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Company Overview: Our mission is to enable its global customers to protect and save lives by enhancing digital investigations and intelligence gathering to accelerate justice in communities around the world. Our AI-powered Digital Investigation Platform enables customers to lawfully access, collect, analyze and share digital evidence in legally sanctioned investigations while preserving data privacy. Thousands of public safety organizations, intelligence agencies and businesses rely on our digital forensic and investigative solutions-available via cloud, on-premises and hybrid deployments-to close cases faster and safeguard communities.?To learn more, visit us in our website.

Position Overview: As a Senior Software Developer in Cellebrite Labs, your daily mission involves designing and developing advanced capabilities to extract digital evidence from modern Android and IOS devices. You will tackle some of the toughest security protections such as PAC, Secure Elements, Code Signing, Hypervisors, and more. Working in the heart of the Digital Intelligence Labs group, you will contribute to productizing world-unique capabilities that enable law enforcement and private sector customers to conduct legally sanctioned forensic investigations effectively and securely. This role requires a combination of deep technical knowledge, creativity, and persistence to solve complex problems while collaborating closely with top researchers and engineers. Your work will have a direct impact on investigations that save lives and uphold justice globally.


Key Responsibilities:
* Lead and contribute to the development of new extraction technologies for Android and IOS platforms.
* Analyze and reverse-engineer low-level OS internals and security mechanisms.
* Develop robust system -level software in C, C ++, and Python.
* Collaborate with cross-functional teams to design, TEST, and integrate new capabilities into our Digital Intelligence platform.
* Stay current with emerging mobile security technologies and forensic challenges.
* Share knowledge and best practices within the team to elevate overall engineering quality.

Office Location:
Tel Aviv

At our company, we empower enterprises and service providers with cutting-edge Storage platforms that redefine performance, reliability, and cyber resilience at scale. Were looking for passionate and bright individuals who wish to take part in the design, development and all technical-related aspects of INFINIDATs R&D Department The selected candidate will be part of a professional team that develops in C ++ / Python / JAVA over Linux high-performance, multi-threaded, clustered, mission-critical, server-side products.
Responsibilities:
* Design and development of C ++ / Python / JAVA code according to product requirements.
* Addition of new features, as well as maintenance, refactoring and improvement of existing products and code bases.
* Accountability for code standards, quality and performance.

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 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 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 building an inference & fine-tuning platform that makes every kind of foundation model - text, vision, audio, and emerging multimodal architectures - fast, reliable, and effortless to train & deploy at massive scale.

Some directions we currently working on and which you can be a part of:
Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.
Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.



Some directions we are currently working on, and which you can be a part of:

Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We are looking for a highly technical and execution-oriented Senior Solutions & Integrations Engineer to lead product evaluations, system onboarding, integrations, automation, and operational enablement across our technology environment.

This role combines hands-on engineering, technical product evaluation, integration development, and operational execution. The ideal candidate is comfortable working across SaaS platforms, APIs, automation workflows, and enterprise operational processes.

You will play a key role in evaluating new products, onboarding enterprise systems, building integrations, automating workflows, implementing monitoring and alerting capabilities, and extending platform functionality where native capabilities are missing.

This is a highly cross-functional role working closely with Security, IT, Infrastructure, Engineering, and Operations teams.

Responsibilities
Product Evaluation & POCs

Lead technical proof-of-concept (POC) activities for new products and platforms
Evaluate architecture, scalability, operational fit, and integration capabilities
Produce structured technical evaluations and recommendations
Work directly with vendors during technical validation and onboarding phases
Identify risks, limitations, and operational considerations
Platform Onboarding & Integrations

Lead onboarding and implementation of new SaaS and enterprise systems
Design and implement integrations between platforms using APIs, webhooks, and automation tools
Configure authentication integrations including SSO and OAuth
Coordinate rollout activities with stakeholders and vendors
API Development & Automation

Develop lightweight APIs, scripts, and automation workflows to close functional gaps in third-party products
Build simple integration layers between internal and external systems
Improve process automation and operational efficiency
Monitoring & Alerting

Build alerting, monitoring, and observability integrations across operational systems
Integrate systems with logging, monitoring, and incident management platforms
Support operational visibility and reliability monitoring
Operational Process Ownership

Define and maintain operational processes for newly onboarded platforms
Create technical documentation, onboarding procedures, and operational runbooks
Ensure operational handoff and support readiness
Drive continuous improvement and automation initiatives
Cross-Functional Collaboration

Work closely with Security, IT, Infrastructure, Engineering, and Operations teams
Translate business and operational requirements into technical solutions
Coordinate with vendors and external partners
Provide technical guidance during implementation and adoption activities

Alice is hiring a Senior Software Developer to lead the development of our internal malware research platform. This is a senior, hands-on role with end-to-end ownership of development and delivery. You'll be the technical authority — setting code-quality standards, making the architecture calls, and mentoring the developer team. What makes this role different is who you build for. Our users are our malware researchers, and they use the tool every day. Your job is to sit beside them, learn how they actually work, surface the heuristics and edge cases they carry in their heads, and build agentic tooling that compounds their productivity. The bar isn't "does it ship" — it's "do the researchers reach for it every day." Success is measured in researcher adoption and time saved, not features merged. Agentic workflows are core to how we build. You should be fluent using them and confident designing systems where agents run in production — with clear judgment about where an agent earns its keep versus where deterministic code or a human-in-the-loop is the right call. What You'll Do Lead development and delivery
* Own technical execution end-to-end: implementation, code review, and release.
* Translate research workflows and feature requests into well-scoped tasks with realistic, risk-aware estimates the team can plan against.
* Manage day-to-day execution: unblock people, sequence work, catch problems early.
* Set and defend the technical bar: review rigor, testing discipline, documentation, architectural consistency. Partner with the researchers — and amplify them
* Embed with malware researchers to understand their workflow and capture the tacit knowledge and edge cases no spec ever wrote down.
* Translate that knowledge into reliable agentic tooling — and know when an agent is confidently wrong before it ever reaches a researcher.
* Spend roughly 5–10% of your time doing actual malware research (with structured onboarding) to stay close to how the tool is used.
* Be willing to tell a researcher when a proposed workflow won't automate well — and explain why. Be the technical authority and mentor
* Make the hard architecture and design trade-off calls.
* Mentor through code review, pairing, and design discussions. Raise the level of everyone around you.
* Dive deep on the critical, difficult features and bug fixes yourself.
* Design agentic workflows into the architecture from the start, and build the evaluations and guardrails that keep them trustworthy.

About Alice:
Alice is 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, Alice 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. Alice is 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 a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

We are seeking a talented and versatile Threat Detection Engineer to work with us in Herzliya with expertise in iOS and Android security. As a key member of our engineering team, you will play a crucial role in designing and developing complex compromise detection solutions and providing advanced professional services to customers.

Responsibilities:
Design and develop mobile focused on-device and off-device malware and compromise detection solutions that enable forensic analysis, including infrastructure, features, classification logic, tools, proof of concepts, heuristics and signatures for Android and iOS devices.
Represent the Company in front of customers by providing advanced professional services including malware and indicator of compromise analysis, as well as professional training sessions.
Develop and implement components and features using C, C++, Python, JavaScript, Go, Rust and other programming languages as needed, while employing secure coding practices and ensuring optimal performance, responsiveness, and cross-platform compatibility in line with product specifications.
Represent the company in front of potential customers and partners by conducting technical demonstrations, participating in meetings and other pre and post sales engagements.
The position may require local and international travel.

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.