לוח משרות דרושים הייטק

Requirements:
BSc in CS/EE/Math/Physics from a well-known university
At least 3-4 years of hands-on machine learning experience
Education in machine learning at the level of advanced academic courses
Practical experience with deep learning
Self-reliant, proactive, with strong motivation and an inquisitive mind
Advantage:

MSc in machine learning or related area
Experience with deep learning on time series data (Transformers / recurrent models)
Experience with training neural networks in cloud environments (GCP/AWS) and distributed systems
Experience/education in signal processing and/or control theory
Proven research background
Experience in leading projects and mentoring

Requirements:
At least 5+ years as a DevOps Engineer
Experience developing and maintaining microservice-based SaaS systems
Experience managing CI/CD tools: Jenkins or GitLab CI or ArgoCD
Experience with container orchestration, Kubernetes, docker swarm
Experience with AWS and/or Google Cloud

Requirements:
MSc in machine learning or related area
Education in machine learning at the level of advanced academic courses
At least 5 years of hands-on machine learning experience
Practical experience with deep learning
Self-reliant, proactive, with strong motivation and an inquisitive mind
Advantage:

Experience with deep learning on time series data (Transformers / recurrent models)
Experience with training neural networks in cloud environments (GCP/AWS) and distributed systems
Experience/education in signal processing/ control theory/ reinforcement learning
Academic research experience
Experience in leading projects and mentoring

Requirements:
4th-year Mechanical Engineering student A must.
Availability for 3 working days a week A must.
Availability for full-time work during up coming semester break - A must.
Previous exposure to the medical device industry an advantage.
Familiarity with SolidWorks, and ERP Systems.
Detail-oriented, organized, and a fast learner.

Requirements:
What It Takes:
3-5 years of experience in marketing, partnerships, influencer marketing, or social media management - Must.
Experience with design and content platforms such as Figma, Riverside.fm - Must.
Engineered viral loops that 10 followers and drive sign-ups, not vanity views - Must.
Launched creator-led challenges, UGC blitzes, and co-branded drops that flood feeds with share-worthy content - Must.
Data-first operator who tracks CAC per creator, kills under-performers fast, and reinvests in winners.
Demonstrated experience growing brand presence and engagement on social platforms.
Experience managing co-branded campaigns or partner/influencer programs with measurable results.
Experience from a fast-growing SaaS, eCommerce, or fintech environment - Strong Advantage.
Strong communication and project management skills, comfortable juggling multiple stakeholders and deadlines.
Analytical mindset with a bias toward data-driven decision making.
Experience managing budgets and tracking performance ROI across campaigns.
Big Bonus: Familiarity with the Shopify ecosystem or direct-to-consumer (DTC) landscape.

Requirements:
MSc (or higher) in Statistics, Machine Learning, Applied Mathematics, or a related quantitative field.
4+ years of experience as a data scientist, with significant focus on insurance pricing or underwriting analytics.
Strong domain expertise in insurance pricing workflows, including rate plan development, evaluation, and optimization.
High proficiency in statistics, machine learning algorithms, data manipulation and analysis.
Extensive experience in research-oriented roles, analyzing business problems from a data science perspective, conducting literature research, and implementing and testing solutions.
Expertise in supervised and unsupervised machine learning models (e.g., GLM, GAM, XGBoost, Deep Learning).
A proactive approach to staying updated with the latest developments in AI and incorporating them to enhance existing products.
A product-driven mindset with a knack for transforming research outcomes into impactful products.
Excellent communication skills, with the ability to articulate experiment goals and methodologies clearly and communicate insights effectively to the team.

Requirements:
Advanced degree (MSc required; Ph.D. strongly preferred) in Statistics, Machine Learning, or a closely related field, with at least 7 years of experience working in data science roles.
High proficiency in statistics, machine learning algorithms, data manipulation and analysis.
Extensive experience in research-oriented roles, analyzing business problems from a data science perspective, conducting literature research, and implementing and testing solutions
Expertise in supervised and unsupervised machine learning models (e.g., GLM, GAM, XGBoost, Deep Learning).
A proactive approach to staying updated with the latest developments in AI and incorporating them to enhance existing products.
A product-driven mindset with a knack for transforming research outcomes into impactful products.
Experience managing stakeholders and prioritizing across multiple business and technical needs.
Excellent communication skills, with the ability to articulate experiment goals and methodologies clearly and communicate insights effectively to the team.

