דרושים » הנדסה » AI Software Engineer

At our company, we're on a mission to shape the future of the shipping industry through cutting-edge autonomous ship technology. Our solutions empower teams both on the ship and ashore to make informed decisions that dramatically enhance safety, reduce fuel consumption, improve navigation, and minimize environmental impact.
Were looking for a hands-on Edge Software Engineer to join our Innovation Team and build the software backbone that connects prototype AI perception to operational deployment. This is a mid-to-senior level role focused on reliability at the edge. Youll own communication and synchronization across distributed platforms, design robust runtime architectures, and package perception pipelines into production-grade modules built for harsh real-world constraints.
This isnt a narrow backend job - its an opportunity to build the next generation of AI-powered maritime infrastructure from the ground up, with full ownership and impact, alongside the most innovative team in the most advanced company in this space.
What Will You Do?
Architect and implement containerized edge pipelines (Docker, DeepStream/Triton) for Jetson and x86
Design and implement the edge comms stack (sync, heartbeat, telemetry)
Lead cross-functional integration with algorithm, product, and field teams
Own the end-to-end integration of AI models into embedded systems
Drive profiling, debugging, and performance tuning in constrained environments
Support hardware-software integration in both lab and vessel environments
Contribute to strategic innovation rollouts and project qualifications.

We are looking for a strong Data Engineer / Software Engineer who wants to move into Data & AI and thrives in an end-to-end environment. You wont be building models in isolation. Youll join a multidisciplinary team that owns the full lifecycle of our AI Engine- from research ideas, through model serving and optimization, to monitoring and production reliability.
If youre a team-oriented engineer with strong communication skills and a passion for becoming a rockstar in the AI security space, we want you.
What youll do
End-to-End Ownership: from shaping research ideas and experimenting with models, to deploying, optimizing, and maintaining them in production.
Solve Real-World Data Problems: Tackle real-world "data-problems" to improve the reliability and accuracy of our production evaluations.
Optimize Runtime & Inference: Improve latency, throughput, and cost efficiency of our model serving stack. Think in terms of real traffic, constraints, and SLAs.
Staying Scientific: Proactively stay updated on the latest developments in NLP and AI technologies, ensuring our approaches remain at the industry's forefront.

We are looking for a hands-on GTM AI Engineer to design, build, and deploy AI-powered workflows and automations across our go-to-market (GTM) systems.
This role sits at the intersection of business operations and technology, and acts as the engine behind revenue intelligence, process automation, and scalable pipeline generation systems.
You will be a technical force multiplier for our GTM team including creating workflows, agents, and integrations, embedded directly into core business systems (e.g., CRM, marketing automation, support tools).
This is not a traditional software engineering role, but it requires strong technical execution and ownership across the full lifecycle.
What youll do:
Design, build, and maintain production-grade AI workflows and automations to streamline GTM execution (e.g., lead enrichment, routing, research, follow-ups, CRM hygiene, and customer handoffs)
Develop and deploy LLM-based solutions, including prompt-driven workflows, reusable prompt libraries, and AI agents embedded within business systems
Build and maintain integrations and data pipelines across CRM, marketing automation, enrichment tools, and internal systems to ensure reliable, connected data across the funnel
Own workflow performance, review success metrics, iterate and demonstrate business impact.
Build and maintain AI-assisted pipeline inspection tools to give RevOps and Sales Leadership real-time visibility into deal health
Identify opportunities to reduce manual work and improve efficiency across RevOps, Sales, Marketing, and Customer-facing teams
Partner with cross-functional stakeholders to map processes, identify bottlenecks, and prioritize high-impact automation opportunities
Drive adoption through enablement: documentation, training, and ongoing feedback loops
Evaluate and implement new tools and technologies based on ROI, scalability, and maintainability.

We're looking for a Senior AI/MLOps Engineer to join a group that specializes in Security and Networking, and specifically ML, AI and agent development. As a Senior AI/MLOps Engineer, youll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, security architects and DevOps teams to ensure smooth deployment, modeling and optimization of AI models. This role involves creative problem solving alongside engineering teams, and is pivotal for the continued success of AI networking security.

What youll be doing:

Developing, improving and optimizing scalable infrastructure for handling and deploying security and networking AI models and agents in production, ensuring high availability, scalability, reproducibility, and performance.

Optimizing AI models and agents for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.

