דרושים » תוכנה » Senior Backend Engineer - ML Platform

We're looking for a Senior Backend Engineer to join our Platform team in Tel Aviv. You'll build the infrastructure that powers our entire engineering organization, accelerating how our teams ship features that millions of customers rely on. This role is perfect for someone who loves solving complex distributed systems challenges and creating tools that make other developers' lives better.
We believe three things matter for every role a: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually ork.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Build core platform services that support all development teams across web, mobile, and backend systems
Design and maintain robust APIs for distributed microservices architecture using TypeScript, with Rust experience as a major plus
Collaborate with staff engineers and tech leads to establish platform standards, patterns, and best practices across the engineering organization
Own service stability and communication between systems, implementing both synchronous and asynchronous patterns at scale
Drive developer efficiency initiatives by creating tools, frameworks, and infrastructure that eliminate friction for product teams
Work hands-on with AWS infrastructure including Kafka, RabbitMQ, EKS, SQS, Lambda, and infrastructure-as-code tools like Pulumi
Partner closely with DevOps teams to ensure seamless deployment, monitoring, and scaling of platform services

Were looking for a senior-level backend engineer to join our growing Engineering team in TLV.
This role will require you to bring features to the finish line while collaborating closely with other developers, as well as with the Product, QA, Data, and Machine Learning teams-all with the goal of delivering a seamless, joyful experience for our customers.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Help build our products using microservices written in Typescript (using NestJS).
Leverage our in-house autonomous tools to manage all development flow, from setting up our development environment to creating git branches and deploying services to production
Collaborate closely with the Product team, in a self-sufficient squad to achieve the squads OKRs
Be the owner of your domain to ensure code quality, performance, and scalability of our products
Coach and mentor other developers and help them elevate their skills

Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of Lemonades data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives Lemonade toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
We believe three things matter for every role at Lemonade: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.

As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.

Key Job Responsibilities and Duties:

Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.

Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.

Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.

Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.

Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Required Senior ML Platform Engineer - Sovereign AI Engineering
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.


Key Job Responsibilities and Duties:

Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.

Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.

Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.

Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.

Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.
This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.
Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.
This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.
Responsibilities:
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes
Work closely with product and engineering teams to translate business needs into scalable AI solutions
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact

Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Staff SW Engineer on the Customer Lifecycle Management team, you will be tasked with joining our dedicated platform team committed to providing essential services that support the success of other developer teams. Your primary customers will be fellow company developers who rely on our department's key services, including identity and user management, metering, and license management; in this role, you'll play a crucial role in ensuring the smooth functioning of these critical components and empower our users to achieve their goals.
We are seeking a seasoned colleague with the ability to lead epics, features, and inspire others, while participating extensively in the architecture of the new solutions we're building to elevate the entire journey of our customers-creating new features and scalable systems, rebuilding existing ones from scratch, and providing comprehensive, robust APIs that help both S1 and our customers/partners manage customer-centric interactions within our flagship SaaS platform.
Join our international team of 9 (with colleagues across Brno, Prague, Slovakia, and Israel) and become an integral part of a friendly, collaborative, pragmatic, professional, and diverse group of individuals who are ready to tackle major SW engineering challenges!
Your stack: Java (v21), Spring framework family (Boot, Web, Web-Flux, Cloud), Gradle, Jooq; Kafka, PostgreSQL, ClickHouse, Redis, Docker, Helm, Kubernetes, Terraform, AWS/GCP across multiple cloudregions, GitHub Actions, ArgoCD, Prometheus, Grafana. To enable you in your work, we provide company access Claude Code
What will you do?
Primary responsibilities include:
Collaborate across teams - to shape and define system requirements, ensuring alignment with overall business goals.
Design and drive projects - lead execution of high-priority, high-visibility platform projects, ensuring timely delivery and exceptional quality.
Own feature development - take full ownership of the feature development lifecycle, from refining requirements through to successful production deployment, ensuring seamless integration and functionality.
Build and maintain secure and scalable backend - infrastructure that serves as the backbone for other development teams, supporting their needs and enhancing overall system performance.
Ensure efficiency and performance - develop solutions that guarantee reliability, scalability, and optimal performance, leveraging best practices and modern technologies.
Conduct code reviews - provide constructive feedback, fostering a culture of continuous improvement and high-quality code standards.
Troubleshoot complex issues - quickly identify, diagnose, and resolve, minimize downtime and ensuring smooth operations; be part of rotating on-call duty to respond/troubleshoot to the outage incidents.

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.

Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior Back-end engineer you will be building our companys next-generation cloud-based security platform and are looking for a strong backend software engineer. Youll enjoy building systems from the ground up, working hands-on in complex, large-scale environments, and taking ownership to drive solutions forward.
What will you do?
The Collection team leads projects that directly impact the company's bottom line, focusing on areas such as remote operations, EDR, and XDR. Our initiatives start from concepts and evolve into products deployed across millions of endpoints and servers
This multidisciplinary team comprises experts in backend, frontend, and endpoint technologies (Windows, Linux, Mac), enabling us to independently ideate, develop, and deliver solutions at scale.
As a Senior Backend Engineer, you will implement innovative projects from inception to implementation, shaping the architecture, design, and development of new modules within our comprehensive security platform. Operating across multiple strategic product lines, youll have a direct and visible impact on the success of key company initiatives.