דרושים » AI » MLOps Team Lead

Were seeking a visionary and technically hands-on AI Lead to join Alison.ai and take charge of driving innovation across our core AI systems. As the AI Lead, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform. You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.

This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.



Key Responsibilities

Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiativesidentify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.

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 seek an experienced technical leader to head our MLOps team.

In this role, you will lead a team of developers and build and maintain our machine learning infrastructure and deployment pipelines. This role combines technical expertise in machine learning operations with strong leadership abilities to guide our team of engineers in delivering scalable ML solutions.


A day in the life and how youll make an impact:
Build, recruit, and lead a team of MLOps engineers.
Architect and implement enterprise-scale MLOps infrastructure
Code ML Infrastructure & Framework for Agile ML Lifecycle, MLOps, and CI/CD.
Design and optimize model-serving architectures.
Ensure high availability and scalability of ML systems.
Collaborate with Algorithm Engineers to deliver innovative solutions.
Partner with product teams to align ML solutions with business objectives.
Communicate technical plans and progress to stakeholders.
Establish and enforce MLOps standards and best practices.

Required Big Data & GenAI Engineering Lead
As a Big Data & GenAI Engineering Lead within our 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 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 you will...
Design, lead, and evolve our 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.

Realize your potential by joining the leading performance-driven advertising company!
As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
About Algo platform:
The objective of the algo platform group is to own the existing algo platform (including health, stability, productivity and enablement), to facilitate and be involved in new platform experimentation within the algo craft and lead the platformization of the parts which should graduate into production scale. This includes support of ongoing ML projects while ensuring smooth operations and infrastructure reliability, owning a full set of capabilities, design and planning, implementation and production care.
The group has deep ties with both the algo craft as well as the infra group. The group reports to the infra department and has a dotted line reporting to the algo craft leadership.
The group serves as the professional authority when it comes to ML engineering and ML ops, serves as a focal point in a multidisciplinary team of algorithm researchers, product managers, and engineers and works with the most senior talent within the algo craft in order to achieve ML excellence.
How youll make an impact:
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Were hiring a Machine Learning Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across our companys B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do
Lead & Mentor: Manage, mentor, and grow a team of ML engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across our companys products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

We are looking for a passionate Computer Vision Software Team Leader who is excited to create, shape, and influence our products and company vision. As a Team Leader, youll deliver scalable, high-quality infrastructure that integrates AI models with complex application needs.
You will build fast, reliable, and efficient solutions on edge devices, as well as machine learning cloud-based systems and pipelines.
You will tackle technological challenges in performance and data scale, and uphold high standards for code quality and architecture.
Youll need both low-level and high-level expertise to address performance and AI challenges, while delivering robust features and infrastructure. You will continuously improve development processes, adopt new technologies, and help shape the future of retail through world-class AI solutions.
About The Role:
Lead the teams day-to-day activities, effectively managing priorities and navigating technical and organizational challenges.
Plan and coordinate work based on business goals estimate effort, set realistic timelines, and ensure timely delivery of high-quality results.
Design, develop, and deliver the next generation of features for our AI-driven solutions.
Conduct code and design reviews, evaluate implementations, and provide clear, constructive technical feedback.
Build and grow a high-performing team recruit, coach, mentor, and empower engineers to reach their full potential.
Collaborate cross-functionally with other teams to define and deliver features and initiatives that span across departments.
Foster a strong engineering culture by promoting best practices, high standards, and continuous improvement.

Were hiring a ML Engineer to accelerate AI-driven innovation across our companys B2B SaaS platform.
Youll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference.
What You Will Do
Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across our companys product and internal workflows.
Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring.
Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality.
Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services.
Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure.
Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders.

A global leader in hybrid cloud security. We bring a new approach that uses the attackers perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. The platform enables companies to rapidly prioritize and respond to cyber risks affecting their business-sensitive systems.
We are seeking a highly skilled and motivated backend Engineer with a Generative AI orientation to join our Infra team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities across our product line. This platform will handle cross-team concerns, such as prompt management, model access, data filtering, logging, and monitoring, centrally, so individual teams can focus on their own business-specific logic. As a backend Engineer with a Generative AI orientation, you will be instrumental in designing, developing, and implementing the core services of this foundational AI Platform. You will build components that enable our development teams to quickly innovate with AI while adhering to high standards for quality, cost-effectiveness, and compliance. Responsibilities:
* Develop and maintain a centralized microservice that handles all AI model interactions.
* Build shared services and libraries to maximize development speed and cost-efficiency for AI based features/systems across the company
* Setting the tone in the fields of automatic testing strategies and CI/CD for AI components, prompt management, and more.
* Define and enforce best practices for model governance, security, and compliance.