חיפוש עבודה

Summa cum laude BSc. in Mathematics, Physics, Computer Science or Electrical Engineering from a well-known academic institute
Advanced degree (MSc./PhD.) in a relevant field is a plus
Programming experience (C++ - advantage)
Experience in statistical analysis of large data sets - significant advantage
Deep learning experience - advantage
Experience in quantitative finance - advantage
A deep sense of intellectual curiosity and excellence
Independent, thorough, motivated, and innovative

M.Sc. or PhD. in Computer Science, Mathematics, Engineering or a related field
Strong knowledge in Python
Good knowledge in Java, Scala or C++
Familiarity with statistical modeling techniques
5+ years of hands on experience with coding machine learning/statistical modeling based solutions
Experience in data analysis and visualization and strong knowledge in SQL

Possess strong problem solving and critical thinking skills

5 years of experience in development (At least 2 years experience in developing big systems with Python) - Must
Asynchronous programming and experience in developing performance-critical applications
Working with AWS, Docker, and microservices – Advantages
Experience with Machine Learning – Advantages
Algorithms development (collaborative filtering, similarity, data normalization, clustering) -
Advantages
Excellent analytical and time management skills
Teamwork skills with a problem-solving attitude

5 years of experience in development (At least 2 years experience in developing big systems with Python) - Must
Asynchronous programming and experience in developing performance-critical applications
Working with AWS, Docker, and microservices – Advantages
Experience with Machine Learning – Advantages
Algorithms development (collaborative filtering, similarity, data normalization, clustering) -
Advantages
Excellent analytical and time management skills
Teamwork skills with a problem-solving attitude

" 5+ years of experience in DevOps roles
" Strong experience with AWS serverless technologies (Lambda, Step Functions)
" Expertise in Kubernetes administration and deployment strategies
" Experience with data warehouse technologies (Redshift, Athena, PostgreSQL, S3)
" Proficiency with Infrastructure as Code using Terraform
" Strong scripting abilities in Bash and Linux system administration
" Experience implementing and maintaining CI/CD pipelines (Jenkins, ArgoCD)
" Demonstrated experience with monitoring solutions (Prometheus, Grafana)
" Knowledge of cloud security best practices and compliance requirements

Ideal Candidates Will Also Have
" Experience with AWS CDK or CloudFormation
" Familiarity with Python or other programming languages
" Experience with event-driven architectures
" Exposure to machine learning infrastructure
" Experience with blue/green deployment strategies
" Contributions to open-source projects

PhD in Computer Science or a related field with focus on computer vision and deep learning
Completion of post-doctoral fellowship - advantage
" Publications in top-tier computer vision and /or machine learning conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML
Knowledge and expertise with deep learning applications for vision?
4+ years hands-on experience in computer vision and deep learning
Experience with Python and machine learning frameworks such as PyTorch and Tensorflow
Highly innovative and independent with strong teamwork skills
Proven track record of achieving significant results and innovation as demonstrated by first-authored publications

4+ years of backend experience in a data engineering/development role
Strong knowledge of Python
Proven experience working with SQL and NoSQL databases, data warehouses, and data lakes
Experience in architecting and implementing data pipelines
Experience with spark
Practical experience in MLOps - big advantage
BSc/BA in computer science or engineering
Fast learner, independent, and able to multitask on several projects
Ability to identify and improve inefficient processes

Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field.
3+ years of experience in AI/ML development, with a focus on telecom applications or related industries.
Proven experience in leading AI/ML projects, ideally in a chip or semiconductor company.
Strong knowledge of AI/ML frameworks (e.g., TensorFlow, PyTorch) and machine learning algorithms.
Hands-on experience in model development, training, and deployment in real-time systems.
Proficiency in programming languages such as Python, C, or C++
Ability to work in a fast-paced, collaborative environment and manage multiple projects simultaneously.

