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At CodeValue , we specialize in delivering cutting-edge software solutions and driving innovation across industries. We are now looking for a Data Engineer to join our team and play a key role in building and optimizing large-scale Big Data systems in production environments.
Key Responsibilities
* Design, implement, and maintain Big Data pipelines in production.
* Work extensively with Apache Spark (2.x and above) , focusing on complex joins, shuffle optimization, and performance improvements at scale.
* Integrate Spark with relational databases, NoSQL systems, cloud storage, and streaming platforms
* Contribute to system architecture and ensure scalability, reliability, and efficiency in data processing workflows.

Experienced Data Engineer? Excellent team player?
Come join a great team to overcome meaningful cyber challenges!
Our Data Solutions Group is looking for an exceptional Python developer with Data Engineering experience.

We are looking for a talented and experienced big data engineer to join our cyber defence group to take over a cutting-edge data solution.
The successful candidate should have hands-on experience with big data processing technologies and architectures.
The candidate will join our growing team of analysts, developers, data scientists, and architects who design and develop innovative solutions to the most critical needs of our customers.
Responsibilities
Designing, architecting, implementing, and supporting our data pipelines and processing flows.
Collaborate with analytics department to analyze and understand data sources.+
Provide insights and guidance on database technology and data modelling best practices.
Insure the maintenance of data integrity, managing data and analysis flows with attention to detail and high responsibility.
Implementing algorithms with our data scientists.

Required Senior Analytics and Compensation Specialist, Temp
So, whats the role all about?
We are looking for a data-savvy professional that thrives in a fast-paced, global environment. The role combines business operations, people analytics, and operational execution capabilities.
How will you make an impact?
Lead the HR QBR (Quarterly Business Review) process and in other global HR processes: Track HR metrics progress and analyze people trends, provide insights, follow up on process progress, issue and analyze reports. Aggregate action items & proactive follow up to completion
People analytics reports and analysis to support the Executive VP HR and company-wide HR decisions and agenda
Own the methodology for running cross-company HR processes to ensure continuous improvement: previous lessons learned, kick-off, summary, and knowledge management
Working with field HR HRBPs and HR Ops, supporting periodical analysis and ongoing needs
Ensure Global HR yearly work plan is on track and executed
HR governance on compensation and Job Architecture elements
Support global and regional compensation processes: data, analytics & insights.

Were seeking an experienced and visionary Data Team Lead to take end-to-end data ownership, managing 3 small teams of engineers, analysts and science, from high-level planning and architectural design to on-going engineering management and strategic cross-functional collaboration.

As we evolve Perceptional AI to Reasoning and autonomous AI initiatives, at orcas solutions deployed at thousands of maritime vessels (cargo, cruising, tankers and more).



Responsibilities:

Lead, mentor, and grow high-performing data teams.
Define and maintain a forward-looking data roadmap aligned with the company AI and product strategy.
Build and maintain work plans that balance tech debt reduction, legacy migrations, alongside next gen. product deliveries.
Act as the central sync point between the Data teams and key stakeholders: Product, CSMs, UI/UX, R&D, Algorithm, System, and Infra.
Identify, prioritize, and resolve cross-team dependencies and roadblocks with a proactive, solution-oriented mindset.
Own and evolve the data platform architecture, including modeling, pipes and services.
Drive the modernization of the stack: enable Gen AI, serverless architectures, and scalable lakehouse and data processing patterns.
Overlook best practices put forward by the team: design patterns, code reviews, CI/CD, tests, infras management (e.g. aws cdk), APIs to other R&D teams.

We are looking for a Data Scientist to join our R&D team. To become part of our journey in helping digital publishers and businesses improve their business growth, empowering meaningful interactions across their digital assets, generating an undeniable increase in revenue, user engagement, conversions, and overall performance.
Build the next generation of ML algorithms for us. Focusing primarily on recommendation engines, personalization, pricing, prediction and causal inference models.
Our Story:
At the heart of every digital revolution, there's a story. Ours began in 2012, with a vision of creating a publisher video platform that offers all the necessary tools, innovation, and knowledge publishers need to fully optimize their websites with video.
Through machine-learning and AI technology, we empower publishers to own their video content and monetization strategies to maximize revenue. Our platform offers global publishers unparalleled access to best-in-class ad serving, monetization, content automation, and video recommendation.
Trusted by some of the leading publishers globally including The Arena Group, CBSi, Hearst, Nasdaq, VICE, and more, our platform helps publishers boost audience engagement and increase revenue. Our success is a direct result of our dedicated team located around the world and visionary backers including The Walt Disney Company, Saban Ventures, Viola Group, 83North, and Firstime Ventures.
At our core is a passion for reimagining the video space and an unyielding commitment to those who rely on us. And now, we're looking for remarkable talent like you to join the next chapter of our story.
Long story short, you will:
Design, build, automate, deploy and maintain machine learning production pipelines, utilizing cloud technologies such as cloud AI / Sagemaker.
Building RAG processes and utilizing LLMs for verius needs.
Deploy and monitor models in production (e.g. building artifacts, measuring model drift, etc.).
Implement and evaluate recommender engines and deep-learning techniques, to work in a production environment and run at massive scale.
Apply complex analytical techniques to derive actionable insights with very good communication skills to write and publish internal documentation to be used by technical and business teams.
Design and execute technical processes needed for experimentation to support an array of business problems, including experiment ideation, experimental design, monitoring, data analysis, code review and communication of results.
Keep up with machine learning research and commercial product offerings across a wide variety of machine learning fields
Role Key Deliverables: Own current recommendation engine modeling stack and its development processes (creation/specification of tasks, daily updates and commitment to deliverables), research and deploy incremental improvements.

