דרושים » AI » AI (Vision) Researcher

Requirements:
WHAT YOU WILL BRING
5+ years of professional experience as a research scientist, applied scientist, or algorithms/ML engineer.
Ph.D. or Masters degree in computer science, machine learning, data science, statistics, or a related field.
Expert-level proficiency in PyTorch and deep learning training and inference optimization.
Hands-on experience training, fine-tuning, evaluating, or optimizing large-scale LLMs in research or production environments.
Strong Python programming skills and experience writing production-grade ML code.
Experience working with large-scale data and ML infrastructure.


NICE TO HAVE
Experience applying AI/ML to cybersecurity, including threat detection, incident response, log analysis, or related problems.
Experience with reinforcement learning or preference optimization for LLMs.
A track record of research publications, open-source contributions, or other technical work demonstrating research depth.

Requirements:
Required Qualifications
Minimum of 5 years of experience in Applied AI research, Data Science, or Machine Learning engineering.
Deep, hands-on experience over the past 12+ months developing leading-edge agentic coding practices.
Proficiency in Python and/or Typescript, with deep familiarity in Agentic AI orchestration libraries like LangChain, LlamaIndex, or LangGraph.
Experience with automated statistical evaluation to track model drift, latency, costs, and hallucination rates.
Hands-on experience developing advanced RAG pipelines, GraphRAG frameworks, and interacting with Graph Databases or vector indices.
Practical experience with autonomous agent protocols, multi-agent communication layers, or Model Context Protocol (MCP).
Preferred Qualifications
Understanding of secure data pipelines, including Role-Based Access Control (RBAC) and prompt injection mitigation.
Hands-on production experience utilizing Google Cloud Platform (GCP) services and infrastructure.
Strong knowledge of data privacy and security considerations specific to AI and ML systems.
Post-graduate work or equivalent advanced degree in Artificial Intelligence, Data Science, or a related field.

Requirements:
M.Sc., Ph.D., or equivalent industry experience.
Strong foundation in mathematics.
Expertise in image processing and computer vision.
A strong research track record in generative modeling, computer vision, or a related field.
Strong programming and software design skills.
Hands-on experience training video diffusion models.
Deep understanding of modern generative-model architectures and training methods.

Requirements:
5+ years of experience as an applied researcher with proven production-level impact.
Masters degree in Computer Science, Mathematics, Statistics, or Engineering (PhD is a plus, but not required).
Experience in applied research, including work with Transformers, open-source LLMs, or other advanced deep learning architectures.
Strong programming skills in Python, with hands-on experience in modern ML frameworks and tooling.
Excellent problem-solving skills and a strong experimental mindset.
Strong communication skills and the ability to collaborate effectively across teams.
High curiosity and a passion for learning new technologies, methods, and domains.

Requirements:
Deep, hands-on application security experience at an engineering level: someone who sits with dev teams, understands development processes from the inside, and reviews code and architectures as a peer (Must)
At least 1 year of dedicated, immersive work in AI security: research, experimentation, or offensive engagements targeting AI/ML systems (Must)
Offensive security capabilities with a focus on AI-specific attack vectors (Must)
Strong understanding of AI/ML technologies, including LLMs, agentic systems, and common AI application architectures
Development skills: comfortable reading and writing code, building tools, and understanding codebases
Excellent communication skills and comfort working directly with enterprise customers
Fluent English
Nice to have:
Published research or public talks on AI security topics
Experience with traditional penetration testing or red teaming
Background in building or deploying AI/ML systems from the development side.

Requirements:
Master's degree in Electrical Engineering, Computer Science, Physics, or a related field

3+ years of experience in designing and implementing AI/ML algorithms, with a strong focus on signal processing

Proven experience working across the full ML lifecycle - from data acquisition and model training to production implementation and ongoing product iteration.

