לוח משרות דרושים בתל אביב יפו, לחיפוש זה נמצאו 8,528 משרות

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're looking for a System Architect to own the technical foundation end to end.

What you'll do

Own the architecture - a scalable, cloud-native system from whiteboard to production on a greenfield Azure environment you'll stand up yourself (Kubernetes-native, Everything-as-Code, GitOps, CI/CD from day one).
Work directly with our Chief AI Officer to translate complex decisioning methodologies into clean,self-service products a customer can run without a data-science team.
Lead the coding. Set the standards, make the hard calls, and write the core code yourself. You'll guide the engineers shoulder-to-shoulder - leadership by example, not by org chart, without managing them directly.
Stand up a fully agentic SDLC - building the product withAI coding agents end to end, so a small team ships like a large one.
Design the integration layer so the product plugs into each host's native agent and data surfaces - customers adopt it without leaving the tools they already use.

we are transforming our internal infrastructure into a high-velocity, self-service product. This is a senior opportunity to architect the future of our platform, setting the technical standard for how we deliver services while ensuring reliability and developer independence across diverse global markets.

Responsabilities:

Self-service enablement: Build secure, automated pathways that accelerate development while keeping organizational standards intact.
Architectural modularization: Design Kubernetes-native abstractions - controllers and operators - and decouple infrastructure into independent service lifecycles that support rapid iteration.
Everything as code: Treat infrastructure, policy, and configuration with the same SDLC as application software - versioned, reviewed, tested, and CI-gated.
Proactive reliability: Own production through robust observability, clear SLOs, and high operational hygiene; define alerting that fires correctly and lead blameless postmortems that fix the system.

We're looking for a System Architect to own the technical foundation end to end.

What you'll do

Own the architecture - a scalable, cloud-native system from whiteboard to production on a greenfield Azure environment you'll stand up yourself (Kubernetes-native, Everything-as-Code, GitOps, CI/CD from day one).
Work directly with our Chief AI Officer to translate complex decisioning methodologies into clean,self-service products a customer can run without a data-science team.
Lead the coding. Set the standards, make the hard calls, and write the core code yourself. You'll guide the engineers shoulder-to-shoulder - leadership by example, not by org chart, without managing them directly.
Stand up a fully agentic SDLC - building the product withAI coding agents end to end, so a small team ships like a large one.
Design the integration layer so the product plugs into each host's native agent and data surfaces - customers adopt it without leaving the tools they already use.

We are seeking an MLOps Engineer to help us grow our technical team's capabilities. The ideal candidate has relevant experience in data engineering, preferably within the AI field. Aviation industry experience would be a great addition.

You will be responsible for building and maintaining models and data pipelines that power our data science workflows. You'll play a crucial role in ensuring the accuracy, consistency, and efficiency of the data we use for model training and inference. This involves working with both structured and unstructured data from various sources, leveraging your expertise in data engineering and machine learning to create a robust and scalable system.

We are looking for an MLOps Team Leadto drive the development of an internal machine learning platform for a group of ML teams. This is a hands-on leadership role: you will guide a small team of MLOps engineers that builds the automation and infrastructure powering our research (R&D) workflows and runs our pipelines to production. You will take ownership of end-to-end initiatives and drive the team toward critical infrastructure and model-lifecycle milestones, while staying close enough to the code to set technical direction and raise the bar by example.

You will be responsible for building and maintaining the models and data pipelines behind our data science workflows, ensuring the accuracy, consistency, and efficiency of the data used for training and inference, working across structured and unstructured data from many sources on a large-scale, distributed platform.

Responsibilities:

Lead, mentor, and grow a team of MLOps engineers, owning delivery and technical quality.
Take end-to-end ownership of infrastructure and pipeline initiatives across the LMM group, from design through production.
Stay hands-on: contribute to design and code, review work, and set engineering standards.
Drive the team through critical milestones in ML model-lifecycle and infrastructure ownership.
Partner with R&D and other stakeholders to translate research needs into robust, scalable systems.
Help evolve the platform, including our ongoing migration from Dask to Ray.

We are seeking a talented and self-driven experienced Data Scientist to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact.

Responsibilities:

Develop and implement state-of-the-art econometric and machine learning models for demand forecasting.
Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability.
Collaborate with cross-functional teams (including product, data engineering, MLOPS and Platform) to deploy ML systems in production.
Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives.

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.

The Price Optimization (PO) team is where insights become decisions. We work with large-scale customer data and market predictions - like demand forecasts - to drive revenue management decisions that actually move the needle.

At our core, we build and maintain the decision-making engine. That means designing the data pipelines that bring customer data in, and running it through an optimization engine that simulates the market - weighing competition, pricing constraints, inventory availability, predictive models, and each client's unique business policies - to generate the best possible price recommendations. As the final step before recommendations reach the client, quality, reliability, and attention to detail aren't just nice to have. They're everything.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems-while growing and mentoring a high-performing team.

Responsibilities:

Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.
Design, build, and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data science engineering team.

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 looking for a BI Developer to join the CISO Data Analytics team in Tel Aviv. This role is primarily focused on designing, developing, and maintaining Tableau dashboards and BI products that support decision-making across security operations, risk, compliance, and leadership. Approximately 60-70% of the role will focus on dashboard development, KPI design, data storytelling, and stakeholder engagement.

What you'll do:
Develop and deliver Tableau dashboards from requirements through deployment.

Work directly with stakeholders to understand reporting needs and turn them into dashboards.

Help translate business needs into KPIs and reporting metrics.

Maintain and continuously improve existing dashboards, ensuring data quality and stakeholder adoption.

Conduct ad hoc analyses and deep-dives to support business decisions.

Write SQL queries to extract, join, and prepare data.

Were looking for a IT infrastructure engineer to troubleshoot and solve data center IT hardware issues, process the RMA. This is a position for a technical expert working at the intersection of multiple technical and operational domains.

Your responsibilities will include
Solve the most challenging firmware and hardware related issues with servers, involving in-depth knowledge of system architecture and advanced troubleshooting

Execute workarounds and solutions for IT hardware issues

Act as a subject matter expert and point of escalation for L1 and L2 technicians

Create new processes and documentation for IT hardware team

Collaborate with related departments to im

Collaborate with vendors on warranty replacements (RMA), create requests and manage.

Improve support processes, documentation and training materials

Were looking for a IT infrastructure engineer to troubleshoot and solve data center IT hardware issues, process the RMA. This is a position for a technical expert working at the intersection of multiple technical and operational domains.

Your responsibilities will include
Solve the most challenging firmware and hardware related issues with servers, involving in-depth knowledge of system architecture and advanced troubleshooting

Execute workarounds and solutions for IT hardware issues

Act as a subject matter expert and point of escalation for L1 and L2 technicians

Create new processes and documentation for IT hardware team

Collaborate with related departments to im

Collaborate with vendors on warranty replacements (RMA), create requests and manage.

Improve support processes, documentation and training materials