Required Data Infrastructure Engineer
What Youll Do:
Design, implement, and enhance robust and scalable infrastructure that enables efficient deployment, monitoring, and management of machine learning models in production. In this role, you will bridge the gap between research and production environments, streamline data and feature pipelines, optimize model serving, and ensure governance and reproducibility across our ML lifecycle.
Responsibilities:
Decouple data prep from model training to accelerate experimentation and deployment
Build efficient data workflows with versioning, lineage, and optimized resource use (e.g., Snowflake, Dask, Airflow)
Develop reproducible training pipelines with MLflow, supporting GPU and distributed training
Automate and standardize model deployment with pre-deployment testing (E2E, dark mode)
Maintain a model repository with traceability, governance, and consistent metadata
Monitor model performance, detect drift, and trigger alerts across the ML lifecycle
Enable model comparison with A/B testing and continuous validation
Support infrastructure for deploying LLMs, embeddings, and advanced ML use cases
Manage a unified feature store with history, drift detection, and centralized feature/label tracking
Establish a single source of truth for features across research and production across research and production.

Required Data Engineer
As part of our Data Engineering team, you will not only build scalable data platforms but also directly enable portfolio growth by supporting new funding capabilities, loan sales and securitization, and improving cost efficiency through automated and trusted data flows that evolve our accounting processes.
Responsibilities:
Design and build data solutions that support our core business goals, from enabling capital market transactions (loan sales and securitization) to providing reliable insights for reducing the cost of capital.
Develop advanced data pipelines and analytics to support finance, accounting, and product growth initiatives.
Create ELT processes and SQL queries to bring data to the data warehouse and other data sources.
Develop data-driven finance products that accelerate funding capabilities and automate accounting reconciliations.
Own and evolve data lake pipelines, maintenance, schema management, and improvements.
Create new features from scratch, enhance existing features, and optimize existing functionality.
Collaborate with stakeholders across Finance, Product, Backend Engineering, and Data Science to align technical work with business outcomes.
Implement new tools and modern development approaches that improve both scalability and business agility.
Ensure adherence to coding best practices and development of reusable code.
Constantly monitor the data platform and make recommendations to enhance architecture, performance, and cost efficiency.

We are looking for a Tech Lead - Data Platform.
As a tech lead, you will take a leading part in designing and building the infrastructure for connecting and analyzing huge, privacy protected datasets in the cloud using Java, Spark and other technologies and mentor team members.
What You'll Do:
Design and develop platform capabilities for scalable data products tailored to enterprise customers
Collaborate with Product Managers, Software Engineers, and DevOps Engineers to gather requirements, create system and feature design documentation, and implement solutions across diverse environments
Write Java-based back-end code, leveraging Spark, various cloud services, and relational databases
Partner with the production team to define solutions, monitor services, troubleshoot issues, and identify cost optimization opportunities
Mentor and guide team engineers, providing support in their daily tasks and development
Build and use monitoring infrastructure to track services, troubleshoot problems, and optimize performance, throughput, and costs
Address privacy challenges to ensure the protection and confidentiality of consumer and patient data

where the creative arts meet technology. If theres one thing we all have in common, its a love of music and film, which is why we build innovative products to help global brands and individual creators make amazing videos. We revolutionized the industry with a radical new music licensing model that has since become the global standard. now the go-to platform for over 26M users worldwide. They range from top-tier global brands like Google, Apple, Amazon, Microsoft, and Calvin Klein to social creators, video editors, and more. Our products:: an all-in-one platform for video creation, including high-quality and curated royalty-free music, SFX, footage, templates, plugins, AI tools and more. Motion Array: the ultimate creator hub with top-tier templates, plugins, music, SFX, footage, AI voiceover, motion graphics, and more.
Were looking for a full-time data Engineer to join our data Engineering team in Tel Aviv.
As a data Engineer, you'll play a pivotal role in crafting and maintaining robust data solutions that empower analysts, data scientists, and diverse business units. Your proficiency in Airflow, Python, and SQL will drive the development and validation of data warehouse models, ensuring data trust and elevating the delivery and quality of insights.
Wake up for this:
* Create and sustain data solutions tailored to support analysts, data scientists, and business units.
* Develop and validate data warehouse models using Airflow, Python, and SQL.
* Ensure continuous data trust and optimize insight delivery and quality.
* Develop, orchestrate, and enhance data pipelines organization-wide, ensuring seamless data ingestion and transformation.
* Collaborate effectively with stakeholders, including data developers, systems analysts, data scientists, and software engineers

This role provides the opportunity to drive significant impact through scalable data solutions while working with a collaborative, growth-focused team. You'll work with cutting-edge AWS technologies, solve complex data challenges, and play a key role in shaping our data platform's future. You'll learn unique graph relations models and valuable graph database experience.