Requirements:
Cybersecurity professional with a minimum of 5 years experience as on-prem/cloud security researcher
Knowledge and experience researching IaaS platforms like AWS, Azure or GCP (advantage)
Experience with identifying and analyzing trends or patterns related to security incidents and abnormal behaviors
In-depth understanding of an organizations security, risks, and potential attack vectors in all the organizations perimeters
Understanding security issues, attack vectors, and related security trends
Strong knowledge of SQL language
2 years of Hands-on experience in programming and scripting (C++/Python)
Passion for conducting Value-to-customers-driven research
Must possess strong verbal & written communication skills in English
Problem-solving skills in an effective and creative way while maintaining a prominent level of flexibility
Experience with data analysis of large data sets.

Requirements:
4+ years of experience in SQL, data analysis and visualization
4+ years of strong scripting experience
Experience with monitoring tools such as DataDog, New Relic, Grafana, Prometheus
Understanding of statistical data
Self-learning and infinite curiosity
Strong troubleshooting and problem-solving skills
Experience with AZURE or other cloud solutions - an advantage
Kusto Query language an Advantage
Experience working with Analytics tools
Excellent teamwork skills and the ability to work autonomously
Statistical analysis experience (e.g. Python)
Experience with Artificial Intelligence - an advantage.

Requirements:
Advanced degree (MSc required; Ph.D. strongly preferred) in Statistics, Machine Learning, or a closely related field, with at least 7 years of experience working in data science roles.
High proficiency in statistics, machine learning algorithms, data manipulation and analysis.
Extensive experience in research-oriented roles, analyzing business problems from a data science perspective, conducting literature research, and implementing and testing solutions.
Expertise in supervised and unsupervised machine learning models (e.g., GLM, GAM, XGBoost, Deep Learning).
A proactive approach to staying updated with the latest developments in AI and incorporating them to enhance existing products.
A product-driven mindset with a knack for transforming research outcomes into impactful products.
Excellent communication skills, with the ability to articulate experiment goals and methodologies clearly and communicate insights effectively to the team.

Requirements:
7+ years of engineering experience, with 3+ years in an early-stage startup environment.
3+ years of experience leading and managing engineering teams.
BSc in Computer Science or a related field.
Strong background in software architecture and system design for scalable, cloud-based applications.
Proficiency in Python (or similar OO programming languages).
Expertise in databases (SQL, NoSQL, Big Data).
Experience with cloud platforms (AWS preferred) and DevOps best practices.
Excellent communication skills, with the ability to work in global, cross-functional teams.
A proactive mindset, with a drive to push for innovative solutions.

Requirements:
3+ years of experience working in DFIR/Research roles.
High-level of proficiency in coding, particularly in Python (PySpark).
Demonstrate knowledge of Windows and Linux forensic techniques, tools, and concepts.
Strong knowledge of network architecture fundamentals (Proxies, NAT, firewalls, IDPS, DMZ, etc.) as well as common network protocols and applications (TCP/UDP, DNS, HTTP/S, etc.)
Strong technical foundation of standard Information Technology concepts and services, including active directory environment.
Experience working with multiple enterprise security solutions (e.g., SIEMs, Firewalls, IDPS, AV/EDRs, IAM, DLP, etc.)
Proven success contributing to a team-oriented environment.
Strong critical thinking, deductive reasoning, problem-solving, and prioritization skills.

Requirements:
3+ years of work experience as a DevOps Engineer and at least 2 years of experience in a SaaS company
Significant coding experience in Python, PowerShell, Go, Bash or equivalent.
3+ years of experience on at least one major cloud platform: Azure, AWS (Azure is an advantage).
3+ years of Windows or Linux hands-on experience (configure, troubleshooting, and deployment).
Experience with IaaC\CM tools such as Terraform, Packer, and Ansible.
Experience with CI\CD platforms such as Jenkins, Github actions, Azure DevOps, and CircleCI. (Azure DevOps is an advantage)
Excellent problem-solving ability with solid communication and collaboration skills
A good understanding of IT infrastructure-related components, technologies, and protocols, such as Active Directory, DNS, TCPIP, Load balancing, PKI, Firewalls, and routing.
Good English communication skills (A global team where all full team discussions are held in English)
Ability to manage multiple projects of varying scopes concurrently, excellent communication skills, and ability to work as part of a team.
Advantages
Experience with various Azure services, such as: Service Fabric cluster, AKS, Virtual machine scale set, Storage account, Azure AD, Event Hubs, App Service, Azure SQL and SQL Managed instance, Log Analytics and Kusto query language, Azure Function, Azure Batch and more.
Experience with analytics, monitoring, dashboarding and incident management systems, such as Grafana, Azure Monitor, PagerDuty, OpsGenie, DataDog, New Relic.
C#\.Net programming experience.
Bachelors degree in a technical discipline, Information Systems Technology or Computer Science.