Director of Algorithm at 4M Analytics Ltd

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

07 Mar, 26

Salary

0.0

Posted On

07 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Artificial Intelligence, Data Science, Team Leadership, Algorithm Development, Technical Excellence, Cross-Functional Collaboration, Innovation, Production Systems, Data Pipelines, Model Architectures, Communication Skills, Mentoring, Research, Intellectual Property, Problem Solving

Industry

Software Development

Description

Who We Are: The 4M story is likely one you haven’t heard before: We are on a mission to unlock access to the world below us, to do for the world below ground what Google Maps did for the world above. By leveraging cutting-edge technology, we are mapping the subsurface infrastructure to make reliable, real-time utility data accessible to the construction industry - completely transforming a traditional industry. We’re a growing startup with 100 employees currently based in Tel Aviv, Israel, and Austin, Texas. Role Overview We are seeking a visionary Director of Algorithm to join our leadership team and report to the VP of R&D. This is a high-impact strategic role for a leader who combines deep expertise in machine learning and advanced AI with a proven track record of turning innovation into measurable business results. As Director of AI, you will lead and expand a group of algorithm engineers embedded in Product pods, play a pivotal role in roadmap planning, and balance cutting-edge research with practical productization. You will drive cross-organizational initiatives that elevate our products and operations, defend our competitive moat, and unlock new opportunities for growth and innovation. Key Responsibilities Team & Talent Leadership Manage, mentor, and inspire a team of algorithm engineers, fostering technical excellence and career growth. Scale the AI team through hiring, skill development, and cultivating a strong data science culture. Promote cross-functional collaboration, execution, knowledge sharing, and experimentation. Attract senior AI talent to build strong teams. AI Roadmap & Innovation Execute the AI roadmap, aligned with the company strategy and product vision. Introduce state-of-the-art techniques to solve complex challenges. Drive initiatives that push the boundaries of what’s possible, turning AI into a measurable business differentiator. Technical Leadership Personally led the resolution of the most complex AI/ML challenges. Architect and guide the implementation of production-ready ML systems, ensuring robustness, accuracy, and low latency. Maintain a strong applied research perspective while delivering practical, business-impacting solutions. Defending & Expanding Our Moat Keep us ahead of industry shifts by monitoring emerging technologies and evaluating competitive threats. Build defensible AI assets - unique data pipelines, proprietary models, domain-specific enhancements - that are hard to replicate. Shape intellectual property (publications, patents, methodologies) that strengthens our positioning. Requirements 10+ years of professional experience in AI/ML and data science with at least 5 years in leadership roles. Advanced degree (MSc/PhD) in Computer Science, Mathematics, or related field. Proven success leading data science / AI teams in production environments. Strong grounding in ML/DL, model architectures, and data pipelines. Track record of translating research into scalable production systems with measurable business impact. Practical trade-off mindset - build vs. buy, open-source vs. proprietary, etc. Excellent communication skills - capable of influencing executives, mentoring engineers, and educating non-technical stakeholders. Passion for continuous learning, innovation, and knowledge sharing.

Responsibilities

The Director of Algorithm will lead a team of algorithm engineers, manage the AI roadmap, and drive initiatives to enhance products and operations. This role involves balancing cutting-edge research with practical productization and ensuring the implementation of robust ML systems.