Were looking for a Staff Data Scientist to join our dynamic and collaborative team in Tel Aviv.
In this role, you will shape strategic initiatives in the domain of AI and algorithm development, driving the creation of deep and innovative capabilities that push the boundaries of AI-driven solutions. By blending cutting-edge methods in Generative AI and Applied Machine Learning, youll play a pivotal part in defining our next generation of advanced, data-driven products and services.
Here are a few of the things you will do:
Collaborative Team Player: Foster an environment where colleagues can thrive. Seek opportunities to enhance team effectiveness, share expertise, and promote a culture of continuous learning.
Lead Applied Research & Development: Drive projects from focused, time-bound experimentation using scientific tools to delivering robust, production-ready solutions.
Strategic Impact: Partner with cross-functional stakeholders to identify, prioritize, and execute on high-impact AI and ML initiatives, ensuring alignment with business objectives.
Hands-On Innovation: Stay up-to-date with the latest technical and scientific advancements in AI, maintaining an experimental mindset to test, adopt, and refine emerging techniquesparticularly in Generative AI and LLMs.
Full Solution Ownership: Take accountability for project outcomesgathering requirements, developing data-driven solutions, and ensuring smooth deployment and operation through best-in-class MLOps practices.
In this role, you will shape strategic initiatives in the domain of AI and algorithm development, driving the creation of deep and innovative capabilities that push the boundaries of AI-driven solutions. By blending cutting-edge methods in Generative AI and Applied Machine Learning, youll play a pivotal part in defining our next generation of advanced, data-driven products and services.
Here are a few of the things you will do:
Collaborative Team Player: Foster an environment where colleagues can thrive. Seek opportunities to enhance team effectiveness, share expertise, and promote a culture of continuous learning.
Lead Applied Research & Development: Drive projects from focused, time-bound experimentation using scientific tools to delivering robust, production-ready solutions.
Strategic Impact: Partner with cross-functional stakeholders to identify, prioritize, and execute on high-impact AI and ML initiatives, ensuring alignment with business objectives.
Hands-On Innovation: Stay up-to-date with the latest technical and scientific advancements in AI, maintaining an experimental mindset to test, adopt, and refine emerging techniquesparticularly in Generative AI and LLMs.
Full Solution Ownership: Take accountability for project outcomesgathering requirements, developing data-driven solutions, and ensuring smooth deployment and operation through best-in-class MLOps practices.
Requirements:
Strong problem-solving mindset, with a passion for continuous innovation.
8+ years of professional experience in Data Science/ML Engineering roles, including at least one role with a tenure of two years or more in the same organization.
A Masters or Ph.D. degree in Computer Science, Engineering, or a related field.
Demonstrated accountability and stakeholder management: Capable of gathering requirements and translating them into actionable, data-driven solutions, while taking full ownership of the outcomes.
Proven track record of deploying ML solutions to production, adhering to proper MLOps practices throughout the model lifecycle.
Experience in fine-tuning LLMs, adapting them to domain-specific problems.
Strong problem-solving mindset, with a passion for continuous innovation.
8+ years of professional experience in Data Science/ML Engineering roles, including at least one role with a tenure of two years or more in the same organization.
A Masters or Ph.D. degree in Computer Science, Engineering, or a related field.
Demonstrated accountability and stakeholder management: Capable of gathering requirements and translating them into actionable, data-driven solutions, while taking full ownership of the outcomes.
Proven track record of deploying ML solutions to production, adhering to proper MLOps practices throughout the model lifecycle.
Experience in fine-tuning LLMs, adapting them to domain-specific problems.
This position is open to all candidates.
