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Requirements:
Deep DevSecOps Expertise: 5+ years of experience in a senior DevSecOps or Application/Product Security role, with a strong, working knowledge of DevSecOps principles and the modern application threat landscape (e.g., OWASP Top 10).
DevSecOps Focus: Proven ability to shift left security by embedding automated security controls (SAST, DAST, SCA, IAST) into CI/CD pipelines.
Open Source Security & Supply Chain Mastery: Deep, hands-on experience managing and hardening open-source software dependencies.
Key Focus: Expertise in utilizing Software Composition Analysis (SCA) tools (e.g., Dependency-Check, Snyk, Black Duck) to maintain an accurate Software Bill of Materials (SBOM) for all products.
Vulnerability & Risk Management Pro: Proven ability to establish and own a continuous CVE tracking and remediation process.
Key Focus: Expertise in risk-rating vulnerabilities based on exploitability and business impact, and driving engineering teams to remediate security risks efficiently using automation and clear Service Level Objectives (SLOs).
Audit & Compliance Automation: Proven, hands-on experience managing security audits and certification programs (e.g., SOC 2, ISO 27001) by leveraging security as code principles and automating evidence collection to demonstrate compliance across the pipeline.
Leadership & Influence: Strong leadership skills with the ability to build consensus and partner with R&D, Platform Engineering, and IT teams to embed security practices without being a bottleneck.

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills - in Java & Python
Experience with TensorFlow - a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
6+ years of experience in hands-on technical roles such as Software Development, QA, Solution Engineering, etc. - Must
Technical hands-on experience in a Web environment - understanding of the ecosystem and ability to debug effectively - Must
Experience in the mobile ecosystem (Android and iOS) - Strong advantage
Bachelors degree in a technical field such as Computer Science, Engineering, or equivalent practical experience
Capability to read and understand code - In a level that allows collaboration with developers and leadership of technical products
Familiarity with at least one of the following programming languages (or a similar one): Java, JavaScript, Python.
Experience with SQL and large-scale data sets, with the ability to analyze and draw conclusions
Experience collaborating with cross functional teams - From Business to R&D
Experience in creating technical documentation and managing knowledge bases
Advanced proficiency in written and spoken English. Exceptional communication and presentation skills
Strong interpersonal skills, ability to influence others, and work effectively in a cross-functional team
Highly experienced and passionate about problem solving and troubleshooting
An independent, self-starter, with a can-do approach
AI knowledge / AI project skills - a big advantage.

Requirements:
3+ years in engineering management, leading backend or platform teams building large scale distributed systems.
Deep understanding of backend architecture, AI/ML systems integration, and scalable infrastructure; able to guide technical design and trade-offs.
Demonstrated ability to define technical roadmaps, prioritize effectively, and deliver complex projects in collaboration with cross functional partners.
Experience in system reliability, performance optimization, observability and cloud environment.
Skilled in developing engineers, fostering a collaborative culture, and influencing across ML, data, and product teams to drive impact.

Requirements:
Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and GenerativeAI models at scale.
Experience designing and executing end-to-end research and development plans and generating impact through large-scale machine learning model development. Preferably evidenced by peer-reviewed publication, patents, open sourced code or the like.
Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience), involved in the application of Machine Learning to business problems.
Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
Excellent English communication skills, both written and verbal.
Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators.

Requirements:
M.Sc. or PhD. in Computer Science, Mathematics, Engineering or a related field
6+ years of hands on experience with coding Deep learning / Machine learning / Reinforcement-learning / Statistical modeling based solutions
4+ years Experience modeling auction dynamics in first-price environments (bid shading, market price modeling, win-rate prediction, clearing-price / floor-price estimation)
Strong knowledge in Python
Good knowledge in Java, Scala or C#
Experience in data analysis and visualization and strong knowledge in SQL
Possess strong problem solving and critical thinking skills
Bonus points if you have:
Deep understanding of RTB ecosystems and standards (OpenRTB), header bidding (Prebid client/server), and ad-exchange integrations
Hands-on experience with budgeting/pacing, frequency capping, throttling, and guardrails to meet margin/CPA/ROAS targets
Strong grasp of measurement and calibration (CTR/CVR calibration, eCPM modeling, lift studies) and experimentation (A/B tests, multi-armed bandits)
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills - in Java & Python
Experience with TensorFlow - a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
We are looking for driven MLEs who enjoy solving problems, who initiate solutions and discussions and who believe that any challenge can be scaled with the right mindset and tools.
We have found that people who match the following requirements are the ones who fit us best:
Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.
Minimum of 4 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions.
Strong programming skills in languages such as Python and Java.
Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.
Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.
Experience with data at scale using MySQL, Pyspark, Snowflake and similar frameworks.
Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.
Deep understanding of machine learning algorithms, statistical models, and data structures.
Experience in deploying large-scale language models like GPT, BERT, or similar architectures - an advantage.
Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.