Moves fast, with strong engineering instincts, able to choose the right level of complexity to drive real-world impact

A get things done attitude with a strong sense of ownership

A team player with excellent communication and collaboration skills; able to convey complex ideas clearly to technical and non-technical partners

Exceptional analytical and problem-solving skills

A fast learner, willing to try things out of your comfort zone

Experience in speech, audio, or music-related domains - Advantage

Requirements:
Requirements:
Deep learning expertise with a track record of non‑trivial research (industry or academia) in LLMs or other domains (e.g., CV, speech). We care that youve changed models or methods in meaningful ways (architecture/training/eval), not just used them.
Strong experimental design and scientific writing; comfort pre‑registering hypotheses, testing causal claims, proposing novel directions in a fast-changing field.
PhD or equivalent research experience in the industry (5+ years in a leading research team). Publication record or a portfolio of high‑impact open artifacts will make you stand out from the crowd.
Familiarity with AI frameworks (e.g., HuggingFace Transformers, LangChain, scikit-learn, PyTorch); Experience with a production grade codebase with several contributors is a bonus.
Experience in data analysis: visualization, exploration, cleanup.
Knowledge in GenAI tools such as LLM Orchestrations and integration packages, Agents, RAG systems - a bonus.

Requirements:
Academic background: B.Sc. in an engineering or quantitative scientific field, with coursework or focus in data science, machine learning, or information systems (or equivalent experience).
Experience: 5+ years of hands-on experience in applied AI research, data engineering, data science, or applied ML - ideally with security-related domains.
Strong Python & Data Pipelines: Proven ability to build robust pipelines that handle large-scale, real-world data.
LLM Systems in Production: Experience building and shipping real product features powered by LLMs, taking solutions from prototype to production, owning reliability through evaluation and monitoring.
Cyber Security Domain Knowledge: Familiarity with core security concepts, including asset inventory and context, vulnerability management and risk prioritization, exposure/attack-surface analysis, network and traffic analysis, and practical remediation workflows in collaboration with security teams.
Experiments & Workflow Design: Experience designing and running experiments and building reproducible end-to-end data workflows to validate new product features and iterate based on measurable results.
Problem Solving Skills: Strong analytical and critical-thinking skills, with the ability to break down ambiguous problems, apply sound algorithmic reasoning, and develop creative, pragmatic solutions.
Startup Mindset: High ownership, strong collaboration, and the ability to execute quickly and effectively in a fast-paced, evolving environment.
Advantage
Experience working with security datasets and real-world enterprise environments.
Experience building structured extraction and normalization systems using LLMs.
Strong product intuition: ability to turn AI capabilities into features users trust and rely on.
Experience designing AI monitoring systems (quality drift, and evaluation pipelines).

Requirements:
Required Qualifications:
Minimum of 5 years of experience in Applied AI research, Data Science, or Machine Learning engineering.
Deep, hands-on experience over the past 12+ months developing leading-edge agentic coding practices.
Proficiency in Python and/or Typescript, with deep familiarity in Agentic AI orchestration libraries like LangChain, LlamaIndex, or LangGraph.
Experience with automated statistical evaluation to track model drift, latency, costs, and hallucination rates.
Hands-on experience developing advanced RAG pipelines, GraphRAG frameworks, and interacting with Graph Databases or vector indices.
Practical experience with autonomous agent protocols, multi-agent communication layers, or Model Context Protocol (MCP).
Preferred Qualifications:
Understanding of secure data pipelines, including Role-Based Access Control (RBAC) and prompt injection mitigation.
Hands-on production experience utilizing Google Cloud Platform (GCP) services and infrastructure.
Strong knowledge of data privacy and security considerations specific to AI and ML systems.
Post-graduate work or equivalent advanced degree in Artificial Intelligence, Data Science, or a related field.

Requirements:
Masters/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field.
3+ years of applied AI/ML experience with a focus on Generative AI, LLMs, and deep learning.
Depth in agentic system design, retrieval-augmented generation, context and tool engineering, and rigorous evaluation.
Familiarity with AI frameworks (e.g., HuggingFace Transformers, LangChain, scikit-learn, PyTorch)
Familiarity with embedding models and vector databases
Exceptional problem-solving, creative thinking, and analytical skills.
Experience with voice AI technologies, speech recognition, or text-to-speech systems - strong advantage.