לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 189 משרות

We are looking for a hands-on AI Platform Team Lead to build and lead the team behind this platform: a high-throughput, low-latency engine that runs GPU-based models, from MMBERT-style models to LLMs, together with CPU-based heuristics and security logic.
This is a core infrastructure role for someone who wants to own the runtime layer of AI security at scale: performance, reliability, orchestration, GPU efficiency, and production-grade execution in the traffic path.
The team will also own the model lifecycle required to take AI security algorithms from research to large-scale production, working closely with research and algorithm teams.


Responsibilities
Build and lead Catos AI Platform team: hiring, mentoring, architecture, technical direction, and execution.
Own the AI security runtime platform for high-throughput, low-latency inline security decisions across Catos global cloud and PoPs.
Design the orchestration layer for running GPU models, CPU heuristics, and security logic as one production engine.
Own production readiness: observability, SLOs, autoscaling, reliability, rollout, rollback, and operational health.
Own the model lifecycle platform: registry, versioning, deployment, monitoring, and safe production rollout.
Work closely with research and algorithm teams to productionize AI security models and algorithms at scale.
Define the long-term platform strategy for AI runtime and model serving at Cato.

We are looking for a Senior Data Scientist / Applied AI Researcher with deep expertise in NLP and LLM-based systems, and the ability to operate across the full lifecycle, from problem formulation and research design to production deployment and real-world iteration.

You wont be working on isolated experiments. Youll be part of a multidisciplinary team that owns the system end-to-end and is responsible for how it behaves under real production traffic.

This role requires strong scientific discipline and the maturity to balance innovation with practical constraints.




What youll do
End-to-End Ownership: Lead AI security solutions from problem formulation and research design through model development, evaluation, and production deployment. Ensure solutions are measurable, reliable, and effective under real-world traffic.
Drive Technical Direction: Take responsibility for ambiguous AI security problems, propose thoughtful approaches, and drive structured experimentation and deep model analysis.
Build for Scale: Design systems that are not only accurate, but scalable, efficient, and robust.
Staying Updated: Continuously explore advances in NLP and LLM-based systems, and critically assess what is worth integrating into a production environment.

We're hiring an exceptional Applied AI Scientist to join our team!
In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.
In This Role, You Will Be Responsible For:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in Tipalti's proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

Were looking for a hands-on AI Engineering Tech Lead to define and drive AI-native engineering practices, lead the architecture and development of scalable, intelligent systems, and embed AI across the software development lifecycle. This role involves providing technical leadership, identifying and solving architectural challenges, and collaborating cross-functionally to deliver high-impact, production-grade solutions.


Responsibilities:
Define and codify AI-native engineering practices, patterns, and guidelines to elevate the software development lifecycle.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Identify architectural risks, systemic bottlenecks, and long‑term scalability concerns - and proactively drive solutions.
Collaborate closely with Product, Customer success, Security and Business stakeholders to ensure technical solutions deliver real business impact.

our company offers hope to patients suffering from rare and severe diseases by forming partnerships with emerging biotech companies to accelerate access to highly innovative therapies in international markets. As the creator and leader of the global partnership category in the pharma industry, we strive to be Always Ahead and work relentlessly to bring therapy to patients in need, no matter where they live. Our values are at the core of every action we take, and we are committed to going above and beyond for the benefit of the patients we serve. We are a dynamic, fast-paced company operating in over 30 countries on 5 continents. We are looking for out-of-the-box thinkers, people who are passionate, caring, agile, and adaptive, to join us on our mission. If you want to make a difference in people's lives, we invite you to join us! We are looking for a professional Senior AI Enablement to drive AI and business transformation initiatives, combining strategic thinking, execution discipline, and strong cross-functional stakeholder management. This role will play a key part in shaping and driving AI-enabled transformation across the organization, working closely with business, product, AI, and IBT teams to translate strategic priorities into clear execution plans, adoption frameworks, and measurable business impact. The role will be responsible for driving transformation execution governance, including initiative prioritization, business process understanding, dependency management, meeting outcomes, follow-up cadence, risk tracking, and cross-functional accountability across strategic initiatives.
Responsibilities:

