דרושים » AI » AI Analyst

Requirements:
Must have:
Background in AI Safety and/or Responsible AI and/or AI Ethics.
Familiarity with recent Generative AI models and agents is essential, though direct technical experience is not a prerequisite.
Command of English at a near-native level.
Attention to detail, organizational capabilities, and the capacity to juggle numerous tasks concurrently.

Additional Wants:
Experience with various model types (Text-to-Text, Text-to-Image) is desirable.
Prior experience with OSINT (Open Source Intelligence) will be considered an asset.
A self-starter attitude, with the energy to excel in a fast-moving and variable environment.

Requirements:
What youll need:
Strong Algo Foundation: 3+ years of practical experience in research and development of Deep Learning algorithms.
Domain Expertise: Deep knowledge in at least one of the following fields: NLP, Computer Vision, or Speech/Audio Processing.
Engineering Excellence: Strong proficiency in Python and DL frameworks (PyTorch/TensorFlow) with a track record of delivering code to production (not just Jupyter notebooks).
Modern AI Stack: Experience or strong familiarity with Transformers, Foundation Models (GPT, Llama, CLIP, Whisper, etc.), and Prompt Engineering techniques.
The Athlete Mindset: You are a fast learner who is not afraid to jump from a Text problem to a Vision problem.
Preferred Qualifications:
M.Sc or PHD in Computer Science, Electrical Engineering, or related fields.
Experience building Multimodal systems (e.g., VQA, Video Understanding, Audio-Visual fusion).
Experience with deployment, optimization, and serving of Large Language Models.

Requirements:
Required qualifications:
BSc, MSc, or PhD in Computer Science, Software Engineering, or a related field
Strong software engineering skills with experience designing maintainable, modular systems
Hands-on experience working with ML models and evaluation pipelines
Proficiency in Python and modern ML ecosystems
Ability to read, modify, and debug deep learning models
Experience with benchmarks, metrics, or evaluation frameworks - preferred
Familiarity with foundation models or multimodal learning - preferred
Comfort navigating complex datasets and doing targeted exploratory analysis
Experience in biomedical or other data-intensive domains - a plus
Desired personal traits:
You want to make an impact on humankind
You prioritize We over I
You enjoy getting things done and striving for excellence
You collaborate effectively with people of diverse backgrounds and cultures
You have a growth mindset
You are candid, authentic, and transparent.

Requirements:
Strong background in applied AI, machine learning, or AI systems.
MSc or PhD in Computer Science, Machine Learning, AI, or a related field, or equivalent practical experience.
Hands-on experience with LLMs, AI agents, or complex AI systems.
Experience designing evaluation and benchmarking methodologies for AI systems.
Experience working with structured and semi-structured data systems.
Proficiency in Python and modern AI frameworks.
Ability to work independently on ambiguous, real-world problems.
Preferred
Familiarity with knowledge graphs, graph databases, or graph-based reasoning.
Experience applying AI in security or adversarial environments.
Experience evaluating system-level behavior of AI systems in production.
Publications, open-source contributions, or prior research in AI systems, agents, or data reasoning systems.

Requirements:
Mandatory:
Minimum 1 year experience in establishing and management of intelligence infrastructure
Operational online security orientation: Demonstrate awareness of security risks in diverse operational environments and understand appropriate mitigation measures
Experience in operational processes and / or investigations within the different realms of the cyber sphere (mobile environments and web)
OSINT and online research experience
Proven ability to identify trends and methodologies that support the different infrastructure environments creation and management
A proactive and independent learner of new practice areas and technological tools
Strong written and verbal communication skills
Fluent English
Nice to have:
Additional languages
Curiosity and out of the box thinking
Ability to work under pressure.

Requirements:
8+ years of experience building and operating large-scale data and AI systems, with 5+ years in architecture or platform leadership roles driving technical direction across multiple teams.
Demonstrated experience defining and executing architectural vision in complex, multi-team environments, including setting standards, leading design reviews, and influencing long-term roadmaps.
Deep expertise in cloud-native distributed systems (GCP, AWS, or Azure), including Kubernetes-based infrastructure (e.g., GKE), scalable storage and compute, reliability, and security at scale.
Strong command of modern data architectures (data lake, lakehouse, warehouse) and large-scale analytics platforms (e.g., BigQuery, Databricks), including data lifecycle, metadata, and governance strategy.
Proven experience designing internal data and ML platforms that enable reproducible experimentation, self-serve workflows, and efficient research-to-production transitions.
Experience architecting end-to-end ML lifecycle systems, including training infrastructure, experiment tracking, versioning, CI/CD for ML, deployment patterns (batch/online), and monitoring across MLOps platforms (e.g., ClearML, RunAI, or equivalents).
Strong understanding of security, privacy, and compliance requirements in regulated environments, including fine-grained access control, auditing, and data protection best practices.
Desired personal traits:
You want to make an impact on humankind
You prioritize We over I
You enjoy getting things done and striving for excellence
You collaborate effectively with people of diverse backgrounds and cultures
You have a growth mindset
You are candid, authentic, and transparent.

Requirements:
6+ years of experience in software development, with a strong focus on Backend.
Minimum 1 year of experience in a leadership or team management role, preferably in a global setup.
Deep expertise in Cybersecurity is a must; you understand the offensive and defensive landscape.
Hands-on mastery of Node.js and experience building complex, distributed systems.
Strategic thinker capable of establishing a new domain from the ground up while balancing hands-on work with leadership.
Strong communication skills in English to effectively lead a global team and interface with stakeholders.

Requirements:
7+ years of experience in software engineering, with 3+ years in a managerial role
Proven managerial experience in developing, incubating, and releasing a product from the ground up
Proven experience in leading and growing engineering teams in dynamic environments
Strong technical background with the ability to dive deep and make high-level architectural decisions
Excellent collaboration and communication skills
Comfortable working in a fast-paced, hybrid startup environment
A proactive, hands-on leader who thrives on impact and accountability
Passion for building scalable, secure, and high-performing products

Requirements:
Strong can-do / builder mindset with real startup DNA (bias toward shipping, not over-process)
Experience leading engineers as a Tech Lead / Engineering Manager / senior technical leader
Deep understanding of production systems and scale
Strong intuition for performance, cost, and reliability tradeoffs
Hands-on backend experience with large-scale systems
Experience with databases such as: Postgres, ClickHouse / Snowflake (or similar OLAP systems), Elasticsearch / OpenSearch
Experience designing distributed systems: Event-driven architectures, Pub/Sub, Queues, Caching layers (Redis or similar)
Practical experience with AI systems: OpenAI / LLM APIs, Embeddings, Semantic search, RAG pipelines
Nice-to-have:
Experience with code indexing or static code analysis
Background in observability platforms
Research-oriented mindset with fast experimentation skills
Experience building knowledge systems or AI agent platforms