לוח משרות דרושים הייטק AI

Requirements:
Hands-on experience with GenAI models, especially LLMs.
Deep understanding of AI models and how to adapt them to various needs.
Experience in evaluating, testing, and implementing AI-based solutions.
Familiarity with open-source tools and how to adapt them to an air-gapped environment.
Job location- Central Israel
Scope of hours: Approximately 100 hours.

Requirements:
Essential:
Bachelors degree or higher academic background in AI/ML, DSP, Computer Science, or Engineering
3+ years experience in ML/AI development, or related experience
Solid expertise in use of ML tools such as Caffe, pyTorch, TensorFlow, scikit-learn, NLTK, etc.
Strong knowledge of low-level programming languages (e.g., C/C++, C#, or Objective-C)
Solid understanding of data structures, data modeling, and software architecture
Deep knowledge of mathematics, probability, statistics, and algorithms
Agility to quickly build prototypes around new ideas
Propose creative approaches to solve complex problems
Experience with agile methodologies
Excellent communication skills
Team player.

Requirements:
Electrical Engineering B.Sc., Computer Engineering or other relevant engineering department graduate with high scores, or equivalent experience.
5+ years in design verification, with strong SV/UVM proficiency (Less experienced engineers with high university grades or vast knowledge in RTL design will also be considered)
Self-motivated, ability to work, lead and drive tasks to completion.
Great interpersonal skills.
Understanding of digital ASIC design flows and SoC development methodologies. experience with SoC/full-chip verification, simulation/debug tools, and Unix/Linux environments, scripting languages (Python, etc.) and version control.
Advantages
Knowledge in Low Power technics and UPF standard.
Knowledge with Mix signals SoCs.
Knowledge with SW/HW Co-development

Requirements:
Proven experience deploying generative AI solutions to production at scale.
Extensive hands-on expertise in frameworks including:
RAG Pipelines: Chunking (token, semantic, markdown-aware), embedding models (OpenAI, Cohere, HuggingFace), vector DBs (Pinecone, Weaviate, FAISS), retrieval evaluation (Precision@k, RAGAS), hybrid search.
LLM orchestration: LangChain, LlamaIndex, Semantic Kernel, Haystack, tool/function calling, memory management.
Evaluation & monitoring: Prompt versioning, grounding evaluation, LLM-as-judge, LangSmith, TruLens, failure analysis (hallucination, context overflow, function calls), real-time observability.
Resilience: Prompt injection prevention, output validation (JSON schema, type checking), fallback logic.
Deployment: Caching strategies, multi-model routing, cost-performance optimization.
Strong software engineering skills: Python, FastAPI, Docker, Kubernetes.
Proven ability to manage real-time IoT or streaming data integration.
Excellent communication skills with technical and non-technical teams.
Comfort in fast-paced, agile environments.
Advantages
Background in IoT or ambient sensing.
Familiarity with advanced orchestration frameworks or autonomous agent systems (AutoGPT, CrewAI, LangGraph).
Prior experience building AI SDKs/developer platforms.
Background in NLP, multimodal AI, or knowledge graphs.
Good understanding (not necessarily expert-level) of data science concepts.

Requirements:
Requirements: - Bachelor’s degree in Computer Science, Software Engineering, Mathematics, Physics, or a related field - At least 3 years of hands-on experience in algorithm development using C++ - Must - Proficiency in SQL- Must - In-depth knowledge of algorithms, physics, and mathematics - Must - Strong analytical, and problem-solving skills - Familiarity with radar systems - Advantage - Experience as a Tech Lead - Advantage

Requirements:
B.Sc. in Computer Science, Electrical Engineering, or Mathematics
Experience in GenAI tools such as LLM Orchestrations and integration packages, Agents, RAG systems
5+ years expertise with modern backend programming languages such as Python/Java/Scala/Kotlin/Go
Experience writing code in Agile, CI/CD-based production environments
Experience working with Big data technologies such as Kafka/Spark/OpenSearch, Parquet/Avro/Delta Lake/Iceberg
Strong communication and collaboration skills
Data-engineering, architecture, data-science roles or security domain knowledge are an advantage

