דרושים » תוכנה » Data Scientist

Requirements:
An analytical mind for problem solving, abstract thought, and offensive security tactics.
Strong interpersonal skills (written and oral communication) and the ability to work collaboratively in a team environment.
Bachelors degree in computer science/engineering or equivalent experience. Post graduate degree and/or related certifications in Machine Learning or Artificial Intelligence recommended.
8+ years in a role performing AI/ML Security reviews and/or assisting in security evaluations during model training
High level of language reading comprehension for Python code and experiencing performing source code reviews for security issues
Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch).
Strong understanding of Natural Language Processing (NLP) and related frameworks (e.g. nltk, spacy)
Experience training machine learning models including transformer based LLMs.
In-depth experience with exploiting OWASP LLM Top 10 application vulnerabilities, such as prompt injection and data poisoning
In-depth experience with exploiting OWASP Top 10 application vulnerabilities, such as deserialization and injection attacks.
Experience performing Threat Modeling, Penetration Testing and/or Red Team recommended.
Knowledge of regulatory and compliance standards related to AI and data security.
Ability to articulate complex issues to executives and customers.

Requirements:
- 4+ years of experience in data science/analytics
- Strong problem-solving skills with an emphasis on product development
- Advantage to those who have experience in stock/futures prediction
- Experience using statistical computer languages (Python) to manipulate data and draw insights from large data sets.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.)
- auto sklearn
- catboost
- arima
- lstm
- deep learning
- gan
- Coding knowledge and experience with
- javascript
- python
- experience with mongodb.

Requirements:
Essential:
Prior experience in designing, building, testing, and maintaining machine learning (ML) infrastructure to empower data scientists to rapidly iterate on model development
2+ years relevant experience in developing continuous integration, CI/CD deployment pipelines (e.g., Jenkins, GitHub Actions), and bringing ML models to CI/CD pipelines
Familiarity with data, feature and pipeline versioning of ML assets using tools such as CML-DVC or similar
Proficient knowledge of Git, Docker, Containers, and Kubernetes
Fluency in Infrastructure as Code tools (e.g., Terraform, Ansible, or Chef, etc.)
Fluency in common system maintenance and scripting languages, such as Python, Bash Shell, etc.
Good knowledge of Linux system administration
E2E production experience with Azure ML, Azure ML pipelines, AWS SageMaker, and GCP AI Platform
Familiarity with setting up hyperparameter tuning/optimization tools, and using them to manage versioning and experiments, model deployment and monitoring, such as Optuna, Kubeflow, AWS SageMaker, Hydrosphere, Seldon, or similar.