דרושים » תוכנה » Data Engineer & MLOps Specialist

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

We are looking for a Senior Backend Engineer to join our AI/ML team. In this role, youll work closely with data scientists to transform cutting-edge machine learning models into scalable, production-ready services. You will take ownership of designing, building, and maintaining the backend systems that power our AI-driven features.

This is a key position that bridges the gap between data science and production engineering, ensuring high performance, reliability, and maintainability of our ML-powered products.

Responsibilities:
Collaborate with data scientists to understand modeling outputs and convert them into deployable services.
Design and develop robust, scalable backend systems and microservices to support AI use cases.
Own the deployment and monitoring of ML models in production (with CI/CD, logging, observability).
Implement data processing pipelines in support of model training and inference.
Ensure software adheres to best practices in architecture, testing, and documentation.
Optimize model inference for latency, throughput, and resource efficiency.
Contribute to design decisions and technical strategy alongside AI and infrastructure leads.

we are looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, automation, and scalable AI platforms.
If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouragedthis role is for you.
Responsibilities:
 Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environments (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.

We are looking for a Senior ML Engineer.
As a Senior ML Engineer , you will lead the design, deployment, and maintenance of production-ready machine learning systems that power legal insights at scale. Youll work across disciplinesintegrating LLMs, building pipelines, and optimizing infrastructureto deliver real-world impact.
Youll gain full ownership over the systems you build, from selecting the tools and platforms to deploying services in production. Youll work closely with DevOps and Data Engineering to ship robust solutions that drive meaningful change in the world.
Responsibilities :
Design and implement production-grade ML systems, including APIs, batch jobs, and streaming pipelines using Databricks, MLflow, AWS/GCP.
Build and manage ML infrastructure, including data pipelines, model training, deployment, and monitoring.
Develop and maintain end-to-end ML/LLM pipelinesfrom data ingestion and labeling to synthetic data generation, model registry, and rollout.
Own and improve MLOps practices: automated testing, CI/CD, monitoring, alerting, and model governance.
Write clean, maintainable Python code and uphold best practices in engineering and documentation.
Collaborate with DevOps and Data Engineering teams to scale systems and improve performance.
Research and recommend the best tools, platforms, and practices to support ML at scale.

We are seeking a Senior Data Scientist to lead the development of personalization models that power our AI agents. In this role, youll design and deploy intelligent systems that understand each travelers preferences, intent, and behaviortransforming complex user journeys into effortless, hyper-personalized experiences.This is a high-impact, cross-functional role working closely with product managers, engineers, designers, and the AI/LLM platform team to create deeply personalized, autonomous travel assistance that feels like magic (but is all math and modeling underneath).
What Youll Do:
Design and build machine learning models that power personalization across our agentic platform, including traveler profiles, flights & hotels recommendation engines, and behavioral prediction systems.
Develop algorithms that adapt and learn from user behavior over time, channels, and modalities (text, voice, action).
Collaborate with PMs, engineers, and conversational designers to integrate ML into real-time decision loops, conversational agents, and proactive UX flows.
Own experimentation pipelines and performance evaluation, AB tests, offline metrics, and production agent behavior.
Work hands-on with structured and unstructured data (e.g., travel history, chat logs, user feedback, booking behavior) to extract insights and drive model improvement.
Define and maintain robust MLops practices: monitoring, retraining, feature pipelines, and real-time inference.
Stay current with the latest in recommender systems, LLM integration, embeddings, retrieval augmentation, and agentic reasoning to continuously evolve our approach.

Were looking for a Product Manager to lead LLM Infrastructure - a foundational role driving the development of systems that enable smarter, AI-powered decision making across the marketplace.

As the PM for LLM Infrastructure, youll shape the capabilities that turn unstructured data into structured, explainable, and actionable insights. Youll work closely with ML engineers, data scientists, and product leaders to design scalable tools and frameworks that support use cases across personalization, matching, search understanding, trust and safety, and more.

Your mission will be to build reliable and extensible LLM-based systems that serve as core building blocks for future-facing product innovation.

What am I going to do?
Define the product vision and roadmap for LLM infrastructure, aligning with long-term company strategy and cross-team needs.
Lead the development of scalable systems that extract meaning.
Structure from conversational and behavioral data.
Drive adoption of LLM capabilities across by building unified APIs, shared frameworks, and streamlined integration pipelines.
Partner with engineering, data science, and research teams to deliver high-quality infrastructure that powers AI-native product experiences.
Collaborate on system design and architecture decisions to ensure alignment between technical solutions and product scope.
Ensure reliability, scalability, explainability, and performance in all LLM-based systems.
Manage technical complexity and connect infrastructure efforts with clear business value.

