דרושים » תוכנה » ML Engineer

We are on the search for a Senior Machine Learning Engineer who will join our Data team in Tel Aviv.
As a Senior ML Engineer in a Data-Driven company, you will have a significant opportunity for impact. You will be part of the team that turns data into solutions that influence the product and drive strategic business decisions that shape the direction of the company.
Here are a few of the things you will do:
Play a significant role in transitioning to state-of-the-art technology
Collaborate with machine learning teams to design and implement seamless workflows for continuous model training, inference, and monitoring, including classical machine learning and LLM-based models
Develop, design, and maintain end-to-end ETL and ELT workflows, including data ingestion and transformation logic, involving different data sources
Enhance the scalability and performance of existing data pipelines, while working on building new data pipelines specifically for machine learning models
Become an expert in our data infrastructure, providing first-line triage and troubleshooting for key business partners with data queries
Maintain and improve existing processes running in production
Promote a culture of open dialogue with business partners for strategic agility in decision-making.
Develop systems and tools to empower the team to find answers independently
Liaise with engineers, product managers, and product analysts to understand data needs.

As part of this role, you will be responsible for designing, building, and maintaining our machine-learning platform. You will work closely with a team of engineers and data scientists to develop and implement new AI and ML capabilities, pipelines, and infrastructures that power our platform.

What am I going to do?
Design and implement scalable, efficient, and maintainable machine learning platforms and pipelines
Develop comprehensive tools and packages to enhance and support a diverse range of data science projects
Design and implement ETL/streaming data pipelines
Collaborate with data scientists and other engineers to develop and implement new AI models and algorithms
Monitor and optimize the performance of our machine-learning platform
Stay up-to-date with the latest trends and developments in machine learning and related technologies

We are looking for an experienced Algorithm Engineer to join our Vision Processor Unit (VPU) algorithm team.
In this role, you will be responsible for developing and optimizing both traditional image processing algorithms and AI-based solutions. You will take part in the full lifecycle of algorithm development, from research and prototyping to real-world implementation and optimization for high-performance systems.
Responsibilities
Develop and optimize image processing algorithms, including both traditional methods and AI-based approaches
Implement algorithms efficiently, ensuring high performance, scalability, and robustness in production systems.
Conduct performance analysis and identify areas for improvement in both algorithmic efficiency and system integration.
Work closely with cross-functional teams, including software engineers and system architects, to ensure optimal performance of algorithms on target platforms.

We are seeking a highly skilled Senior Machine Learning Engineer to join our dynamic Data Department. In this role, you'll work with petabyte-scale data to design, develop, and deploy state-of-the-art machine learning pipelines and systems. You'll build robust ML infrastructure using AWS services and orchestrate processes with Apache Airflow. If you're a passionate problem solver with a commitment to excellence and thrive in a collaborative environment, we offers a unique opportunity to make a significant impact. Here, your expertise will drive innovation and help shape the future of machine learning, all while working on groundbreaking projects at a massive scale.

What you'll be doing:
End-to-End Project Ownership: Take charge of feature design from concept through to deployment, ensuring robust, scalable solutions in a complex and dynamic environment.
Pipeline & Infrastructure Development: Architect and implement advanced machine learning pipelines that efficiently manage and process massive data volumes.
Collaboration & Teamwork: Embrace a team-first mindset"there is no I in team"actively supporting your peers while continuously learning and striving for excellence.
Problem Solving: Utilize your analytical skills to navigate technical challenges and deliver high-quality results on schedule, all while taking full ownership of your projects.

Our Data Science team is opening its gates and looking for an experienced ML Engineer.
Our mission is to improve the quality of online conversations and build a healthier web where content creators of all kinds are empowered to thrive. As a product company, we partner with publishers and brands to forge strong, direct relationships with their audiences.
To achieve this, our Data Science team leads various initiatives around conversation moderationthink spam detection, toxicity, hate speech, or bot detection. We incorporate large-scale transformer models and LLMs at scale to make it happen.
In our work, we research, build, deploy and monitor solutions using the latest and greatest tools.
When you join our Data Science team, youll tackle everything from NLP classification challenges, RL model training for optimizing real time bidding, detection of bots using graph networks and scaling cutting-edge transformer models in production.
If youre ready to dive into huge amounts of data and have fun doing it - read on!
What Youll do:
Develop & Standardize ML Tooling: Build frameworks and reusable modules to streamline model deployment and code standardization
Innovate with NLP & LLMs: Fine-tune transformers or LLMs, train new models, and continuously explore advancements in language technologies
Automate Model Deployment: Train transformers to flag conversations and automate the process from training to deployment (using JFrogML & CircleCI)
Collaborate on Big Data: Use Databricks and AWS to wrangle datasets of epic proportions
Develop Production-Ready Code: Leverage Python, OOP, and best practices (packaging, pre-commit, linting) to turn POCs into production ready services - while collaborating with our incredible back-end/DevOps teams
Stay Curious: Keep up-to-date with the latest in ML, share knowledge with the team, and keep the data (science) party going.