* Drive AI and business transformation initiatives from strategy into structured execution.
* Work closely with business, product, AI, and IBT stakeholders to shape AI-driven capabilities and adoption processes.
* Lead transformation execution governance, including planning, prioritization, follow-up, dependency management, and execution rhythm.
* Translate business priorities into actionable plans, clear workstreams, and measurable outcomes.
* Define KPIs, ROI models, and cost-related considerations to support decision-making and value realization.
* Identify risks, gaps, dependencies, and blockers, and ensure timely escalation and resolution.
* Build and implement transformation processes, governance structures, and execution frameworks.
* Support senior stakeholders with clear communication, structured updates, and presentation materials.
* Drive cross-functional alignment and accountability across multiple teams and initiatives.
City:
Petah Tikva

CodeValue is looking for a hands-on Senior AI Engineer with real-world experience building and deploying LLM-based and Agentic Systems to production. You will be responsible for taking AI solutions from concept to reliable, scalable production systems, working across AI, backend, cloud, and infrastructure. Responsibilities
* Design, develop, and deploy LLM-based and Agentic Systems for production environments.
* Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems
* Develop backend services and AI solutions using Python
* Work hands-on with agentic frameworks such as LangGraph, CrewAI , or similar/custom frameworks.
* Deploy and operate AI systems in cloud environments
* Troubleshoot complex system issues and improve observability, reliability, and performance
* Collaborate with development, DevOps, security, and other technical teams.

We are looking for a strong Backend Software Engineer to bridge the gap between our Machine Learning research team and our enterprise production systems. You will act as the technical backbone for our ML Scientists - by advising, designing and implementing the production facing features. If you are a backend expert who wants to solve complex system architecture challenges and dive into the world of ML platforms & Agentic LLM pipelines, this is the role for you - An exciting role collaborating with ML science team, data/infra team and DevOps to drive real customer impact.



As a ML Engineer, you will:



Lead ML delivery: transforming research output (code, models, ideas) into robust, scalable, low-latency microservices in production

Help architect e2e solutions to real customer pains ranging from ingestion, integration, ETLs, DB design up to low-latency services

Design, build, and maintain automated workflows for ML models, including auto-trains, benchmarking, testing, performance gating, and production deployment.

Tackle complex backend challenges: optimizing API response times, managing database connectivity and concurrency at scale, balancing accuracys drive for complex questions with the business needs of fast responsiveness by making hard technical trade-offs between customer gains and business costs.

Design and optimize data pipelines and ETL processes, connecting our Snowflake data warehouse to our training environments.

Work within our existing ML infrastructure (Kubeflow, MLflow, KServe) to ensure smooth model lifecycles and performance monitoring.

Collaborate closely with ML Scientists, guiding them on software engineering best practices without slowing down their research.

Monitor and optimize production models for performance, cost efficiency, availability, and observability.

We are seeking an AI Full-Stack Developer to build and scale automation solutions across internal company processes using AI, LLMs, and agent-based systems. This role focuses on delivering practical automation solutions, integrating AI capabilities with internal tools, and orchestrating workflows across multiple systems, with a dynamic range of tasks that offer both quick wins and complex challenges.

Responsibilities:

Build AI-driven automation solutions using LLMs, APIs, and agent frameworks.
Develop systems to automate document processing, data extraction, and operational workflows.
Design and implement multi-step automated workflows connecting AI models and internal services.
Integrate automation solutions with internal systems such as HR, finance, legal, dashboards, and ticketing tools.
Deliver and iterate practical automation solutions swiftly, from simple GPT/AI integrations to complex workflows.
Train and support internal teams on newly built or optimized systems for strong adoption and self-sufficiency.
Collaborate with Technical Team Lead, Product Manager, and IT teams on architecture and system integration.
Communicate clearly with internal stakeholders and external partners or vendors.