" A data-oriented mindset
" 7+ years of development experience, using a general purpose programming language (Python, Java, Scala, Kotlin, Go, etc)
" 5+ years of experience in data engineering - designing & building data pipelines, analytical tools, and data lakes
" 3+ years in a leadership role
" Great interpersonal skills - a team player who is communicative and empathetic
" Vast experience with Python - Big Advantage
" deep experience in SQL/NoSQL databases and data lakes
" Vast experience with the data engineering tech stack: ETL & Orchestration tools (e.g. Airflow, Argo, Prefect) and data processing tools (e.g Spark, Kafka, Presto, Iceberg, dbt)
" Experience working in a containerized environment (e.g. k8s ) - advantage
" Experience building and maintaining ML infrastructure - big advantage

Ph.D./M.Sc. in Computer Science, Electrical Engineering or a related field

Track record of publishing papers in high quality conferences such as NeurIPS and ICML

5+ years of work experience with primary emphasis on AI research

Proficiency in Python and ML packages

" 6+ years of relevant industry experience in data science or machine learning
" Education: MSc in Math / EE / CS / Statistics OR BSc in one of the disciplines above and 10+ years of substantial, hands-on experience in data science or a closely related domain - demonstrating expertise equivalent to that typically acquired through formal advanced education
" Demonstrated research expertise in the tech industry or published academic papers
" Profound understanding and hands-on expertise in mathematics, statistics, machine/deep learning, and data mining
" Expertise in data science pipelines is essential, including data cleansing, feature engineering, and model tuning
" Strong coding and software engineering experience focusing on advanced proficiency in Python, especially in data science libraries such as Pandas, Polars, NumPy, SciPy, Scikit-learn, and others
" End-to-end experience in leading the development of AI/DS/ML products or features, including managing their deployment in production environments, whether through direct integration or by using existing APIs
" Demonstrated experience in working streaming data (including sequential/time series) and implementing corresponding algorithms/models in a production environment, whether in batch processing or real-time scenarios
" Solid experience in deep learning, utilizing platforms such as TensorFlow, Keras, PyTorch, etc.
" Proficiency in SQL
" Strong communication skills, with the ability to convey ideas and share knowledge effectively
" Independent and quick learner, capable of developing independently
" A valuable team player who cooperates well
" Experience thriving in a dynamic work environment

" Academic degree with a major in communication, signal processing, electronics or systems, advanced degree is advantage.
" At least 3 years of work experience in the fields of communication, semiconductors, radars, robotics, IoT ,5G or similar, preferably in startup environment.
" Good understanding of DSP algorithms, such as time/frequency synchronization, AGC, RF channel estimation, equalization, decoding, etc.
" Previous experience in both algorithm research, development and implementation (from research and POC to official product release) is highly preferred.
" Ability to extensive debug of HW and SW systems, rigorous analysis of experimental data, identification, and analysis of problems
" Knowledge in statistical signal processing, estimation theory, statistics is big advantages.
" Background and understanding of classical machine learning and statistical data analysis methods is advantage.
" Experience with Python scientific stack, Jupyter notebook and Git. Additional experience with C/C++ in RT and embedded environment is advantage.
" Highly motivated and "technologically passionate", hard worker and quick learner, adept of hands-on approach
" Good interpersonal skills, team player with good ability to work independently and take responsibility, good references - must.

3 years of experience in managing development teams
Extensive experience in the design and development of web applications
At least a year of experience in client-side development
At least 3 years of experience in server-side development with Java
Experience with Linux environment and containers (Docker)
Experience with Agile development, effort estimations, and timelines management
Experience with cyber security products development
Experience with Spring boot
Experience with SQL databases
Experience with NodeJS
Experience with Micro frontends architecture
Experience with big data technologies
Familiarity with network protocols and log formats (Syslog, NetFlow, etc.)
Experience with of data monitoring and visualization tools (Prometheus/Grafana)
Knowledge of machine learning libraries and their application in security analytics

5+ years of experience in Machine Learning
2+ years of experience leading a team of ML researchers
Strong technical skills in ML, including deep learning (bonus: recommendation systems)
Excellent communication and interpersonal skills
Ability to work independently and as part of a team
Masters degree in Computer Science, Mathematics, Physics, Engineering, Statistics, or a related field

Requirements:
At least 3 years of proven experience in data science or machine learning, with a proven track record of delivering production-grade ML solutions.
Proficiency in Python and commonly used libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
Strong knowledge of SQL and experience with querying large datasets.
Familiarity with data pipelines, ETL processes, and data QA.
Strong analytical skills with the ability to translate complex data challenges into actionable solutions.
Deep understanding of ML algorithms and techniques.
Experience in feature engineering, model evaluation, and hyperparameter tuning.
Team player, problem-solver, responsible, delivery-oriented.
Bachelors degree in Computer Science, Statistics, Applied Mathematics, or a related field.

