דרושים » תוכנה » Machine Learning Backend Engineer

We're looking for a Backend Engineer to help build and scale the Machine Learning Platform that powers how we use AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
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 you'll:
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.

We're looking for an experienced xEngineer with a backend orientation to join the User Voice team.
User Voice is the platform that lets our company hear its users at scale. It ingests feedback from millions of user interactions and transforms it into actionable insights through a multi-stage AI pipeline - combining natural language understanding, semantic representation and retrieval, and large-scale unsupervised clustering. The platform is expanding rapidly - onboarding new feedback channels and new types of user signals - and you'll be a driving force in shaping the backend architecture behind that growth, powering the insights that shape product roadmaps across our company.
In your day-to-day, you will:
Design and evolve the platform's backend together with the team - a large-scale, event-driven microservices system processing feedback in real time and in batch
Lead the expansion to new feedback channels and new types of insight, shaping how each one is brought into the platform reliably and at quality
Build and improve the AI pipeline stages that turn raw feedback into structured, trustworthy insights - from LLM-based information extraction to semantic clustering
Help establish evaluation as part of how the team ships - automated quality measurement, regression evaluation on model and prompt changes, and readiness criteria for new feedback channels
Collaborate with data engineering, data science, and product to take capabilities from idea to production
Treat reliability, scalability, and cost as core features of the platform.

Were hiring a ML Engineer to accelerate AI-driven innovation across B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do:
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

we are looking for a Senior AI Builder to take AI from a "promising demo" to real production systems that customers rely on - and that continue to work well over time.

Our R&D group is a team of 12 engineers and one architect, spanning backend to mobile, building the accounting platform businesses actually run on every day.



What you'll do

Build and ship LLM-powered AI capabilities to production- agentic flows, retrieval over our data, extraction from real-world documents, and more. Solutions need to be accurate, measurable, cost-efficient, and rollback-ready.
Build and lead the evaluation process - continuously measure the quality of models and solutions, and be able to answer clearly: is the new version actually better than last week's?
Own whatever it takes to get the solution into production- from AWS Lambda to Vue and PHP. You don't need to be an expert in every technology, but you should be comfortable getting into the code and solving problems wherever the work actually lives.

Were seeking a Senior Machine Learning Engineer with strong MLOps abilities to own the production ML systems behind user engagement, cardiovascular risk stratification, and personalized health recommendations in the app. You'll build and run the CI/CD, real-time serving, versioning, and monitoring infrastructure that models depend on, working closely with data scientists who own the modeling to make sure what they build runs reliably at scale. You should have a proven track record of shipping ML systems to production and be comfortable using AI coding assistants as a core part of your workflow.
Responsibilities:
Build and own production ML infrastructure, including CI/CD pipelines, real-time model serving, model versioning and registries, automated evaluation pipelines, monitoring, and observability.
Serve models in real time at scale, with a strong focus on low-latency inference, reliability, and graceful degradation under load, and operate batch inference with clear standards for latency, availability, correctness, and cost.
Write high-quality, maintainable, well-tested production-grade code, and own its observability, debugging, reliability, and scalability in production.
Implement model monitoring for drift, data quality, latency, and performance degradation, with automated retraining.

we are looking for a Machine Learning Engineer.
What You'll Do:
- Design and ship the ML backbone of Gini AI Workers - routing, tool selection, reasoning, memory, evaluation.
- Build evaluation and feedback loops - offline evals, online A/B, regression harnesses, human-in-the-loop labeling pipelines.
- Optimize cost and latency across the agent stack: prompt engineering, model routing (frontier ↔ small ↔ fine-tuned), caching, speculative decoding, distillation.
- Fine-tune and/or RAG-tune models for vertical enterprise tasks (invoice extraction, PO matching, ticket triage, forecasting).
- Own the ML infra - training pipelines, experiment tracking, model registry, deployment, monitoring, drift detection.
- Partner with backend + product to turn research into shipped features on a weekly cadence.

