דרושים » תוכנה » Real-Time AI Database Engineer

Join us at our company, a global fintech leader (NASDAQ; TASE: NYAX) revolutionizing the world of cashless payments, consumer engagement, and business management solutions. With more than 1,200 employees across 12 offices worldwide. At our company, youll be part of a diverse and innovative community where your work makes a real impact and helps shape the future of payments.
Syte is an image recognition solution for retailers in different verticals such as fashion, home, furniture, DIY etc. We offer AI-powered product recommendation and discovery platform. Our solutions include visual search, automated product tagging, advanced personalized recommendations, and more.
We are currently looking for a Senior Machine Learning Engineer to design and implement scalable and integrate machine learning solutions into production. You will work with modern technologies like Node.js, Python, Kafka, MongoDB, and OpenSearch, AirFlow, while driving architectural decisions and CI/CD best practices. This role combines backend engineering excellence with ML deployment expertise.
The Senior Machine Learning Engineer will report directly to the Director of R&D.
Your key responsibilities will include:
Architect and develop MLE services using Python, ensuring high performance, reliability, and scalability.
Collaborate with Data Science teams to productionize ML models (model serving, monitoring, retraining pipelines).
Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring.
Design and implement system architecture for distributed, event-driven systems.
Integrate and optimize Kafka for real-time data streaming and event processing.
Design and manage MongoDB schemas and queries for optimal performance.
Implement and maintain OpenSearch clusters for search and analytics use cases.
Ensure security, observability, and fault tolerance across all services.
Mentor team members and contribute to engineering best practices.

We are seeking a highly skilled Senior Software Engineer to join our team responsible for large‑scale data processing, distributed computation, and performance‑critical backend services. This role is ideal for an experienced backend engineer with a strong Python background who has built and optimized data pipelines at scale. You will design, build, and optimize systems that process large volumes of data using technologies such as Python, Databricks, and modern cloud‑native tooling. This is a senior technical position where architectural thinking, hands‑on coding ability, and ownership of end‑to‑end data workflows are essential.

Responsibilities
Design, develop, and maintain scalable, high‑performance backend services in Python.
Build and optimize large‑scale data processing pipelines running on Databricks.
Implement efficient algorithms and data transformations to support analytical and operational needs.
Optimize performance, throughput, and reliability of distributed data workflows.
Collaborate closely with Data Scientists, Product Managers, and other engineering teams to translate requirements into scalable solutions.
Implement monitoring, alerting, and observability for data workloads.
Ensure code quality through best practices such as code reviews, testing, CI/CD, and documentation.
Contribute to architectural decisions and technical strategy for the data platform.
Troubleshoot production issues, perform root‑cause analysis, and optimize system stability.

We are looking for a Software Engineer specializing in Deep Learning to join research department.
While vision and language models have become increasingly commoditized, proprietary deep learning models are unique, fast-evolving, and deployed in live trading across the worlds most efficient and sophisticated financial markets. Operating in this environment presents distinct scaling challenges and continuous opportunities for optimization. Success in this role requires first-principles thinking and a deep understanding of the engineering trade-offs behind high-performance DL systems.
This is a pivotal role within research organization. You will work closely with researchers and engineers across the company, training deep learning models on massive compute clusters and adapting them for production serving under strict and non-trivial constraints.

We are looking for a highly motivated R&D Software Engineer with strong algorithmic thinking, problem-solving skills, and hands-on software development experience. While experience in signal processing, communications, DSP, or RF is a strong advantage, it is not a requirement.

This role is ideal for engineers who enjoy tackling complex problems, designing practical solutions, and turning ideas into working systems. You will work in a multidisciplinary environment at the intersection of algorithms, software and hardware, with real impact on end products.


Design and implement algorithms and software solutions for complex problems
Develop high-quality, production-ready code in C++ and Python
Take ownership of features and components from concept through implementation and validation
Build prototypes, run experiments, and iterate quickly based on results
Participate in code reviews, architecture discussions, and technical decision-making
Document designs, trade-offs, and implementation details

Were looking for engineers who are proactive, curious, and take full ownership of their work. In this role, youll have the opportunity to drive real impact, shape the direction of our product, and grow as a technical leader.
You will:
Take end-to-end ownership of features-from design and implementation to deployment and ongoing improvement
Build high-quality, scalable, and resilient systems using modern engineering practices
Work closely with PM, design, and security experts to define and deliver customer-facing experiences
Drive technical direction and make thoughtful tradeoffs that balance speed, quality, and long-term maintainability
Bring a strong sense of initiative-identifying opportunities, raising issues early, and pushing ideas forward
Qualifications
Minimum Qualifications
B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent.
3+ years of professional software development experience.
Strong expertise in C/C++ and/or Rust.
Hands-on experience with at least one of:
Windows internals (process model, memory manager, IO manager, registry, drivers/WDF/KMDF)
Linux kernel development (modules, syscalls, device/IO subsystems, scheduling, security models)
Experience with low-level debugging
Solid understanding of networking or security protocols, memory safety, and concurrency primitives.
Ability to independently plan, design, and deliver engineering components in an ambiguous environment.

We are looking for a passionate software engineer to join our validation software development team. You'll have the unique opportunity to build the validation infrastructure and frameworks that kernel engineers rely on, while also validating kernel features that support our silicon and product roadmap - including memory management, concurrency, scheduling, power transitions, kernel/user boundaries, CPU tracing, and more. You'll be given the ownership and agency to influence the future direction of our products.

Successful candidates will join a multifaceted team responsible for building validation infrastructure and qualifying the latest kernel technologies on all our products, from watches to laptops, including unreleased prototypes. Our team collaborates with software development and validation teams around the world and is involved throughout the development lifecycle, from initial design until we ship to the customer.

