ML Platform Engineer at Teads Ltd

Netanya, Center District, Israel -

Full Time

Start Date

Immediate

Expiry Date

10 May, 26

Salary

0.0

Posted On

09 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Backend Engineering, ML Infrastructure, System Design, APIs, Distributed Systems, Performance Optimization, ML Frameworks, Python, Cloud Infrastructure, AWS, GCP, Data Processing, Monitoring, Performance Engineering, Production ML Pipelines

Industry

Advertising Services

Description

About Teads Teads is the omnichannel outcomes platform for the open internet, driving full-funnel results for marketers across premium media. With a focus on meaningful business outcomes for branding and performance objectives, the combined company ensures value is driven with every media dollar by leveraging predictive AI technology to connect quality media, beautiful brand creative, and context-driven addressability and measurement. One of the most scaled advertising platforms on the open internet, Teads is directly partnered with more than 10,000 publishers and 20,000 advertisers globally. The company is headquartered in New York, with a global team of nearly 1,800 people in 30+ countries. For more information, visit www.teads.com. Our main Engineering challenges at Teads Build efficient and easy-to-use web products used by thousands of users working for the world’s most premium publishers, advertisers, and agencies. Rich and diverse tech stack and system architecture to optimize for performance, scalability, resiliency, and cost efficiency. We use mostly Scala and TypeScript, among others. Working in a very high-traffic environment (2.2 billion users per month, 100 billion events per day) with low latency and high availability constraints (2 million requests per second, responses in less than 150 milliseconds). Management of large datasets with milliseconds order of magnitude access time, to compute in a near real-time complex auction resolution algorithm (18 million predictions per second). A fast-changing environment where we continuously collaborate with Product teams and constantly adapt our Cloud infrastructure for new features and Products. Bring a wide diversity of profiles to the same level of quality and knowledge Work in an international environment with offices located in Israel, Slovenia and France. Team Overview The ML Platform team builds the core infrastructure, services, and systems that enable machine learning at scale across the company. We own the full lifecycle of ML workloads — from research and experimentation to reliable, large-scale production deployment. The team focuses on: Building scalable backend and infrastructure solutions for end-to-end ML workflows Developing core ML platform components, including data processing, training, evaluation, and deployment Empowering data scientists and product teams with robust, observable, and high-performance ML infrastructure Solving complex challenges around scale, latency, throughput, reliability, and cost efficiency Continuously evolving the ML platform by adopting new technologies and improving system performance and stability What will you do? As a ML Platform Engineer, you will design and build core backend systems and ML infrastructure that power research, training, and online inference at scale. You will work at the intersection of backend engineering, data engineering, and machine learning, partnering closely with data scientists to transform research needs into production-grade platform capabilities with real business impact. Key Responsibilities Design, build, and own backend systems that support ML workflows, data processing, and core platform services Architect and optimize systems for performance, scalability, reliability, and cost efficiency in production ML environments Collaborate closely with data scientists to implement, iterate, and evolve ML platform capabilities Build and maintain large-scale data ingestion, processing, and training pipelines Ensure systems are production-ready through testing, observability, monitoring, and performance optimization Investigate and resolve infrastructure and performance issues affecting critical ML and business KPIs What will you bring to the team? 3+ years of experience in backend and/or ML infrastructure engineering Strong foundation in system design, APIs, distributed systems, and performance optimization Hands-on experience with ML frameworks such as TensorFlow or PyTorch Advanced backend development skills in Python Experience working with cloud infrastructure (AWS or GCP), including services such as AWS Batch, S3, and GPU-based workloads Strong communication skills and ability to collaborate across engineering, data science, and product teams Master’s degree in Computer Science, Engineering, or a related technical field is an advantage Bonus / Plus Points Backend experience in Java, Scala, Go, or Rust Experience with large-scale data systems and tools such as Spark, Airflow, or BigQuery Performance engineering expertise, including profiling, benchmarking, and tuning ML workloads Hands-on experience building or maintaining production ML pipelines and flows Please submit your CV in English. We care about you Hybrid working model (3 days per week in the office) Nearby parking available Expand your toolbox with our mentorship program and internal learning tools Pet friendly office Happy hours …and of course a fully stocked kitchen! #LI-Hybrid #LI-Hybrid Life at Teads At Teads, we don’t just offer new roles - we blend creativity, technology, and data to shape the future of media. You’ll work with smart humans, meaningful brands, and cool tools, all while helping redefine how advertising works in a world that demands more transparency, better insights, and smarter strategies. As a Teadster, you’ll play a critical role in shaping our future success in the region. Here’s why Teads stands out: We've merged two open internet category leaders—Outbrain and Teads—to create the ‘new’ Teads, a unified omnichannel platform that drives results from branding to performance across all screens, including CTV, mobile, and web. As part of our team, you’ll thrive in a collaborative and forward-thinking environment that fosters innovation, creative problem-solving, and continuous learning. Teads is committed to your success, offering the support, tools, and development opportunities you need to excel in your role. Our company culture is welcoming, dynamic, diverse, global, and built on top performance. Teads is an equal employment opportunity employer and committed to diversity and inclusion at all stages of recruitment and employment. Our team is made up of individuals who are approachable, resourceful, passionate, and proactive. We foster a sense of belonging through our Employee Resource Groups – employee-led groups in which we debate topics and drive change: environmental, women empowerment, charitable initiatives to diversity, equity, and inclusion, you’ll be able to share your passions with likeminded people.

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Responsibilities

As a ML Platform Engineer, you will design and build core backend systems and ML infrastructure that power research, training, and online inference at scale. You will collaborate closely with data scientists to implement and evolve ML platform capabilities.