דרושים » תוכנה » Experienced Algorithm R&D Engineer - תל אביב

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.

You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.

Responsibilities:

Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
Develop real-time parameter steering for calibration during QEC and between circuits.
Develop and maintain agentic frameworks for autonomous system control and calibration.
Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.

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 hands-on AI Platform Team Lead to build and lead the team behind this platform: a high-throughput, low-latency engine that runs GPU-based models, from MMBERT-style models to LLMs, together with CPU-based heuristics and security logic.
This is a core infrastructure role for someone who wants to own the runtime layer of AI security at scale: performance, reliability, orchestration, GPU efficiency, and production-grade execution in the traffic path.
The team will also own the model lifecycle required to take AI security algorithms from research to large-scale production, working closely with research and algorithm teams.


Responsibilities
Build and lead Catos AI Platform team: hiring, mentoring, architecture, technical direction, and execution.
Own the AI security runtime platform for high-throughput, low-latency inline security decisions across Catos global cloud and PoPs.
Design the orchestration layer for running GPU models, CPU heuristics, and security logic as one production engine.
Own production readiness: observability, SLOs, autoscaling, reliability, rollout, rollback, and operational health.
Own the model lifecycle platform: registry, versioning, deployment, monitoring, and safe production rollout.
Work closely with research and algorithm teams to productionize AI security models and algorithms at scale.
Define the long-term platform strategy for AI runtime and model serving at Cato.

This is a Senior AI Software Engineer role within our companys AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products.
Responsibilities
Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging.
Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features.
Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems
Develop and maintain high-quality, scalable, and efficient code.
Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems).

Required Senior Algorithm Engineer (RTB)
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Algorithm Engineer on the Algorithms team in our Tel Aviv office, youll play a vital role in building machine learning models that power real-time bidding and optimize billions of daily auctions. Youll design and evolve large-scale ML solutions that drive bid optimization, price prediction, win-rate prediction, and auction strategy. Working at the intersection of machine learning, data, and engineering, youll take models from research and experimentation through production, creating solutions that directly impact advertiser performance, publisher revenue, and marketplace efficiency.
How youll make an impact:
Design, train, and deploy machine learning models for bid optimization, price prediction, win-rate prediction, CTR/CVR estimation, calibration, and auction optimization.
Own the full machine learning lifecycle, from research and prototyping through production deployment, A/B testing, monitoring, and optimization.
Build and evolve large-scale ML models serving low-latency, high-throughput production traffic.
Analyze auction and marketplace data to identify modeling opportunities and translate insights into measurable business impact.
Partner with Product, Engineering, and Business teams to translate marketplace goals into scalable machine learning solutions.
Mentor junior engineers and contribute to technical design reviews, code reviews, and deep technical investigations.

We are looking for a Staff Algorithm Engineer to join our core Algorithm team
What You'll Do



Research and implement novel computer vision and algorithmic solutions for challenging real-world problems - spanning perception, learning, optimization, and graph-based reasoning.
Own algorithm quality end-to-end: design experiments, evaluate results, and drive iterations until production reliability targets are met.
Work across disciplines - sharing models, methods, and insights with algorithm, data engineering, and product teams.
Monitor production model health proactively; identify degradation early and lead remediation efforts.
Integrate AI tools into your workflow and grow into the role of architect and team lead - designing the solution, then directing agents to build it.
Raise the bar on the team's technical culture through code reviews, knowledge-sharing, and rigorous algorithmic thinking.

Required Senior Algorithm Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Senior ML Engineer on the Matchmaking and Marketplace R&D unit in our Tel Aviv office, youll play a vital role in building machine learning models that power our real-time auctioneer and optimize billions of daily auctions. Youll design and evolve large-scale ML solutions that drive advertiser bids and expected outcomes for advertisers, publishers and the company itself. Working at the intersection of machine learning, data, and engineering, youll take models from research and experimentation through production, creating solutions that directly impact advertiser performance, publisher revenue, and marketplace efficiency.
How youll make an impact:
Design, train, and deploy machine learning models for CTR/CVR/value prediction
Own the full machine learning lifecycle, from research and prototyping through production deployment, A/B testing, monitoring, and optimization.
Build and evolve large-scale ML models serving low-latency, high-throughput production traffic.
Analyze auction and marketplace data to identify modeling opportunities and translate insights into measurable business impact.
Partner with Product, Engineering, and Business teams to translate marketplace goals into scalable machine learning solutions.
Mentor junior engineers and contribute to technical design reviews, code reviews, and deep technical investigations.

Required Algorithm Engineer (RTB)
As an Algorithm Engineer on the Algorithms team in our Tel Aviv office, youll play a vital role in building machine learning models that power real-time bidding and optimize billions of daily auctions. Youll design and evolve large-scale ML solutions that drive bid optimization, price prediction, win-rate prediction, and auction strategy. Working at the intersection of machine learning, data, and engineering, youll take models from research and experimentation through production, creating solutions that directly impact advertiser performance, publisher revenue, and marketplace efficiency.
How youll make an impact:
Design, train, and deploy machine learning models for bid optimization, price prediction, win-rate prediction, CTR/CVR estimation, calibration, and auction optimization.
Own the full machine learning lifecycle, from research and prototyping through production deployment, A/B testing, monitoring, and optimization.
Build and evolve large-scale ML models serving low-latency, high-throughput production traffic.
Analyze auction and marketplace data to identify modeling opportunities and translate insights into measurable business impact.
Partner with Product, Engineering, and Business teams to translate marketplace goals into scalable machine learning solutions.
Mentor junior engineers and contribute to technical design reviews, code reviews, and deep technical investigations.

We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges.
A day in the life and how youll make an impact:
Design and Development of novel, robust and efficient Machine Learning/ Deep Learning algorithms for major Vision challenges.
Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems.
Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data-centric AI methodologies (active learning, data curation).
Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for real-time inference constraints (on Edge/Cloud devices).