דרושים » תוכנה » MLOps engineer

For many of us theres that one podcast we never miss, and video content is part of our daily routine, whether its 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. Thats 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. Riversides 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 its Real-Time rendering, intelligent editing, or new ways to process media, we turn cutting-edge research into practical tools that creators rely on. If youre excited about shaping the future of media tech, youll fit right in.
On your day to day We are looking for a backend Engineer to join our Machine Learning team and help build the infrastructure that powers cutting-edge AI models in Natural Language Processing ( NLP ) and Computer Vision (CV). In this role, you'll collaborate closely with Machine Learning and video-processing teams to shape the AI-driven future of our product.

We are seeking an experienced Data Scientist with a strong background in AI engineering to join our AI Platform team. This role focuses on developing and fine-tuning advanced machine learning models, including LLMs, to support various product teams across . As a member of the AI Platform team, you will collaborate with cross-functional teams to build scalable, efficient, and robust AI solutions that serve diverse business domains.

What am I going to do?
Take leading roles in foundational AI projects across : developing and fine-tuning LLMs, building reusable components for generative AI, supporting real-time predictions, and enabling streaming data utilization across online models.
Provide advanced Data Science and AI Engineering solutions end-to-end - from research and prototyping to robust production-grade implementations.
Own the design, training, and evaluation of models tailored for tasks like summarization, classification, semantic matching, personalization, and more.
Drive innovation by exploring new model architectures, training techniques, and fine-tuning strategies aligned with business needs.
Lead and mentor other team members, setting high standards for technical excellence and knowledge sharing.
Continuously identify new opportunities to evolve the platforms capabilities and streamline how AI is built and adopted across .

We are seeking an experienced Data Scientist with a strong background in AI engineering to join our AI Platform team. This role focuses on developing and fine-tuning advanced machine learning models, including LLMs, to support various product teams across Fiverr. As a member of the AI Platform team, you will collaborate with cross-functional teams to build scalable, efficient, and robust AI solutions that serve diverse business domains.

What am I going to do?:

* Take leading roles in foundational AI projects across Fiverr: developing and fine-tuning LLMs, building reusable components for generative AI, supporting real-time predictions, and enabling streaming data utilization across online models.
* Provide advanced Data Science and AI Engineering solutions end-to-end - from research and prototyping to robust production-grade implementations.
* Own the design, training, and evaluation of models tailored for tasks like summarization, classification, semantic matching, personalization, and more.
* Drive innovation by exploring new model architectures, training techniques, and fine-tuning strategies aligned with business needs.
* Lead and mentor other team members, setting high standards for technical excellence and knowledge sharing.
* Continuously identify new opportunities to evolve the platform’s capabilities and streamline how AI is built and adopted across Fiverr.

Equal opportunities:
At Fiverr, we’re not about checklists. If you don’t meet 100% of the requirements for this role but still feel passionate about the position and think you have the right skills and qualifications to excel at it, we want to hear from you. At Fiverr, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. Fiverr is proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, Fiverr will provide accommodation to individuals with disabilities or a special need.

We are scaling our AI team with mission-driven individuals eager to shape the future of mobility. As a Machine Learning Model Evaluation Engineer (Computer Vision), youll collaborate closely with our research team to design, build, and optimize data infrastructure and annotation workflows. You will be the focal point between the team and the annotation team, ensuring high-quality labeled data and efficient processes. Additionally, you will help optimize our algorithms, analyze performance metrics, and define optimal operating points to enhance model effectiveness. Your work will directly contribute to pushing the boundaries of Vision AI and advancing our cutting-edge projects.