Responsibilities:
- Designing, building, and maintaining scalable validation infrastructure, test frameworks, and CI/CD pipelines that enable kernel engineers to efficiently qualify their work across a wide array of Apple devices.
- Developing tooling and automation that improves test reliability, execution speed, and coverage reporting.
- Defining validation strategies, test plans, and testing methodologies for kernel technologies.
- Planning and developing automated test suites to validate new and existing kernel features.
- Independently managing efforts across cross-functional teams and communicating quality status to stakeholders.

Required Software Engineer
Powerstore Data Path Engineering team constantly push the boundaries of what is possible in the world of Big Data storage and distributed systems. We are a true systems company and work at every layer of the storage stack, including all aspects of operating systems and file systems, distributed algorithms, high-performance protocol stacks, and next-generation virtualization technology.
Join us as a Software Engineer on our Data Path Engineering team in Herzliya, Israel to do the best work of your career and make a profound social impact.
What youll achieve:
You will be part of Engineering development team, where software engineers constantly push the boundaries of what is possible in the world of storage and distributed systems. We are a true systems company and work at every layer of the storage stack, including all aspects of operating systems and file systems, distributed algorithms, high performance protocol stacks, and next-generation virtualization technology.
You will:
Participate in the preparation, review and evaluation of software/storage requirements and specifications
Develop of core Software - using mainly C/C++, Python
Prepare written specifications for tasks of varied complexity from verbal requirements
Use defined software lifecycle methodologies
Review and implement test strategies for software products
Take the first step towards your dream career
Every team member brings something unique to the table.
Job ID:R287349.

We are hiring Senior and Staff ML Engineers that sit within Safety Systems / autonomy organisations, building critical behaviours for Level 2 to level 4 driving. It is highly product-focused: you will train and iterate on end-to-end driving models and get them shipped into the car on a fast timeline measured in months. The opportunity is to own the full loop from data and training through evaluation and on-road validation, with direct impact on high-priority commercial deliveries (including the Nissan MVP). You will join a small, high-ownership teams at the point of rapid growth, where execution and real-world outcomes matter.
Key responsibilities
Develop the AI driver model architecture and training algorithms to introduce and enhance the safety behaviors for L2/L3/L4
Own key parts of the training model lifecycle, including evaluation strategy, success metrics, and iteration planning.
Mine, bucket, and curate real-world and synthetic data to teach specific driving behaviours, and implement data schemes to support training.
Run and analyse on-road and offline experiments, translate results into clear next steps, and drive improvements through repeated training cycles.

As a Cloud Architect, you will serve as a technical focal point, driving strategic architectural decisions that shape the future of our globally distributed platform.
Platform & Scale Leadership: Lead the architectural efforts to modernize and significantly scale the companys infrastructure across multiple geographies and heterogeneous cloud providers.
Cross-Organizational Influence: Work with other groups in the organization to deeply understand their needs and translate them into concrete, production-ready capabilities and platform offerings.
Multi-Cloud Data Strategy: Define and champion a comprehensive, petabyte-scale multi-cloud data strategy, ensuring optimal data governance, security, and cost-efficient flow for streaming ingestion, data lakes, and advanced analytics workloads across environments.
Microservices Design & Resilience: Provide high-level architectural oversight for the multi-cloud design patterns of our microservices, focusing on cross-cloud resilience, global traffic management, data locality, and failure domain isolation.
AI Transformation Leadership: Lead the AI transformation initiatives aimed at radically enhancing the developer experience, introducing intelligent automation, and leveraging generative AI models to accelerate software delivery, testing, and operational efficiency.
Strategic Alignment: Foster cross-group alignment and build consensus among engineering leaders and business stakeholders for strategic platform projects, translating complex technical roadmap items into clear, measurable business outcomes.
Architecture Definition: Help define the technical vision, architecture, and long-term directions of the Cloud Platform group and the wider R&D organization.
Engineering Excellence: Be a champion for engineering excellence, setting high standards, mentoring engineers across the group to foster solid architectural principles, and supporting their professional growth.
Architect Forum Participation: Be a key member of the companys architect forum, participate in complex technical discussions, and facilitate effective, org-wide decision-making processes.

Data has never been more valuable and vulnerable. As cybercriminals become more sophisticated and regulations more strict, organizations struggle to answer one key question: Is my data safe?"
At our company, we see the world of cybersecurity differently. Instead of chasing threats, we believe the most practical approach is protecting data from the inside out. Weve built the industrys first fully autonomous Data Security Platform to help our customers dramatically reduce risk with minimal human effort. At our company, we move fast. Were an ultra-collaborative company with brilliant people who care deeply about the details.
Together, were solving interesting and complex puzzles to keep the worlds data safe.
We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.
The FinOps Technical Manager leads cloud cost operations, driving cost optimization and governance across multi-cloud environments. This role combines technical expertise with strategic leadership to align cloud spend with business objectives while fostering a culture of cost accountability.
Key Responsibilities:
Strategic Leadership
Champion cost-awareness across teams and influence architectural decisions for efficiency.
Lead cross-functional initiatives to improve cloud economics and operational excellence.
Team Management
Provide hands‑on technical guidance on cloud architecture, cost‑efficient design patterns, and optimization best practices. Foster strong collaboration between finance, DevOps, and engineering teams to ensure shared ownership of cloud costs
Cloud Cost Management
Monitor and analyze cloud spend across AWS, Azure, and Kubernetes clusters.
Identify optimization opportunities by diving into current system architecture/ flows and implementation and resent actionable recommendations to leadership.
Be able to challenge current and future technological and architecture decisions in favor on cost optimization.
Ability to detect bad designs and implementations that cause high spend.
Automation & Tooling
Oversee automation of cost reporting and anomaly detection.
Evaluate and implement tools and integrations for real-time visibility.