לוח משרות דרושים NLP/Machine Learning בחיפה וסביבתה

Requirements:
10 or more years of experience in AI, machine learning, signal processing, or related computational fields, with a proven track record of designing and operating production-grade intelligence systems.
Commercial experience designing, building, or leading agentic AI systems, including LLM-based reasoning, orchestration, tool use, and autonomous or semi-autonomous decision workflows in production environments.
Strong ability to combine classical ML, time-series modeling, and signal processing with LLMs and agentic flows to deliver reliable, explainable, and actionable outcomes.
Experience delivering AI-powered products end-to-end, from research and experimentation through deployment, monitoring, and continuous improvement in SaaS, edge, or hybrid environments.
Solid understanding of AI system concerns such as model governance, evaluation, safety, observability, and lifecycle management, particularly in customer-facing or mission-critical contexts.
Leadership and Scale
4 or more years of experience leading high-impact ML, AI, or engineering teams across both research and product execution and experience as manager of managers.
Demonstrated ability to scale multidisciplinary teams while maintaining delivery focus, technical rigor, and clear ownership.
Proven track record of building cultures of technical excellence, accountability, experimentation, and continuous learning.
Experience leading teams through architectural change or AI paradigm shifts, including the adoption of LLMs and agentic systems.
Domain and Strategic Vision
Ability to set and communicate long-term AI direction while balancing near-term delivery, technical risk, and business impact.
Hands-on experience with agentic systems, autonomous decision workflows, or LLM-driven systems applied to real-world operational problems.
Sound judgment in choosing when to apply classical ML, deep learning, LLM-based techniques, or agentic approaches based on problem context and constraints.
Strong plus: background in time-series analytics, real-time inference systems, sensor data fusion, or closely related domains.
Communicator and Influencer
Exceptional communicator with the ability to align technical and non-technical stakeholders around complex AI decisions and tradeoffs.
Strong aptitude for translating AI innovation into measurable business value, particularly in reliability, efficiency, and operational optimization domains.
Comfortable representing AI strategy and technical direction in executive discussions, customer engagements, and cross-functional forums.
Education
Ph.D. or Masters degree in Computer Science, Electrical Engineering, Physics, AI or ML, Applied Mathematics, or a related field.

Requirements:
Technical Depth: Masters or PhD in Computer Vision, ML, or a related field, with strong software engineering skills and comfort in complex ML training environments.
The "Metric" Mindset: Deep expertise in evaluation methodology and statistical rigor. You know why standard metrics often fail and how to build better ones.
Perceptual Intuition: A sharp "eye and ear" for quality. You can articulate subtle nuances in motion or sound that automated systems might miss and use that intuition to improve our reward models.
Data-Driven Detective: You love diving into datasets to find the "why" behind the numbers, taking pride in curating and specializing data for specific evaluation tasks.
Product-Minded Scientist: You can think like an end-user. You care that our models don't just "beat the benchmark" but actually work reliably in professional pipelines.
Statistical Rigor: You understand experimental design, significance testing, and the nuances of perceptual quality assessment.