Required Software Engineer, Machine Learning
We are embarking on the most transformative change to its business and technology in company history, and our Machine Learning Engineers are at the forefront of this evolution. By leading crucial projects and initiatives that have never been done before, you have an opportunity to help us advance the way people connect around the world.
The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems. You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. You will work alongside the worlds leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.
Software Engineer, Machine Learning Responsibilities
Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
Leading a team from a technical perspective to develop ML best practices and influence engineering culture
Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesize requirements and create effective feature roadmap
Code deliverables in tandem with the engineering team.

We are looking for experienced, creative and impact-oriented Algorithm Developers to join our team!

As an Algorithm Developer you will be responsible for building state of the art algorithms powering LLMs and agentic frameworks. You will be part of a multi-disciplinary team that also includes engineers and product professionals, all working together to bring our products to life.

You will take part in the full life cycle of our development process, deeply understand the problem we are solving, come up with algorithmic approaches for solving these problems, devise strategies for collecting necessary training data, train and evaluate large language models and other machine learning models and also be in charge of deploying these solutions in production.

Role and Responsibilities
Build the algorithms that power our various products
Develop production-grade solutions to challenging product-driven NLP tasks by combining language models, RL and classical ML/NLP.
Collaborate with product, sales and customer success teams to define success criteria and translate them into quantitative measures and objectives
Devise innovative strategies for collecting training and evaluation data
Train and evaluate models in realistic production scenarios
End-to-end ownership of the algorithmic components of our products, from design, through implementation and monitoring in production

We are looking for an experienced Machine Learning Engineer who is passionate about developing scalable and robust machine learning infrastructures and has a keen interest in leveraging advanced AI models to drive significant business impact. The job involves creating and maintaining high-performance model inference systems that support both batch and real-time AI processing in cloud and on-premises environments.
Responsibilities:
Design and implement scalable, high-availability machine learning inference architectures.
Develop robust systems that efficiently manage the deployment and operation of complex models like LLMs and anomaly detectors.
Utilize AWS technologies such as SageMaker, Lambda, SQS, and Redshift to optimize the performance and scalability of our machine learning infrastructure.
Collaborate with data scientists and AI researchers to ensure seamless integration and optimal performance of machine learning models.
Build and maintain monitoring systems to ensure the stability and efficiency of the machine learning infrastructure.
Troubleshoot and resolve issues related to model performance, infrastructure bottlenecks, and system failures.
Maintain strong communication skills and collaborate effectively within a dynamic team environment.

For many of us there’s that one podcast we never miss, and video content is part of our daily routine, whether it’s professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at Riverside, we know it well. That’s exactly why we built an AI-powered platform that helps content creators, podcasters, marketeers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.
Riverside’s technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.
About the Innovation Team At Riverside, the Innovation team is all about pushing the limits of AI to transform content creation. We work on everything from enhancing audio and video quality to automating production with machine learning, NLP, and computer vision. Whether it’s real-time rendering, intelligent editing, or new ways to process media, we turn cutting-edge research into practical tools that creators rely on. If you’re excited about shaping the future of media tech, you’ll fit right in.
On your day to day We’re on the lookout for a hands-on, experienced MLOps Team Lead to help build and grow our team at Riverside. You’ll play a key role in driving AI innovation by building fast, scalable, cost-efficient, and reliable ML infrastructure that enables our AI model development across multiple modalities and cloud environments. You’ll work closely with AI researchers, software engineers, and DevOps to create smooth ML workflows, manage large-scale GPU clusters, build data pipelines, and ensure everything runs efficiently. You’ll also mentor a team, drive a culture of excellence and good vibes, and take ownership of the employee's full lifecycle, from recruitment to growth and development.

We are looking for a strong, hands-on Data Scientist to join our Data Loss Prevention team.

In this role, you will join an R&D team that researches, designs, and develops Check Points data loss prevention cloud services, providing state-of-the-art AI-based data loss prevention solutions on a global scale.

Key Responsibilities


Join the research and development of new innovative capabilities for data loss prevention, involving advanced AI and algorithms.
Quickly iterate on design approaches based on data-driven research and user feedback.
Design and develop novel data-driven solutions that have the potential to deliver game-changing results involving advanced AI and algorithms.
Utilize Natural Language Processing (NLP) and large language models to enhance data loss prevention capabilities.
Work on web content categorization as part of the broader scope of data protection.
Collaborate with Cyber Researchers, Analysts, Fellow programmers, and Data Scientists to deliver machine learning and analytics solutions.
Push the solutions all the way to large-scale production systems. Understand the architectural constraints of such systems and work with a cross-organizational engineering and product team to quickly transition from prototype to a scalable robust implementation.