We are looking for an experienced MLE Team Lead to lead our Machine Learning Engineering team as part of the Infrastructure group. AI/ML are core components of Navina unique technology, and a significant part of our technical edge. This is a unique opportunity to take a leadership role in building the infrastructure that powers the models driving Navinas products.

Youll lead a team of ML engineers in designing scalable production systems, collaborating with cross-functional stakeholders, and mentoring team members as we scale our ML platform and capabilities.

Responsibilities:
Provide technical leadership and team management for the Machine Learning Engineering team, including mentoring team members, and encourage ongoing personal and professional growth.
Define and drive the roadmap for ML infrastructure in collaboration with other technical leaders and data science team, ensuring alignment with broader engineering and organizational goals.
Remain actively involved in the architecture and development of systems that enable scalable and reliable model training, deployment, serving, and monitoring.
Own the engineering aspects of the ML lifecycle, including the design of efficient production-grade deployment mechanisms, robust observability and maintenance practices.
Work closely with data science, product, medical, and dev teams to understand evolving needs and deliver infrastructure and tooling that improve development velocity and model reliability.
Continuously evaluate emerging tools and best practices in ML infrastructure and thoughtfully integrate relevant technologies to strengthen the teams capabilities.

As a Software Engineer in the team, you will contribute to the design, development, and operation of our comprehensive data fabric an enterprise-grade system that enables data-driven decision-making and high-impact product features across our company. You'll work closely with a cross-functional team of engineers, product managers, and data experts to build scalable data infrastructure and intelligent data management capabilities that power internal and external services. You will:
Drive the development of sophisticated and robust logic and backend infrastructure that supports large-scale data and compute workflows.
Collaborate across teams to design solutions that meet performance, reliability, and security requirements.
Contribute to the automation and optimization of engineering processes, improving deployment velocity and system health.
Participate in the full software development lifecycle, from ideation and design to deployment and monitoring.
Help shape engineering standards, technical architecture, and operational best practices within the team.

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of machine learning, GenAI, and computer vision within the automotive sector. With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.
We are seeking a highly motivated and skilled Release Engineer to join our AIOps group. In this role, you'll play a critical part in bridging the gap between development and operations, ensuring the seamless qualification, deployment, and monitoring of our AI algorithms and infrastructure, and be responsible for the end-to-end operationalization of our core technology.
A day in the life and how you’ll make an impact:
* Manage the end-to-end release process of machine learning algorithms and infrastructure components, from qualification through deployment.
* Validate and test new algorithm releases to ensure they meet performance, stability, and compliance standards.
* Create and execute deployment plans across various environments (staging, production), ensuring minimal risk and downtime.
* Collaborate closely with AI researchers, MLOps, and software engineers to understand release requirements, share feedback, and resolve pre-release issues.
* Identify and drive automation opportunities within the release pipeline to improve efficiency, reliability, and traceability.
* Oversee updates to infrastructure components, ensuring compatibility and performance across systems.
* Monitor deployments, proactively identify issues related to model behavior or infrastructure anomalies, and drive resolution with relevant teams.
* Maintain clear and accurate release documentation, including version history, deployment notes, and incident reports.

we are seeking a Senior Data Scientist to drive the development and implementation of AI-based solutions that solve complex business challenges across our innovative SaaS platform. In this key role, youll work cross-functionally to lead end-to-end AI projectsfrom data exploration to deploymenthelping shape the future of our intelligent products and user experiences.
If youre passionate about machine learning, LLMs, and real-world impact, and thrive in a collaborative, high-velocity environment, wed love to connect.
What You Will Do:
Identify AI opportunities to enhance product experiences and operational efficiency.
Collect, analyze, and model diverse financial datasets to develop actionable AI Products.
Own the full AI solution lifecyclefrom problem definition to research, modeling, and hands-on implementation.
Break down complex problems into well-defined, structured work plans.
Collaborate closely with developers, product managers, and other stakeholders to integrate AI solutions seamlessly into products.
Stay up to date with AI, ML, and LLM trends, translating them into practical applications.
Provide technical leadership and mentorship to junior data scientists while balancing immediate delivery with long-term innovation.