We're backed by tier-1 global VCs, led by second-time founders, and already deployed with organizations operating at serious scale. AI is not a feature here - it's the system.
We're hiring a Senior AI Engineer to design, fine-tune, and operate AI agents and large-scale models in production. This role exists because off-the-shelf models aren't enough for the problems we're solving.
If you enjoy pushing models until they break - and then fixing them - keep reading.
What you'll do:
Design and operate AI agents that reason, act, and collaborate with humans
Fine-tune and adapt large language models for:
Behavior analysis
Reasoning over long, messy timelines
High-precision enterprise workflows
Build agent orchestration systems (tool use, memory, planning, feedback loops)
Run large-scale inference and training pipelines in production
Work on model evaluation, drift detection, and continuous improvement
Optimize for latency, cost, and reliability at real enterprise scale
Partner closely with DevOps, security, and backend engineers - no research silos
Ship models that are auditable, explainable, and safe in sensitive environments

we are using technology to transform transportation around the world. From changing a single persons daily commute to reducing humanitys collective environmental footprint - weve got huge goals.
As a Senior Backend Engineer in the Routing team, you will be responsible for designing, building, and scaling the backend systems that power our companys core products. Youll work on high-impact, distributed services that manage geospatial data, large-scale databases, real-time events, and mission-critical workflows used across multiple teams and regions. Your work will directly influence system reliability, performance, and developer productivity at scale.
You will collaborate closely with Product, Infrastructure, Data, and other engineering teams to define system boundaries, evolve shared services, and ensure our backend platform can support rapid product growth. You will be part of a highly skilled and motivated engineering group responsible for building robust, scalable, and maintainable backend systems that operate in real time and at high load.
What Youll Do:
Design, build, and scale backend systems and data pipelines that power our companys GIS and mapping platform, from initial design through production deployment and long-term ownership.
Own features end-to-end with strong accountability, including design, implementation, testing, deployment, monitoring, and ongoing maintenance.
Develop and maintain Python-based data pipelines that ingest, process, and transform large-scale OpenStreetMap (OSM) and other geospatial datasets.
Model, store, and query complex geospatial data using PostgreSQL and PostGIS, including road topology, zones, polygons, points, and other business-critical spatial entities.
Optimize database schemas, spatial indexes, and queries to efficiently handle large datasets and high-throughput workloads.
Build and maintain backend services and APIs that expose geospatial and mapping data to other backend services, frontend applications, and data consumers.
Collaborate closely with other backend teams, frontend teams, data teams, and infrastructure to align on data contracts, system boundaries, and cross-team initiatives.
Improve system reliability, observability, and performance through monitoring, alerting, benchmarking, and continuous optimization.
Contribute to architectural decisions, technical standards, and best practices, while mentoring other engineers and raising the overall engineering bar.

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 disrupting the multi-trillion dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal driven, and, at our core, we believe every voice has value and can impact our bottom line. If you are a creative, solutions oriented individual who is ready to put your career in drive, we are the place for you! We are looking for Senior Engineers who treat AI as a core part of their workflow - people who experiment, iterate, and know how to get real value out of AI tools. Flexibility, curiosity, and a problem-solving mindset are must-haves. In this role you will have the opportunity to take ownership of the development of groundbreaking, AI-driven products and work on interesting projects inside a smart, fun, and dynamic engineering team. This position is based out of our Jerusalem or Tel-Aviv offices and reports to the Dev team lead.

What you will be responsible for:
* Write clean, high-quality, high-performance, maintainable code.
* Ensure that the projects you work on meet business objectives and coding standards.
* Support the deployment and testing of new products and features.
* Collaborate with cross-functional teams to gather and analyze requirements, translating them into technical specifications.
* Design and implement APIs and integrations with third-party services to enhance system functionality.
* Optimize application performance through code profiling, monitoring, and refactoring as necessary.
* Implement automated testing frameworks to ensure code robustness and reliability.
* Participate in code reviews and provide constructive feedback to peers to foster continuous improvement.
* Stay updated with emerging technologies, best practices, and industry trends to drive innovation within the team.
* Assist in the establishment and enforcement of development standards and coding conventions.

Why you should join us:

* An awesome global team of forward-thinking, innovative go-getters
* Integrate with tech titans: Work directly with APIs from Google, facebook, Microsoft, and more.
* Be part of a rapidly scaling company poised for the future.
* Learning and growth opportunities within a fast-paced SaaS startup environment
* Clear career advancement path for strong performers
* As a part of our team, your success in this role is crucial to our company's growth. We are committed to supporting you in achieving your KPIs and goals and providing regular feedback to help you reach your full potential. Together, we can make a real impact and achieve great things!
* And how can we forget? Cibus and lots of yummy kitchen treats:-) In the meantime, you can get to know us a little better by checking out  on instagram facebook LinkedIn Are you the one? Send your resume to us