דרושים » תוכנה » דרושים מנחי.ות פרויקט data Science לשכבת י"ב בתכנית מגשימים AI באזור מרכז

Required Senior Machine Learning Platform Engineer
What will you do?
As a Senior 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.

We are seeking a Data Product Manager to join Teads Data Department within the Data Product Team. In this role, you will be at the core of our mission to transform data into a strategic asset, ensuring that Teads business teams can make smarter, faster, and more impactful decisions.
As a Data Product Manager, you will be responsible for defining and delivering the vision, strategy, and roadmap of data products that serve internal stakeholders across Sales, Operations, Finance, and Marketing. You will focus on Looker as the central BI platform, ensuring reliable, scalable, and user-friendly data products that democratize insights and maximize business value.
This role requires a strong mix of product management expertise, BI platform experience (Looker is mandatory), and cross-functional collaboration skills. You will partner closely with data engineers, BI developers, and business teams to translate requirements into actionable data solutions, while upholding governance, quality, and scalability.
If you are passionate about creating data products that directly impact the efficiency and success of global teams in a fast-paced, data-driven environment, this opportunity is for you.
What will you do?
As a Data Product Manager, you will shape, deliver, and scale data-driven products that empower Teads business functions to operate more efficiently and make smarter decisions. You will partner with engineers, analysts, and stakeholders across departments to translate business needs into data products that drive measurable impact.
Your responsibilities will include:
Roadmap & Strategy
Define and prioritize the data product roadmap in alignment with Teads global objectives.
Identify key data opportunities, define success metrics, and ensure products are aligned with business impact.
Ensure data governance, quality, and scalability in all delivered solutions.
Product Design & Delivery
Translate business requirements into clear, actionable data product specifications.
Ensure stakeholders are kept informed on milestones, changes, and impacts.
Product Roll-out & Continuous Improvements
Contribute to a culture of data democratization, enabling teams to self-serve insights.
Oversee the roll-out of new Looker products, ensuring adoption and training across internal teams.
Monitor product usage and performance, gather feedback, and iterate to drive continuous improvement.

the industry leader in the web data domain, is looking for students for a part-time Deploy position!
The position is part-time, in shifts that include nights and weekends.
Responsibilities:
Monitor and support company servers in Linux
Release new features and updates on the server
QA (manual)

Required Machine Learning Platform Engineer
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.