Monitoring and deploying agentic systems, LLMs, and ML models in production.

Designing and implementing frameworks/pipelines for AI training, inference, and experimentation.

Collaborating closely with data scientists, security architects and software engineers to operationalize and deploy AI models and agents, including packaging and integration with existing systems. Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews.

Collaborating with DevOps teams to integrate pipelines and workflows into the CI/CD process, ensuring flawless deployments and rollbacks.

Building and maintaining monitoring and alerting systems to proactively identify and resolve issues relating to quality, performance and infrastructure.

Implementing access controls, authentication mechanisms, and encryption standards for AI models and data.

Documenting guidelines, and standard operating procedures for MLOps/AI processes and sharing knowledge with the wider team.

Develop proof-of-concepts for new features.

Realize your potential by joining the leading performance-driven advertising company!
As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Realize your potential by joining the leading performance-driven advertising company!
As a Senior MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Required Machine Learning Engineer - AI Coding Agents & LLM Infrastructure
Tel Aviv
Full-time
A bit about us:
We are redefining how software gets built. Trusted by over 1M+ developers, we build AI-first developer experiences powered by state-of-the-art coding agents and code reasoning models. With support for 30+ programming languages and 15+ IDEs, our platform is pushing the limits of LLM-based software engineering - enabling teams to design, write, review, and ship code faster than ever. Were committed to advancing code-native AI models, multi-agent systems, agent orchestration frameworks, memory, and autonomous dev tooling to empower developers at every step of the software lifecycle.
Were growing fast, and our team is passionate about pushing AI engineering to new heights - solving complex problems in LLM training, inference optimization, reasoning, and agent orchestration at scale.
About the Role:
As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code models-optimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.

Help build an Always-On, low-overhead GPU profiling service that runs in production, scales across cluster environments, and delivers actionable insights for ML workloads. You will be hands-on delivering our profiling solutions across system software, drivers, and CUDA to make profiling continuously available and reliable.

What youll be doing:

Develop low-overhead, high-reliability implementations in C/C++, with bounded CPU/memory budgets.

Lead end-to-end feature delivery spanning user-mode components, driver/platform layers, and performance counter/trace providers.

Establish profiling models that integrate with existing ML/AI workflows (e.g., PyTorch/XLA) to turn low-level signals into actionable insights.

Required xEngineer (ai-native software engineer)
makes it possible for anyone to succeed online. since 2006, weve grown to around 5,500 employees in 22 countries, launched over 40 products, and serve over 243 million users and their visitors worldwide. here, we push you to innovate, evolve in non-traditional ways, and collaborate. we operate in small teams that work closely together at a high level.
although were already industry leaders in web creation and business, our work is nowhere near done. our goal is to become the main engine of the internet so we can create a more open web for all.
we're proud to be an equal opportunity employer. the company was built around the idea that everyone has the right to be successful, online. this same vision defines us as an employer: creating a work environment where everyone is welcome, and anyone has the right to succeed.
as an xEngineer, youll combine deep technical expertise with system -level thinking and product ownership, applying ai across the development lifecycle to build impactful systems, make thoughtful architectural decisions, and drive technical excellence from idea to production. in your day-to-day, you will:
design and own end-to-end systems and features that serve millions of users, taking responsibility across stack boundaries - from product flows and User Experience to apis, data models, and production systems
apply ai-powered tools and workflows across planning, design, implementation, testing, debugging, and refactoring
work with modern technologies and platforms (e.g., typescript, React, Node.js, JAVA, cloud, and ci/cd), continuously evolving your toolkit with ai-powered tools
lead architectural thinking by making thoughtful trade-offs around scalability, reliability, security, performance, and maintainability
collaborate closely with product managers, designers, and engineers to shape solutions while ensuring production quality, observability, and long-term system health
at the company, we believe our best work happens together. our work model is fully in person, with 5 days a week from our office. flexibility remains a core value at the company and special requests are handled thoughtfully at the team level.
we are engineering at the company - a team of ai-native xengineers with deep expertise in frontend, backend, or mobile, who use ai support to take ownership over projects end-to-end. we work in a fast-paced, dynamic development environment with autonomous teams that never compromise high quality standards. as ai increasingly generates production code, we dedicate more and more of our time developing the skills we believe are critical for today and tomorrow: system design, architecture, scalability, reliability, and security.