דרושים » מדעים מדוייקים » Senior Manager, data Science and Research בחברת הייטק

Data-driven insights. Help identify new products and opportunities for the company in diverse domains.
Develop Machine Learning models. Define requirements & combine data from a wide set of sources to develop ML/DL models that will automate and speed up our business processes.
End to end model management. Conduct in depth research, POC, write production-grade code and implement it (all the way to production) using our MLOps Infra to solve a diversity of business problems

We are looking for a Machine Learning Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.

As a Tech Lead on the ML team , you will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle managementthe foundation of our product.

Responsibilities:

Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as:
Feature Store centralizing feature engineering and serving across teams.
Vector Databases enabling large-scale embedding storage and retrieval for advanced ML applications.
GPU Cluster Scaling optimizing distributed training and inference infrastructure.
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.

We are looking for an experienced Data Science Manager to work on incredibly interesting projects as we take our personalization capabilities to the next level. You will focus on leading the team that are developing and advancing ML/AI across our platforms, researching and investigating new machine learning applications within the company, and improving pre-existing models.

Role & Core Responsibilities
Lead, mentor, motivate and inspire a small team of Machine Learning Engineers & Data Scientists.
Own the model development and release process across all products and internal platforms, including both OptiX and .
Manage the cloud-hosted modelling environment.
Operationalize models as APIs working in real-time and batch environments.
Monitor production models, ensuring data quality and model performance.
Develop predictive machine learning models for classification, ranking, and personalization purposes, utilizing multi-modal data including images and text.
Leverage LLMs and other cutting-edge technologies to enhance product capabilities.
Collaborate closely with product and development teams to define and prepare new ML applications.
Analyse performance and continuously improve scoring processes for hosted models.

Required Senior Algo Data Engineer
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Algo Data 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 Senior Algo Data 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
Our tech stack:
Java, Python, TensorFlow, Spark, Kafka, Cassandra, HDFS, vespa.ai, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes, Docker, git and Jenkins.

We seek a strong, motivated, and highly technical researcher who can be part of the Innovation & Research team.

With an R&D mindset, the research outcome will be integrated into products.

The position allows gaining extensive knowledge about security-related issues based on Machine Learning algorithms that would help to secure organizational networks, including IoT devices.

You will be able to directly impact protections against major vulnerabilities.

Key Responsibilities
Be part of the Innovation team that is responsible for Policy Insights and IoT security solutions.
Build ML/AI solutions together with a strong partnership with our engineering team.
Work with data throughout the entire pipeline from Data Engineering and Data Analytics to ML/AI models.
Collaborate with all the data & research-related groups within .
Developing and implementing protection mechanisms against diverse cyberattacks, while investigating IoT devices to analyze their network behaviours and integration within complex systems.
Productization & development of technologies from the POC stage into an enterprise-scale security solution.
Work closely with other development teams, QA, product management, and customers.

Architect and Evolve Data Infrastructure- Design and implement scalable data pipelines, Data Lakes, and Data Warehouses to support analytics, AI, and product intelligence.
Build and Deploy AI-Powered Systems- Operationalize AI/ML models- from prototyping to production-grade inference- ensuring performance, monitoring, and reliability.
Enable BI and Analytics- Collaborate with business and product teams to turn raw data into actionable insights, visualizations, and predictive metrics.
Ensure Data Quality and Governance- Establish standards for data collection, validation, lineage, and retention.
Leverage LLMs and AI APIs- Integrate modern large language models and external AI services for chatbots, insights generation, and automation use cases.
Collaborate Across Teams- Work closely with engineers, ML specialists, and product stakeholders to align data and AI architecture with business goals.

The ML Detection team is a new, cross-functional team at the core of our product strategy. Its mission is to own and advance the machine learning-based validations that form the foundation of our accessibility testing solutions. This includes everything from data collection and research to deploying, monitoring, and maintaining models in production. You will lead a multidisciplinary team of Data Scientists, ML/Data Engineers, and Algorithm Developers to build foundational models and standalone validations that extend the reach and precision of our products, giving Evinced a critical competitive edge.

Your Impact:

Lead, mentor, and grow a multidisciplinary team of Data Scientists, ML Engineers, and Algorithm Developers, fostering a culture of trust, collaboration, and professional growth.
Own the end-to-end delivery of ML-based detection capabilities, from initial research and data collection to model deployment, monitoring, and algorithmic post-processing.
Provide hands-on leadership, actively contributing to technical solutions, architecture, and design reviews for new algorithms and models.
Collaborate closely with Product, DevOps, and R&D teams to align on priorities, manage integrations, and ensure efficient, impactful development cycles.
Architect and oversee the development of the infrastructure required for the entire ML lifecycle, including data management, experimentation platforms, and model deployment/monitoring systems.
Define and refine team processes, tools, and methodologies to optimize performance, quality, and stability, ensuring data science tasks have clear definitions of done.
Drive the strategic vision for the evolution of our detection capabilities, including UI patterns, interactive elements and accessibility issues, to meet current and future needs.
Act as the primary problem solver and technical resource for the team, guiding them through complex research and engineering challenges.