We are seeking a Senior AI Researcher to lead post-training evaluation, red-teaming, and reinforcement learning (RL) gym audits on open-weight models. The ideal candidate will establish rigorous benchmarking methodologies, evaluate large language models (LLMs) against complex threats like Indirect Prompt Injections (IPI), and construct post-training evaluation pipelines that accurately measure realistic frontier-level security capabilities. Key Responsibilities RL Post-Training & Benchmarking: Execute post-training runs (e.g. GRPO) using mainstream open-weight generalist models against security-focused RL environments, targeting threat vectors like Indirect Prompt Injection (IPI). Reward Diagnostics & Trace Analysis - Analyze live loss curves and rollout traces to identify reward hacking, lazy policy convergence, and flawed or over/under-specified verifiers. Task & Environment Auditing: Review tasks and multi-turn environments (including tool use, web navigation, and computer use) for realism, threat model accuracy, data distribution, and dataset balance. Performance Reporting (Gym Cards): Generate comprehensive evaluation cards detailing hill-climbing performance uplift across checkpoints, failure modes, tokens/turns per rollout, and task-level success rates. Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings.
About us:
we are a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, our company provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. we are widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

We are looking for an AI Engineer to build the systems that drive this: AI agents that investigate vulnerabilities, generate and validate code fixes, and continuously refine their performance. In this role, youll work at the intersection of AI engineering, security automation, and rigorous evaluation to translate cutting-edge models into dependable production tools.

Responsibilities

Build and evolve production AI agent pipelines for CVE research, patch generation, validation, container image remediation, and end-to-end merge requests.

Design the agent capabilities behind those workflows: prompts, tools, model selection, context, guardrails, and integrations.

Build the feedback loops that make our systems better: tracing production runs, creating datasets, defining evals and scorers, and using results to guide iteration.

Analyze real-world performance to answer the questions that matter: Did this change improve patch success, quality, latency, or cost Can we prove it?

Operate what you build in production across Kubernetes, Argo Workflows, AWS, and GitOps.

Partner closely with Product and engineering to focus on the customer problems with the highest security impact-and ship quickly.

we are looking for a AI Engineer.
Key Responsibilities:
Develop state-of-the-art ML applications using LLMs and computer vision
Design end-to-end web application features and AI workflows
Collaborate with co-founders on requirements and software solutions for construction
Stay current with emerging technologies

In this role, you will define and execute the GenAI GTM strategy for us in Israel and Sub-Saharan Africa.
You will be driving adoption campaigns for new and existing services including Amazon Bedrock, Kiro, Amazon Quick, Amazon SageMaker and more. You will be creating salesplays to serve your markets and enabling the local specialists, account teams and customers on new launches. You will be working directly with customers, forming trusted executive relationships and supporting customers as they move from experimentation to wide AI value creation. Youll collaborate with a broad group of people across us and act as the conduit between our customers and our product teams. Most importantly, youll make a difference by applying your expertise to our customers most critical problems.

We are looking for a hands-on Computer Vision & AI Algorithm Engineer to develop advanced imaging algorithms for a cutting-edge medical device. The role spans the full spectrum of algorithm development - from creating new solutions to improving, maintaining, validating, and integrating them into the product. The ideal candidate is curious, pragmatic, and comfortable moving between deep learning, classical computer vision, data analysis, debugging, validation, and product integration as needed. They measure success by seeing algorithms work reliably in a real-world product and enjoy collaborating across disciplines to solve the challenges that move the product forward.

Responsibilities may include the following and other duties may be assigned:
Design, develop, maintain, and continuously improve AI, computer vision and image processing algorithms for a medical imaging product.
Own the full lifecycle of algorithm development, from concept and data definition through implementation, validation, product integration, and long-term maintenance.
Use both classical computer vision methods and machine/deep learning methods to come up with solutions for various problems in the domains of image classification, segmentation and 3D modeling.
Collaborate with SW developers, biomedical engineers, product specialists and other algorithms developers to refine and enhance existing applications.
Maintain and improve algorithm robustness, performance and reliability in production environments.
Identify opportunities for innovation and design novel algorithms to address complex technical challenges.
Stay at the forefront of relevant academic research by reviewing the latest papers and evaluating their potential impact on the companys algorithmic stack.