דרושים » תוכנה » Software Developer GenAI Systems

We are looking for an enthusiastic Junior Software Developer with an interest in GenAI technologies to join our innovative team. The ideal candidate will have foundational knowledge of Python programming, database concepts, and experience with Retrieval Augmented Generation (RAG). You will work alongside experienced developers to build and maintain cloud-native applications, gaining valuable experience with cutting-edge GenAI technologies in a supportive learning environment.
What You'll Do: Assist in developing and maintaining Python -based microservices with AI capabilities under guidance from senior team members. Learn to implement and optimize PostgreSQL database queries for AI applications. Support the development of RESTful APIs and contribute to integrating AI models into our systems. Gain hands-on experience working with foundation models from various providers in the AWS ecosystem. Apply prompt engineering techniques and best practices for GenAI applications. Contribute to building reusable components for AI model integration. Assist with data processing pipelines between knowledge bases and AI models. Participate in CI/CD processes for testing and deployment of AI systems. Develop understanding of responsible AI practices and implementation strategies.

Position Intro:we are the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. we have been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

We are looking for a DevOps Engineer to join our expanding team, responsible for cloud technologies, software development life cycle processes, and 24/7/365 production reliability. You will be promoting DevOps practices and collaborating in an engineering environment, where you will work closely with software architects, developers, and support engineers, to provide solutions to enable innovation and support our customers. What you’ll do: Identify, integrate, and adapt new cloud technologies to meet evolving needs Ensure high availability, reliability, and performance of Earnix’ services Develop and maintain CI/CD pipelines, tools, and processes Build and manage the Earnix platform and automation using Infrastructure as Code (IaC) principles Troubleshoot and resolve issues across development, testing, and production environments Document infrastructure, processes, and configurations for knowledge sharing and future reference

Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.

we are hiring a Software Engineer to help revolutionize the world of observability. Using cutting-edge AI-driven technology, we are redefining how organizations monitor, analyze, and optimize their systemsmaking observability more intelligent, efficient, and accessible than ever before. As we scale, we seek top talent to push the boundaries of innovation and shape the future of AI-powered observability. If youre passionate about solving complex challenges and building game-changing technology, join us in transforming how the world understands and interacts with data.
Responsibilities:
End-to-end development and ownership of products and features, from design to scalable and predictable production behavior
Solve diverse and complex problems in a high-scale, cloud-native environment
Collaborate with other engineers and product managers to improve product functionality, scalability, and performance
Design, develop, and maintain robust, secure, and efficient software solutions
Ensure high system reliability by implementing best practices in monitoring, observability, and automation
Review code, architecture, and data to identify and troubleshoot technical and performance issues
Work with AI/ML teams to integrate AI capabilities, including model monitoring, evaluation, and fine-tuning.

We are seeking a highly skilled and motivated Machine Learning Engineer to join our Data Science Engineering team. The ideal candidate will have a deep understanding of machine learning infrastructure and solutions, enabling data scientists and engineers to efficiently develop, deploy, and maintain models in production by delivering a scalable and high-quality solution. This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams.
Key Responsibilities:
Develop and maintain machine learning infrastructure and solutions to support the efficient development, deployment, and maintenance of models in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models.
Design and implement software architecture for machine learning solutions.
Optimize model deployment and serving using industry best practices with CPU, GPU, and external APIs.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Collaborate with the DevOps team to establish best practices for MLOps.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning and related technologies.

We are seeking a backend engineer with a strong foundation in building scalable, high-performance systems and a deep understanding of cloud infrastructure, distributed systems, and data pipelines. This role focuses on designing and optimizing backend services that support our machine learning (ML) operations and real-time personalization capabilities.

We foster a professional environment where experienced engineers collaborate to drive technical excellence, continuously improving our backend architecture and infrastructure. As a Backend Engineer, you will play a key role in building and maintaining the backend services that power our ML infrastructure, ensuring efficiency, scalability, and reliability.

Role & Responsibilities:
- Design, develop, and optimize backend services that support ML pipelines, APIs, and real-time decision-making systems.
- Architect and implement scalable and reliable data processing workflows, integrating ML models into production environments.
- Build and maintain infrastructure for efficient model deployment, monitoring, and versioning.
- Ensure high availability, performance, and security of backend services.
- Lead initiatives to improve system architecture, reduce technical debt, and enhance development processes.
- Stay up to date with the latest advancements in backend technologies, cloud computing, and distributed systems.

R-241031

We are seeking a backend engineer with a strong foundation in building scalable, high-performance systems and a deep understanding of cloud infrastructure, distributed systems, and data pipelines. This role focuses on designing and optimizing backend services that support our machine learning (ML) operations and real-time personalization capabilities.