*At least 5 years of experience as a Data Scientist, with a proven track record of delivering machine learning algorithms to production.
*Hands on experience with recommendation system development
*Extensive knowledge of ML disciplines and algorithms - able to manage research in a large scale
*Excellent programming skills in Python, SQL
*Proficient in PyTorch, GPU computing, Scikit-learn, or other ML frameworks
*Familiar with cloud services such as Amazon SageMaker and Vertex AI pipelines, as well as architecting solutions
*Experience in developing recommender systems, search algorithms - a plus
*Experience with multimodal models - a plus
*Creativity and a passion for music and art - a plus
*Excellent teamwork skills, with experience working closely with product managers and other stakeholders to deliver user-centric solutions.
*A team player who is also self-sufficient, able to work independently as well as part of a diverse team.

BSc. in Computer Science, Engineering or a related discipline

Minimum of 4 years of industry experience

Proficiency in Python, including Panda & Numpy libraries, strong background in C++

Experience working in Linux environment

Experience working with SQL DB & building distributed or data intensive systems is a big plus

Familiarity with Machine Learning is a plus

Familiarity with Google Cloud is a plus

Experience with user interface development is a plus

Demonstrated problem solving abilities, insight, and judgment as well as a strong attention to detail

Strong communication skills; ability to express complex concepts in simple terms

M.Sc or Ph.D. in computer science, electrical engineering, physics, mathematics or equal

Passionate about innovation and keeping in tune with up to date trends

Work within a team and mentor others while being able to Independently lead a task\algorithm project, including multi-disciplinary interaction

Vision\data ( at least 3 years of experience):

Theoretical and practical knowledge of machine learning, deep learning and statistical analysis and modeling

Proficiency with a deep learning framework such as TensorFlow\Keras\PyTorch

Familiarity with and understanding of the classic image processing and computer vision field

Proficiency with Python and Matlab, including machine learning, machine vision and image processing libraries\extensions

Coding ( at least 3 years of experience):

C\C++

Matlab \ Pytho

M.Sc or Ph.D. in computer science, electrical engineering, physics, mathematics or equal

Passionate about innovation and keeping in tune with up to date trends

Work within a team and mentor others while being able to Independently lead a task\algorithm project, including multi-disciplinary interaction

Vision\data ( at least 3 years of experience):

Theoretical and practical knowledge of machine learning, deep learning and statistical analysis and modeling

Proficiency with a deep learning framework such as TensorFlow\Keras\PyTorch

Familiarity with and understanding of the classic image processing and computer vision field

Proficiency with Python and Matlab, including machine learning, machine vision and image processing libraries\extensions

Coding ( at least 3 years of experience):

C\C++

Matlab \ Pytho

Experience: 5+ years of hands-on experience in cloud infrastructure, DevOps and platform engineering in production environments.
Cloud Platforms and IaC: Expertise in managing cloud infrastructure on at least one of the major providers: AWS, GCP, Azure. Proficient in Infrastructure as Code tools such as Terraform, CloudFormation, or Pulumi.
Containerization & Orchestration: Solid experience with Docker and Kubernetes.
Monitoring & Logging: Hands-on experience with monitoring tools (Prometheus, Grafana) and logging systems (ELK, Splunk, or equivalent).
Software Engineering: Proficient Software engineering, architecture, as well as scripting languages such as Python, Bash, or Go. Full control of version control systems such as Git.
DevOps Tools: Strong experience with CI/CD pipelines and automation using Jenkins, CircleCI, GitHub Actions, GitLab CI, or similar.
Networking: Strong understanding of cloud networking, VPNs, VPCs, DNS, and firewalls.
Security Best Practices: Experience implementing cloud security best practices, including IAM, encryption, and key management.
Startup Experience: Previous experience in a fast-paced startup environment, where adaptability and hands-on execution are key.
Team Player: Strong communication skills and ability to work cross-functionally with different teams.