RESPONSIBILITIES

Model Evaluation
Work closely with the research team to evaluate model performance and define optimal operating points using precision, recall, and other ML evaluation metrics.
Annotation Management
Be the focal point for annotation processes to ensure high-quality labeled data and streamlined workflows.
Database Management
Manage and maintain internal research databases for data-driven decision-making.
Cloud Infrastructure
Develop, maintain, and optimize cloud-based data infrastructure (AWS, GCP).
Benchmarking Framework
Build and maintain a benchmarking framework for continuous algorithm performance evaluation, including human-in-the-loop pipelines.
Dataset Curation
Curate training and testing datasets by querying databases and annotations, and by running data quality and auto-labelling tools.
Model Execution
Run algorithms and deep-learning models at scale.

Were seeking an experienced AI/ML Platform Engineer to join our Foundations team, the group behind our next-generation GenAI platform powering innovation across the company and beyond. This team is building scalable, high-performance AI systems for both internal users and external customersdesigned to run seamlessly across cloud and on-premise environments using the latest advancements in hardware. In this role, youll lead efforts in distributed training, inference at large scale, resource optimization, and robust model lifecycle management using MLOps best practices. Your work will be critical to accelerating research, supporting production-grade AI infrastructure, and driving the development of our internal AI ecosystem.

Responsibilities
Architect and build scalable ML infrastructure for training and inference workloads across heterogeneous compute environments (on-premise and cloud).
Design and implement distributed systems to support model lifecycle management from data ingestion and preprocessing, to training orchestration and deployment.
Optimize performance and cost-efficiency of large-scale model training and serving pipelines using technologies like Ray, Kubernetes, Spark, and GPU schedulers.
Collaborate with AI researchers, data scientists, and product teams to understand their workflows and translate them into reusable platform services and APIs.
Drive adoption of best practices for CI/CD, observability, and reproducibility in ML systems.
Contribute to the long-term vision and technical roadmap of the ML platform, ensuring it evolves to meet the growing demands of AI across the company.

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 looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, you’ll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.
As a hands-on team lead, you’ll shape the technical roadmap for NLP and Speech at Riverside, identifying key opportunities to invest in foundational technologies and grow the team through strategic hiring and mentorship. You’ll work cross-functionally with product, engineering, and design partners to ensure that advanced research translates into robust, scalable features that define the future of AI-assisted content creation.

We are looking for an experienced AI/ML Engineer to join our Applications team within our platform engineering group. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and ML pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model deployment both in cloud environments and on-premises using GPUs and CUDA. Youll optimize and implement ML models, workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities
Design, implement, and deploy ML models, AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust ML pipelines and systems.
Deploy models on cloud and on-premises GPU servers.
Optimize system performance, including model inference, scalability, and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

We are looking for an experienced Software Engineer with GenAI/ML knowledge to join our AI/ML Applications team. In this role, you'll be responsible for designing, building, deploying, and maintaining production-grade AI systems and GenAI pipelines. You'll translate cutting-edge data science research into practical, scalable solutions, handling model/agent deployment both in cloud environments and on-premise. Youll optimize and implement workflows, and AI agents to ensure high performance and reliability in production environments.

Responsibilities
Design, implement, and deploy AI-driven applications, AI workflows, and LLM-based agents into production.
Build, manage, and maintain robust GenAI systems.
Optimize system performance, including robustness, scalability, communication protocols and resource utilization both on cloud and on-premises.
Develop and maintain services, APIs and integrate ML models into microservices-based applications.
Collaborate with cross-functional teams including data science, backend, DevOps, and platform teams.
Stay up to date with the latest developments in AI and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services.

Our team is looking for a Deep Learning Engineer.
Role and Responsibilities:
Develop Large Language Models as part of our applied research projects and in support of AI21 Platform, including designing, implementing and training massive-scale deep language models
Implement, optimize, scale and test new cutting edge ideas and architectures
Perform large-scale evaluations and comparisons of trained models across a range of benchmarks, as well as adding support for new benchmarks.

We are seeking a highly skilled and experienced Senior NLP Researcher to join our AI research team and drive the development of Dream's next-generation large language models (LLMs). The ideal candidate will have a strong background in NLP, deep learning, and applied research, with a passion for innovating and pushing the boundaries of generative AI technologies.

Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.