דרושים » תוכנה » AI Senior Software Engineer, ML Platform

we are looking for a AI Staff Software Engineer, ML Platform.
This is a Principal AI Software Engineer role at the heart of AI Engineering group-where algorithms, infrastructure, and products intersect. Youll lead the evolution and scaling of AI architecture, ensuring reliability, efficiency, and impact across global clinical workflows. The role combines technical depth with cross-functional influence, strengthening how our AI systems are built, integrated, and delivered to drive ongoing impact for patients and care teams.
Responsibilities:
Lead cross-domain engineering initiatives connecting AI algorithms (CV, NLP, and deep-learning systems), software, and data systems-from design to delivery.
Stay hands-on, contributing to AI-serving (training and inference), integration, and orchestration components while setting high technical standards.
Partner with Algo teams to connect algorithmic innovation with strong system design, ensuring smooth delivery across Product and Engineering.
Guide architectural evolution, ensuring efficiency, consistency, and maintainability across AI workflows.
Communicate direction and priorities clearly, aligning teams around technical goals.
Mentor engineers and promote technical excellence, sound design, and shared best practices.
Foster collaboration and shared ownership, helping maintain a culture that values clarity, curiosity, and technical excellence.
Uphold quality and reliability-including clean code, testing, and CI/CD discipline-while evaluating and adopting new tools that enhance performance and long-term scalability.

we are looking for a Senior Software Engineer.
The Senior Software Engineers main responsibilities are developing the customer-facing products, enhancing medical workflows, integrating with our AI solutions, and growing our products scale both on technical aspects as well as scaling our product offerings.
Responsibilities:
Work as an integral part of our senior (and super strong) development team.
You will have a leading role, central responsibility and will be the owner for the design and development of many of our customer-facing components and projects (both frontend, backend and databases).
Receive end-to-end ownership for product features from ideation to deployment, and work closely with Product and UX to bring the teams imagination to life.
Be trusted with autonomy, freedom and influence to design solutions and make technical decisions, in a critical position for the companys growth.

we are looking for a AI Software Tech Lead, ML Platform.
This is an AI Software Tech Lead role within AI Engineering group - working side by side with Algo teams to build and evolve AI solutions that deliver real clinical impact. Youll take ownership of the design and development of AI-driven systems, leading projects that turn advanced models into scalable, reliable components within platform. The role is highly hands-on and combines technical excellence with leadership - guiding design decisions, mentoring engineers, and collaborating across Algo, Product, and Engineering to ensure alignment, robustness, and impact.
Responsibilities:
Build and evolve the AI-specific infrastructure and components that enable robust, scalable model training and serving, working side by side with Algo teams to co-design interfaces, workflows, and deployment strategies
Stay deeply hands-on, driving complex technical work while setting high standards for design, code quality, and execution
Own project-level architecture and key technical decisions, ensuring sound design choices and smooth collaboration across teams
Promote engineering excellence and mentorship, fostering maintainable systems, clean code practices, and continuous learning
Communicate clearly and proactively throughout design and development-articulating goals, progress, and technical decisions to all relevant stakeholders
Collaborate across Algo, Product, and Engineering to ensure technical alignment, clear interfaces, and cohesive delivery
Continuously evaluate and adopt new tools or frameworks-from cloud infrastructure to orchestration and MLOps practices-that improve efficiency and long-term scalability.

we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.

Required Machine Learning Hardware Architect, Hardware, Software Co-Design, Cloud
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Tel Aviv, Israel; Haifa, Israel.
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Machine Learning Hardware Architect within the Co-design team, you will serve as a technical lead bridging model architecture innovation and next-generation hardware design. Operating at the highest levels of AI research and engineering, you will define the goal and architectural roadmap for our future machine learning serving and training capabilities. You will guide the integration of ML research such as massive-scale foundation models with advanced silicon architectures to create industry-leading, high-performance, and power-efficient accelerators.
Responsibilities
Define and drive the technical roadmap and architecture for the hardware/software stack to ensure exceptional performance for ML models. Act as the technical liaison across research, software, and hardware teams, steering model architecture innovation to maximize scaling, quality, and hardware efficiency.
Architect next-generation configurable simulation frameworks and performance models, setting the organizational standard for evaluating complex microarchitectural decisions. Drive high-stakes choices regarding Power, Performance, Area (PPA) and buildability for future chip and system architectures, expertly balancing long-term technological trends with strict product delivery timelines.
Guide system-level performance analysis across highly distributed ML systems, innovating new methodologies to optimize and balance compute, memory bandwidth, and inter-chip network requirements. Their leadership will directly shape the future of high-performance AI infrastructure and hardware-software co-design.
Manage cross-functional partnerships across hardware, compiler development and ML teams.

We are looking for an experienced NLP Data Science Team Leader to lead a team of talented NLP Data Scientists and drive the development of cutting-edge NLP solutions at scale. This role combines hands-on technical leadership, people management, and strategic influence over product and research directions.
Responsibilities:
Lead and grow a team of NLP Data Scientists
Manage, mentor, and support team members professional development
Foster a culture of excellence, ownership, and continuous learning
Own end-to-end delivery of NLP solutions
Oversee algorithmic features from ideation through research, development, and production
Ensure high-quality, scalable, and maintainable solutions
Drive technical direction and innovation
Guide research efforts and evaluate new NLP/ML technologies
Translate business needs into impactful NLP solutions
Collaborate cross-functionally
Work closely with Product, Engineering, and Business stakeholders
Align team priorities with company goals and product roadmap
Maintain hands-on involvement
Contribute to architecture, modeling, and critical algorithmic challenges
Review code, experiments, and methodologies

As a Principal Backend Engineer on the Access Team, you will be a key technical leader responsible for designing, building, and scaling the critical backend services that manage identity and access for the entire Cortex Platform. You will drive architectural decisions and ensure the security, reliability, and performance of our core access control systems.
Key Responsibilities
Lead the design and implementation of highly scalable, secure, and resilient backend services for identity and access management.
Set the technical direction for the team, making key architectural decisions and promoting engineering best practices.
Write and review high-quality, production-ready code for critical platform services.
Mentor and develop other engineers on the team, fostering a culture of technical excellence and continuous improvement.
Collaborate with product managers, security experts, and other engineering teams to translate complex requirements into robust technical solutions.
Drive the operational excellence of our services, including monitoring, alerting, and participating in an on-call rotation.
Investigate and integrate AI and ML models to enhance threat detection and intelligent access control within the platform.

We're looking for an experienced and passionate ML Engineering Team Lead to lead our ML Engineering team and shape the next generation of our AI infrastructure. This is a hands-on leadership role where you'll combine technical leadership, software architecture, and people management to build scalable, production-ready AI systems running on edge devices.
About The Role:
Lead, mentor, recruit, and grow a team of software engineers, fostering a culture of ownership, collaboration, and continuous improvement.
Own the team's technical roadmap, architecture, execution, and project prioritization, aligning delivery with business goals.
Design, build, and maintain scalable software and ML infrastructure across cloud and edge environments.
Partner with AI Researchers to productionize Computer Vision and Deep Learning models into reliable, high-performance systems.
Design and optimize inference pipelines with a focus on scalability, latency, and reliability.
Drive engineering excellence through architecture reviews, code reviews, development best practices, and modern AI-assisted engineering workflows.

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.