Were looking for a senior Data Scientist to lead into the next stage, utilizing our data assets for in-house business development, product development, and customer outreach.

You will work with large-scale data at the intersection of agronomy and commerce, designing and implementing algorithmic and machine learning solutions that power our data-driven platform. This will include predicting buying behaviors models, sales, and product recommendation models based on farmers' behavior, and combining this with relevant product recommendations. If youre passionate about turning complex data into real-world impact in agriculture, we are looking for you, a talented, detail-oriented person to join our team.

Were looking for a Product Analyst to join our Product team and play a critical role in unlocking the power of maritime data. Youll dive deep into complex datasets, ensuring quality, uncovering insights, and shaping the foundation for products and workflows built on AI. Your work will directly contribute to product innovation, customer impact, and the next generation of AI-driven maritime solutions.

What will you do?

Extract, analyze, and interpret maritime data using Python, SQL, and other data tools, working across sources such as Rockset, MongoDB, and S3.
Ensure data quality, accuracy, and consistency, supporting both product development and Generative AI-powered workflows.
Identify patterns, anomalies, and emerging risks within large, complex datasets to drive actionable insights for customers and internal stakeholders.
Collaborate with product managers, engineers, and data scientists to optimize data pipelines, workflows, and models.
Support the development of strategies for handling structured and unstructured data, contributing to scalable, automated solutions.
Visualize and communicate findings effectively, using tools such as Matplotlib, Grafana, or Redash, tailored for technical and non-technical audiences.
Apply domain knowledge of the maritime industry to contextualize data and generate meaningful insights for product workflows.
Conduct data integrity and QA checks, ensuring reliability for both operational use and AI model training.

Were rapidly growing and looking for another important piece of the puzzle.
Is it you?
We are looking for a highly motivated candidate to join our Data Science team If you are passionate about NLP \LLMs and have 4+ years in the field, this is for you!
What Youll Do:
Research, experiment, develop and productize advanced NLP, LLM and autonomous agent solutions in various domains such as classification, summarization, translation, information retrieval and AI assistant.
Use advanced deep learning and large language models, to enhance Shields ability to find the needle in a haystack in the world of structured & unstructured data of financial electronic communication.
Conduct rigorous experimentation, analysis, and optimization to ensure performance, efficiency, and scalability.
Develop processes, tools and frameworks to monitor and analyze model performance and data accuracy
Innovate, develop, and test state-of-the-art approaches to solve our challenging problems: domain adaptation, fine-tuning, prompt engineering, zero- and few-shot learning, autonomous agents, using open and close large language models.
Assist and mentor other team members in the implementation and research
Collaborate closely with domain experts, product and engineering teams to translate research breakthroughs into scalable commercial products
Identify the latest technology to improve our AI capabilities in a variety of languages and help shaping our AI roadmap

we are a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc.). The company offers an award-winning disruptive solution; a sensor free approach to smart infrastructure. The company is VC backed and in the revenues stage.
Combining pioneering technology in optical fiber sensing with state-of-the-art machine learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly.
Our technology turns the optical fiber embedded along high‑voltage lines into a national‑scale sensor network. By measuring real‑time wind and thermal conditions continuously along each line segment, we transform the grid into a smart, self‑aware network whose capacity is assessed accurately and dynamicallyincreasing current flow through the grid so more renewable projects can connect and more electric vehicles can charge.
Conventional grid‑monitoring depends on scattered line‑mounted sensors that are highly expensive and do not scale. Our solution converts the optical fiber running inside the shield wire into a continuous, high‑resolution sensor array that observes every meter of conductor in real time. This array of acoustic sensors produces a continuous flow of high-resolution waveforms, which is enriched with topographic, asset, and weather context.
We are looking for a Senior Data Scientist to join our journey to reinvent how power‑grid capacity is unlocked. The ideal candidate combines deep expertise in AI, physics, and engineering, with a strong track record in handling raw sensor and time-series data. They should excel in signal processing, statistical modeling, and building production-grade analytics and data pipelines. The role demands both software engineering skill and rigorous, safety-conscious development, as it impacts critical infrastructure.
What Youll Do:
Low‑Level Signal Processing Transform raw millisecond‑scale waveforms into meaningful features: design signal processing pipelines, extract spectral and temporal signatures of wind‑induced motion, and craft features that power the next layers of modelling.
Research, train, and optimize models that infer local wind speed and direction, conductor temperature and strain, and detect anomalous eventsleveraging cutting‑edge AI techniques to explore a fascinating, largely untapped domain.
Deliver physical and mathematical insights from the data; work closely with academic partners to design preprocessing, augmentation, and physics‑context layers that translate wind‑induced vibrations into accurate wind metrics.
Write, test, and maintain reliable code that operates 24/7 in production and integrates seamlessly with utility systems.
Shape the teams data roadmap, mentor peers, and champion best practices in MLOps, experimentation, and documentation.