We foster a professional environment where experienced engineers collaborate to drive technical excellence, continuously improving our backend architecture and infrastructure. As a Backend Engineer, you will play a key role in building and maintaining the backend services that power our ML infrastructure, ensuring efficiency, scalability, and reliability.

Role & Responsibilities:
Design, develop, and optimize backend services that support ML pipelines, APIs, and real-time decision-making systems.
Architect and implement scalable and reliable data processing workflows, integrating ML models into production environments.
Build and maintain infrastructure for efficient model deployment, monitoring, and versioning.
Ensure high availability, performance, and security of backend services.
Lead initiatives to improve system architecture, reduce technical debt, and enhance development processes.
Stay up to date with the latest advancements in backend technologies, cloud computing, and distributed systems.

Youll work in an exciting environment alongside some of the most innovative people in the industry, using cutting-edge tools and technologies. you have the opportunity to directly influence the products and solutions used by our clients worldwide, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN and thats just the beginning of what we have to offer! Join us and be a part of the best tech team as we Fuel The Fandom.

We are looking for a Senior GenAI/NLP Algorithm Developer to join us in research and development of our next-generation automatic sports video content engine. If you are passionate about state-of-the-art NLP and Generative AI research we are looking for you!

What youll do:

The teams main focus: NLP & Generative AI.
Research and develop end-to-end real-time solutions for sports content automation using state of the art deep learning algorithms for text, speech, audio and data analysis.
Full R&D cycle, from problem definition and research to implementation and productization with a high level of autonomy.
In addition, part of the role & responsibilities will be:
Design, develop and implement state-of-the-art Generative models, prompt engineering and classical ML/NLP techniques to create high-quality solutions for demanding product-oriented NLP tasks.
Engage in collaboration with product, account, and customer success teams to establish success criteria and convert them into measurable objectives and quantitative measures.
Conduct training and evaluation of models within practical production scenarios.

We are seeking a highly skilled and motivated Engineering Tech Lead to join our Data Science Engineering team. The ideal candidate will have a deep understanding of software development and the ability to guide technical solutions.
This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams. As an Engineering Tech Lead, you will play a crucial role in exploring and investigating solutions and technologies, contributing to technological and architectural decisions with a hands-on approach.
Key Responsibilities:
Develop and maintain software infrastructure and solutions to support the efficient development, deployment, and maintenance of machine learning models and our surveillance pipe solution in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models and a fully integrated scalable solution.
Design and implement software architecture for machine learning solutions.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning, software development, and related technologies.

We are looking for a highly skilled and experienced Performance Tech Lead to drive our performance engineering strategy and ensure our systems are highly scalable, reliable, and efficient.

This role is a unique opportunity to combine technical leadership, hands-on optimization, and cross-team collaboration, ensuring performance best practices are embedded across the development lifecycle.

As a Performance Tech Lead, you will define and implement performance testing frameworks, analyze system bottlenecks, and work closely with development, DevOps, and architecture teams to optimize application and infrastructure performance.

You will also provide performance as a service infrastructure, developing self-service tools and frameworks that enable development teams to independently run, analyze, and fine-tune performance tests based on their specific needs.

This role requires deep hands-on expertise, strong analytical skills, and a proactive approach to performance optimization.

Your Role & Impact:
Architect, develop, and scale performance testing infrastructure for load, stress, endurance/longevity, and scalability testing.
Provide performance as a service, building self-service performance testing frameworks that allow development teams to execute and analyze tests autonomously.
Establish and enforce performance KPIs, ensuring optimal system behavior under various workloads.
Conduct in-depth performance analysis, identifying and resolving bottlenecks in APIs, databases, agent, caching, and distributed systems.
Lead the adoption of performance best practices, embedding them into the development and CI/CD pipelines.
Provide mentorship, best practices, and technical guidance to engineering teams, ensuring a performance-first mindset.
Enhance observability and monitoring capabilities, implementing APM tools like Prometheus/Grafana.
Analyze customers incidents, proactively identifying trends and areas for performance improvement.
Advocate for a shift-left approach, ensuring performance considerations are addressed early in the SDLC.

As a DevOps Engineer, you will join our data & engineering team and design and manage scalable, cloud-based infrastructure focused on big data and machine learning. You will ensure high-scale production environments are reliable, secure, and efficient, supporting seamless ML/AI deployments.

What will you do?

Design, build, and maintain scalable and reliable infrastructure for our big data applications
Automate the deployment and scaling of our applications using Kubernetes and related technologies
Implement and maintain security and compliance protocols
Monitor and troubleshoot infrastructure and applications
Collaborate with product teams to define and implement infrastructure requirements
Stay up-to-date with the latest industry trends and technologies
Manage and optimize large GPU clusters