, or a related field (or equivalent experience).
Demonstrated experience of 5+ years in AI safety/security and offensive cybersecurity.
Knowledge of AI (both model and infrastructure) vulnerabilities and effective mitigation strategies.
In-depth understanding of LLM, MLLM, Generative AI, Agents and RAG workflows.
Proven Python programming expertise
Self-starter with a passion for growth, enthusiasm for continuous learning, and sharing findings across the team
Extremely motivated, highly passionate, and curious about new technologies.

Ways to stand out from the crowd:
Hands-on experience designing and building software products, including infrastructure and system design.
Knowledge of MLOps technologies such as Docker and Kubernetes.
Familiarity with ML libraries (PyTorch, TensorRT, or TensorRT-LLM).

Requirements:
What Were Looking For

5+ years of professional software development experience

Strong, proven experience in modern C++ (C++17/20)- multi-year hands-on development in native/cross-platform environments. We expect fluency with:

Modern language features (RAII, smart pointers, move semantics, templates,constexpr, the STL)

Concurrency and parallelism- threads, async tasks, synchronization primitives, atomics, and the C++ memory model, with the ability to write correct, high-performance multithreaded code

Clean, maintainable, well-structured C++ and modern build tooling (e.g. CMake)

Memory management, performance profiling, and debugging in native environments

Inter-process communication, native integrations, and low-level system programming

Cross-platform development across Windows and Linux

Experience with C# / .NET Core- valued alongside C++, as parts of the platform are built in .NET for extensions and integrated services. Strong C++ engineers who are newer to .NET are encouraged to apply; well support you in ramping up

Solid testing knowledge and discipline- you write unit and integration tests as a natural part of development, are familiar with testing frameworks (e.g. GoogleTest/Catch2) and practices such as mocking and test-driven development

Hands-on experience with AI-assisted development tools(e.g. Cursor, Claude Code) - you use AI to accelerate coding, code review, and problem-solving, and are keen to push these tools further

A customer-first mindset- comfortable jumping on customer calls and turning first-hand feedback into better software

Thrive in a globally distributed team- you communicate clearly and collaborate well across time zones and cultures

Experience working in and succeeding within agile development teams

Comfortable with change and continuous evolution of product direction

A get-your-hands-dirty attitude: not afraid to pick up a new technology or pattern quickly

A proven track record of producing high-quality, maintainable code and applying engineering best practices

Nice to Have (Not Required)

Experience with cloud services development, ideally on Azure

Experience with Docker and Kubernetes

Experience with DevOps pipelines and Cloud Operations (monitoring, observability, logging)

Experience developing automation engines or background service architectures

Requirements:
What we need to see:

M.Sc. or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.

+5 years of experience.

Strong ML/Data Science background with hands-on experience in LLMs or generative AI.

A systems-level mindset with the ability to estimate end-to-end requirements across the entire AI stack.

Proven ability to translate research and product requirements into clear software/hardware specifications.

Exceptional research skills: you can digest academic papers, self-learn new domains, and independently test hypotheses.

Advanced Python programming skills for performance modeling and data analysis.

Excellent communication skills, with the ability to present complex findings with clarity and conviction.

A pragmatic approach: you are detail-oriented but can prioritize effectively to focus on the most critical issues.


Ways to Stand Out from the Crowd:

Deep understanding of datacenter infrastructure, network topologies, and protocols.

Expertise in distributed training methods and their impact on infrastructure.

Knowledge of AI performance metrics and the impact of different deployment strategies.

Experience extrapolating academic research into tangible hardware architecture requirements.

A track record of leading complex, multidisciplinary research projects that result in production impact.

Requirements:
What we need to see:

B.Sc./M.Sc. in Computer Science, Computer Engineering, or a related technical field.

8+ years of software engineering experience building production distributed systems.

Core Systems Programming: Expert-level proficiency in languages such as Go, C++, or Rust, with a focus on high-performance, concurrent architectures.

Solid understanding of Kubernetes and container-based deployments for production services.

Experience deploying, monitoring, and maintaining ML models or data-intensive services in a production environment.

Comfort working in ambiguous, fast-moving environments where the product is still being shaped.


Ways to stand out from the crowd:

Experience building ML model-serving platforms or MLOps tooling (model registries, A/B rollout frameworks, feature stores) at scale.

A track record of taking systems from prototype to stable, production-grade platform serving real enterprise customers.

A "Systems" Thinker: You don't just write software; you understand the full stack, from how data moves across the wire to how its processed in a distributed cluster.

Practical Innovation: The ability to simplify complex problems and build internal tools or frameworks that empower other engineering teams to move faster.

Requirements:
What we need to see:

B.Sc. degree in Computer Science or equivalent experience.

3+ overall years of experience in technical software development.

Experience in C++ and Python programming on top of Linux operation system.

Fast and self learner with outstanding communication and technical skills.

Motivated, responsive, and keen on process improvement.


Ways to stand out from the crowd:

Experienced in software development on open source project.

Experienced in Networking protocols: L2 and L3.

Background in Linux shell scripting.

Scrum methodology and active scrum master.