דרושים » הנדסה » AI/ML Team Lead

As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
Responsibilities:
Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects.
Design and conduct research and experimentation to improve algorithm performance and accuracy.
Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team.
Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives.
Provide strategic direction and technical mentoring to elevate the capabilities of the AI team.

We are seeking an experienced Algorithm and Signal Processing Engineer We are seeking a data Scientist and LLM Engineer with a strong background in Python and hands-on experience in developing and implementing advanced ML and NLP solutions.
* The ideal candidate will bring in-depth technical skills and industry experience to design, develop, and optimize AI/ML models, particularly Large Language Models (LLMs), to address complex challenges in our target sectors ementation in simulation environments.
* Support software, hardware, and firmware teams in implementing algorithms on Embedded systems.
Responsibilities
* Design, develop, and deploy cutting-edge causal inference and AI models to solve complex problems in user behavior, root cause analysis, gaming and mobile applications domains.
* Develop Python -based solutions for data processing, model training, and deployment in production environments.
* Collaborate with cross-functional teams to integrate AI/ML solutions into enterprise-grade applications.
* Conduct research on the latest advancements in AI, ML, and LLMs to maintain competitive edge.
* Optimize and fine-tune LLMs for performance, scalability, and cost efficiency.
* Analyze and process large datasets to extract actionable insights that drive business value.
* Develop and maintain robust, scalable, and efficient codebases and documentation.

We are seeking an experienced Senior Architect to lead the design and delivery of scalable, high-performance, and robust systems that drive the next generation of AI/GenAI lifecycle solutions. This individual will play a key role in shaping the architecture of our core platform and its components, ensuring alignment with business goals and technical excellence.

The ideal candidate will have a proven track record in large-scale systems design, the ability to lead complex technical projects, and a strong understanding of AI/ML, cloud environments, and modern software development practices. While this is primarily an individual contributor role, experience managing or mentoring teams is highly valued.

Responsibilities:

Lead architectural design and decision-making for large-scale, high-performance, and fault-tolerant systems.
Collaborate with cross-functional teams (Product, Engineering, Operations) to ensure architectural alignment with company objectives.
Provide technical leadership and mentorship to engineering teams, fostering best practices in system design, coding standards, and scalability.
Evaluate and recommend new technologies and tools to enhance system performance and developer productivity.
Develop detailed system specifications, including API designs, data flow diagrams, and integration strategies.
Drive the end-to-end success of complex technical projects, from concept to deployment.
Advocate for architectural consistency and efficiency across multiple teams and repositories.

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 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.

We are seeking a AI Lead to drive the development and deployment of intelligent applications powered by ambient IoT platform. This role will be at the forefront of building AI-native interfaces that connect the physical and digital worlds redefining how users interact with real-time data, business operations, and physical assets.

This is a flexible leadership position: Ideal for someone who can build and lead a team, or an exceptional technical expert capable of executing as a high-impact individual contributor. The role reports to the Director of Strategy and will be central to shaping AI roadmap across internal tools, customer-facing solutions, and SDKs for external developers.

Responsibilities
AI Product Execution: Lead the development of GenAI-driven products, such as intelligent agents, copilots, and self-serve interfaces for real-world sensing and IoT data.

Architecture & Engineering: Design scalable, secure, and maintainable architectures for deploying LLM-powered services in production.

AI/ML Ops & Infrastructure: Own the full lifecycle of AI solutions prompt engineering, model evaluation, vector search, function calling, monitoring, retraining.

Team Leadership (optional): Mentor and grow a team of AI engineers and applied researchers, or collaborate across squads as a senior IC.

Cross-functional Collaboration: Work with data scientists, software engineers, product managers and business stakeholders to embed generative AI into the core of data product strategy.

Customer Use Cases: Translate ambient IoT data into actionable AI experiences supporting applications in logistics, sustainability, inventory management, and supply chain visibility.

Developer Platforms: Help build the SDKs and APIs that let customers and partners create their own AI-powered workflows using technology.

Experimentation & Research: Stay at the frontier of GenAI advancements (LLMs, RAG, agents, vision-language models) and apply them to real-world constraints and data environments.

We are looking for a AI Architect GenAI Group.
The individual in this role will drive the architectural vision for advancing the next-generation solutions of our Multimodality GenAI infrastructure. Additionally, he will provide technical guidance to various teams on design decisions, address key AI development challenges within the group, and serve as the tech lead for the GenAI team.
Reporting to the Group Manager, this role is part of the groups leadership committee, shaping the AI and engineering vision and setting strategic goals.
What youll do:
Lead the architecture design and implementation of our Large Sports Model
Guide and Mentor engineers from our GenAI Teams
Implement significant components of the architecture hands-on independently
Lead the integration of new components into our system
AI/ML Integration: Work with data scientists and engineers to integrate machine learning models into software systems.
Cross-functional Collaboration: Work with stakeholders, including product managers, data scientists, and engineers, to align technical strategy with business objectives.
Scalability & Performance: Ensure system designs can handle large-scale data processing and high availability.
Participate in the technical evaluation of other companies for potential partnerships

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.

We are seeking a highly skilled and experienced Machine Learning (ML) Application Engineer Team Lead to spearhead the development of reference applications in computer vision and large language models (LLMs). This role involves designing and implementing robust ML pipelines utilized by both our customers and internal teams to evaluate and benchmark our hardware/platform. The ideal candidate will lead a team of four engineers, each focusing on individual applications, ensuring synchronization and cohesive progress across projects.

Key Responsibilities:
Team Leadership: Manage and mentor a team of four ML engineers, fostering a collaborative environment that encourages innovation and professional growth.
Application Development: Oversee the design and development of reference applications in computer vision and LLMs, ensuring they meet industry standards and client requirements.
Pipeline Engineering: Develop and optimize ML pipelines for vision and LLM applications, facilitating seamless integration and deployment for customers and internal assessments.
Performance Evaluation: Lead efforts to benchmark our hardware/platform's performance against competitors, providing insights and recommendations for continuous improvement.
Cross-Project Coordination: Ensure alignment and effective communication among team members, synchronizing efforts across various application projects.
Stakeholder Collaboration: Work closely with product managers, hardware engineers, and other stakeholders to align application development with business objectives and technological advancements.

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic AI team. The ideal candidate will have a strong background in machine learning, data engineering, and software engineering, and will be responsible for leading the design, development, and deployment of cutting-edge machine learning pipelines and systems.
What you'll be doing
System Design and Architecture: Develop and maintain robust, scalable, and efficient ML pipelines including data collection, preprocess, and analyze large datasets to facilitate model training, evaluation and monitoring.
Research and Innovation: Stay current with the latest advancements in machine learning and AI, and apply innovative techniques to improve model performance and application.
Mentorship and Leadership: Provide technical guidance and mentorship to junior engineers and data scientists, and lead project teams to successful completion.
Cross-Functional Collaboration: Work closely with data scientists, software engineers, architects and product managers to integrate machine learning solutions into production systems.