Requirements:
5+ years of Red-Team and Vulnerability Research experience
Extensive Cloud and AppSec experience
Intimate knowledge of GenAI and LLM internals
Bonus: Proven track record of published research

Requirements:
At least 10 years of experience in a data engineering role, including 2+ years as a data & AI architect with ownership over company-wide architecture decisions.
Proven experience designing and implementing large-scale, Big Data infrastructure from scratch in a cloud-native environment (GCP preferred).
Excellent proficiency in data modeling, including conceptual, logical, and physical modeling for both analytical and real-time use cases.
Strong hands-on experience with:
Data lake and/or warehouse technologies, with Apache Iceberg experience required (e.g., Iceberg, Delta Lake, BigQuery, ClickHouse)
ETL/ELT frameworks and orchestrators (e.g., Airflow, dbt, Dagster)
Real-time streaming technologies (e.g., Kafka, Pub/Sub)
Data observability and quality monitoring solutions
Excellent proficiency in SQL, and in either Python or JavaScript.
Experience designing efficient data extraction and ingestion processes from multiple sources and handling large-scale, high-volume datasets.
Demonstrated ability to build and maintain infrastructure optimized for performance, uptime, and cost, with awareness of AI/ML infrastructure requirements.
Experience working with ML pipelines and AI-enabled data workflows, including support for Generative AI initiatives (e.g., content generation, vector search, model training pipelines) or strong motivation to learn and lead in this space.
Excellent communication skills in English, with the ability to clearly document and explain architectural decisions to technical and non-technical audiences.
Fast learner with strong multitasking abilities; capable of managing several cross-functional initiatives simultaneously.
Willingness to work on-site in Ashkelon once a week.
Advantage:
Experience leading POCs and tool selection processes.
Familiarity with Databricks, LLM pipelines, or vector databases is a strong plus.

Requirements:
Minimum Qualifications
PhD degree in Computer Science, Computer Engineering, Computer Graphics, Applied Sciences, Mathematics, Physics, or related field.
Experience in Python and PyTorch.
Track record of publishing papers in high-quality journals and conferences such as CVPR, ECCV/ICCV, SIGGRAPH, NIPS.
1+ years of work experience in a university or industry, in a role with primary emphasis on AI research
Preferred Qualifications
Experience with generative AI / neural rendering models.
Experience with affective computing and behaviour understanding.
Experiences in the creation and processing of large audio-visual datasets.
Experiences in solving complex problems and comparing alternative solutions, trade-offs, and different perspectives to determine a path forward.

Requirements:
MSc in Computer Science, Engineering, or a related field with a focus on AI, ML, or DS.
5+ years of experience in DS roles, with a strong emphasis on building and deploying machine learning models in production environments.
Expertise in Python and SQL.
Experience with machine learning frameworks such as TensorFlow or PyTorch.
Familiarity with cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
Proven experience in developing, fine-tuning, and deploying ML models, particularly in NLP.
Ability to translate complex business problems into data-driven solutions.
Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Preferred Qualifications:
Background in academic or industrial research in AI.
Familiarity with the e-commerce domain and related data challenges.
Previous experience leading projects in a DS capacity.

Requirements:
Minimum Qualifications
Currently has or is in the process of obtaining a PhD degree in the field of Computer Science, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining us.
Research background in machine learning, artificial intelligence, computational statistics, applied mathematics, or related areas.
Research publications reflecting experience in theoretical or empirical research.
Experience in developing and debugging in Python or similar programming languages.
Experience in analyzing and collecting data from various sources.
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred Qualifications
Research and engineering experience demonstrated via grants, fellowships, patents, internships, work experience, and/or coding competitions.
First-authored publications at peer-reviewed conferences, such as ICML, NeuRIPS, ACL, EMNLP, ICLR, FacCT, CCS, IEEE S&P, and other similar venues
Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
Experience collaborating in a team environment on research projects
Experience communicating research for public audiences of peers.