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Requirements:
Ph.D. or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Strong background in machine learning, deep learning, and statistical modeling.
Proven experience in conducting research and publishing papers in reputable conferences and journals.
Proficiency in programming languages such as Python, R, and experience with ML frameworks like TensorFlow, PyTorch, or similar.
Experience with data preprocessing, feature engineering, and model evaluation.
Strong problem-solving skills and the ability to work independently and as part of a team.
Excellent communication skills, both written and verbal.
Familiarity with video technology and applications is a plus.

These would also be nice:
Experience with natural language processing (NLP) and computer vision.
Knowledge of big data technologies like Hadoop and Spark.
Experience working in an Agile development environment.
Prior experience in a similar role within the technology or media industry.

Requirements:
5+ years of experience in data science, with experience in managing full-cycle projects from initial concept to production deployment.
PhD in Computer Science, Data Science, Statistics, Mathematics or a related field .
Comprehensive understanding of machine learning and deep learning principles and techniques, including hands-on experience.
Specialized expertise in NLP (Transformers, LLMs) and computer vision (multimodality is an advantage).
Ability to write production-ready code.
Publications and talks at leading conferences - an advantage.

Requirements:
M.Sc degree from a prominent academic institute in a relevant field (e.g., Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or equivalent).
Proven industry or research experience with Large Language Models (LLMs), Vision-Language Models (VLMs), and Retrieval Augmented Generation (RAG) systems.
Strong theoretical and practical understanding of deep learning, particularly for computer vision tasks.
Excellent programming skills, with strong proficiency in Python.
Hands-on experience with deep learning frameworks such as PyTorch.
Familiarity with the HuggingFace Transformers library and ecosystem.
Demonstrated ability for independent research, problem-solving, and self-learning.
Bonus points if you have:
Experience with deployment of AI models to production environments.
Familiarity with other deep learning platforms (e.g., Pytorch, Keras).

Requirements:
2+ years of experience in applied AI, ML research, or systems involving language models.
Solid experience as a software engineer, with preference for full-stack development background to ensure strong domain understanding.
Proven experience in data science and algorithmic development.
Deep understanding of transformer-based LLMs, vector retrieval, and prompt engineering.
Familiarity with building agents is a plus, but not requiredwe will support your training in this emerging space.
Experience with Python and working with LLM APIs or fine-tuning pipelines.
Familiarity with tools like Docker, cloud environments (AWS/GCP), and scalable infrastructure.
Advantage: Experience in developer tooling, compilers, or software engineering workflows.
Advantage: Research or publications in AI planning, LLM agents, or program synthesis.

Requirements:
M.Sc. in Computer Science or related field.
Minimum 3 years of hands-on security R&D AI, application or network or cloud.
Strong Python programming skills with a focus on production-level code.
Proven ability to work both independently and collaboratively in a team environment.
Self-starter DNA you should be able to thrive on autonomy, move fast, and communicate well with stakeholders at every level.

Requirements:
2 + years as a leader of engineering or data science teams, with a track record of shipping data-intensive tools or services to production.
6 + years hands‑on building data-driven solutions with Python and SQL.
Experience deploying services using cloud-based infrastructure and data tools such as PostgreSQL, Databricks, and Spark.
Strong understanding of the key concepts and usage of modern AI tools such as LLMs, RAG systems, and AI agents.
Solid software engineering fundamentals (including design patterns, data structures, and version control) and familiarity with Agile practices.
Proven ability to manage project scope, timelines, and cross‑team dependencies.
Comfort implementing rapid, iterative development processes while also prioritizing quality, reliability, and maintainability.
Excellent command of English, both verbal and written, and comfortable presenting technical topics to non‑technical stakeholders.
Its even better if you have:
Proficiency with CI/CD tools and practices, containers, serverless architectures, and automated testing and monitoring.
Experience deploying models to production using leading machine learning frameworks such as TensorFlow or PyTorch.
Experience with Agile development processes and project management in JIRA.
Expertise in machine learning metrics and monitoring.
Experience with geospatial analysis, government data, survey research, or civic tech applications.
Demonstrated success hiring and developing technical talent.
Contributions to open‑source projects or an advanced degree in a relevant field.

Requirements:
- Bachelors degree in data Science, Computer Science, Computer Engineering, or related field. - 2+ years of experience in data Science roles. - Proven experience managing AI/ML project lifecycles from conception to deployment. - Deep understanding of classic ML, deep learning, and LLMs. - Strong proficiency in Python and experience with frameworks such as PyTorch, Scikit-Learn, and TensorFlow. - Hands-on experience with low-level programming in C / C ++. - Team player with strong collaboration and communication skills. - Quick learner with ability to adapt to new tools, methods, and frameworks. Preferred Qualifications: - Background in mobile app research or development ( Android / IOSgreenTxtBg!). - Image processing experience. - Reverse engineering experience with tools like IDA, gdb, and lldb. - Knowledge of OS internals. - Cybersecurity background with understanding of threat landscapes and attack vectors. About the Company:our company's mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With our company, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines. Leading financial, healthcare, m-commerce, consumer, and B2B brands use our company to upgrade mobile DevSecOps and protect Android & IOS apps, mobile customers, and businesses globally. Today, our company's customers use our platform to secure over 50,000+ mobile apps, with protection for over 1 billion mobile end users projected.
we are an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.

Requirements:
2-4 years experience in a customer-facing analytically oriented role (e.g., SaaS Customer Success, Management Consulting, etc.)
Experience managing large strategic accounts
B.A./B.S. Degree in an analytical/ economics/ business management discipline
Strong project management or organizational skills and an ability to multitask without difficulty
Flexibility, including the ability to adapt quickly to changing priorities; capable of operating in an ambiguous environment
Native-level English- MUST

Requirements:
610 years in Data Science, Machine Learning, or AI Research.
Expert in Python ecosystem (PyTorch, TensorFlow/Keras, Hugging Face, Pandas, NumPy, Scikit-learn).
Expertise in ML/DL modelling
Strong analytical skills for structured & unstructured data and the ability to translate academic research into real‑world applications.
Excellent communication & collaboration skills.
Background in product-driven environments with rapid prototyping and iterative development.
Nice to have
Generative AI Proficiency (e.g. LLMs, RAG, etc.).
Experience with cloud platforms (AWS, Azure, GCP).
Experience with multimodal AI solutions (text, image, audio).
Background in FinTech, Banking.
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Requirements:
MSc or PhD in a computational or statistical field (Computer Science, Statistics, Applied Math, Econometrics, Operations Research), or equivalent experience
3+ years Data Science experience.
Experience working on one of the cloud platforms: AWS, GCP, Azure
Well versed in Data Science languages, tools and frameworks, including data processing platforms and distributed computing systems (for example Python, R, SQL, SKLearn, NumPy, Pandas, TensorFlow, Keras)
Familiarity with LLM based applications an advantage
Familiarity with LLM security and safety aspects - an advantage
Resourceful, motivated, and organized.