Requirements:
6+ years of experience in hands-on technical roles such as Software Development, QA, Solution Engineering, etc. - Must
Technical hands-on experience in a Web environment - understanding of the ecosystem and ability to debug effectively - Must
Experience in the mobile ecosystem (Android and iOS) - Strong advantage
Bachelors degree in a technical field such as Computer Science, Engineering, or equivalent practical experience
Capability to read and understand code - In a level that allows collaboration with developers and leadership of technical products
Familiarity with at least one of the following programming languages (or a similar one): Java, JavaScript, Python.
Experience with SQL and large-scale data sets, with the ability to analyze and draw conclusions
Experience collaborating with cross functional teams - From Business to R&D
Experience in creating technical documentation and managing knowledge bases
Advanced proficiency in written and spoken English. Exceptional communication and presentation skills
Strong interpersonal skills, ability to influence others, and work effectively in a cross-functional team
Highly experienced and passionate about problem solving and troubleshooting
An independent, self-starter, with a can-do approach
AI knowledge / AI project skills - a big advantage
How youll make an impact:
Own your technical domain by putting any effort required to make it successful
Work closely with our companys Engineering and Product teams on enabling new features/products for scale
Be the voice of Professional Services - Playing a pivotal role in the product lifecycle and its roadmap
Lead the enablement of new products - From Beta, to Limited Availability (LA) through to General Availability (GA)
Serve as the primary technical point of contact during early product rollout and stabilization. Take end-to-end ownership of new products and features.
Enforcing best practices across product operations to ensure consistency, efficiency, and scalability
Deliver, create and maintain in-depth product documentation and training for Professional Services and business teams
Owning and handling highly complex technical escalations coming from Professional Services and consulting on complex implementations/issues coming from clients (may require dev-to-dev calls with clients Engineering teams)
Monitoring product health and performance to identify issues early and analyzing the quality of service (delivery/support) provided to our customers
Managing bugs and feature gaps proactively to improve product health and user trust
Improving Professional Services efficiency through AI developments that streamline decision-making, automate repetitive tasks, and enhance operational visibility.

Requirements:
Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and GenerativeAI models at scale.
Experience designing and executing end-to-end research and development plans and generating impact through large-scale machine learning model development. Preferably evidenced by peer-reviewed publication, patents, open sourced code or the like.
Relevant work or academic experience (MSc + 6 years of working experience, or PhD + 4 years of working experience), involved in the application of Machine Learning to business problems.
Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
Excellent English communication skills, both written and verbal.
Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators.

Requirements:
Bachelors degree in Electrical, Computer, or Software Engineering, or Computer Science.
Minimum 8 years of experience in system validation, verification, or integration across firmware and embedded software, including machine learning algorithm validation.
Demonstrated leadership in defining validation processes, methodologies, and quality standards.
Proficiency in Python and Bash scripting for automation and test development.
Experience with CI/CD pipelines, Git workflows, Docker, and cloud environments (AWS - advantage).
Strong analytical and debugging skills with the ability to drive system-level quality improvements.
Excellent communication skills with the ability to influence, coach, and align cross-functional teams.
Preferred Qualifications:
Experience with validation environments such as FPGA, emulation, RTL simulation, or post-silicon bring-up.
Background in embedded firmware practices (C/C++) and build systems (GNU Make, CMake).
Proven success in defect prevention initiatives and continuous improvement programs.
Familiarity with automotive standards (ISO 26262, ASIL-B, MISRA-C).
Hands-on experience with semiconductor test equipment (Advantest, Teradyne, or equivalent ATE platforms), including test program development, debug, and validation workflows.

Requirements:
Must-Have:
10+ years in software QA / Quality Engineering, including automation.
5+ years in a quality leadership or quality management role.
Experience with distributed cloud systems (AWS / Azure / GCP).
Strong understanding of backend microservices, frontend UI frameworks, and data pipelines.
Proven experience with test automation frameworks (Playwright, Cypress, pytest, etc.).
Experience with CI/CD pipelines and DevOps tooling.
Excellent understanding of the SDLC and Agile processes.
Strong analytical, problem-solving, and data-driven decision-making skills.
Excellent communication and stakeholder management abilities.
Nice-to-Have:
Experience with ML model validation and ML lifecycle quality.
Knowledge of observability stacks (Prometheus, Grafana, Kibana, ELK).
Experience with performance, scalability, and resiliency testing.
Experience working with SQL/noSQL databases and large-scale datasets.

Requirements:
5+ years in product management or in leading teams developing firmware or embedded software products.
Strong technical understanding of embedded systems and hardware-software integration.
A strategic thinker who thrives in fast-paced, innovation-driven environments.
A strong communicator, capable of bridging the gap between technical teams and stakeholders.
Familiarity with Agile methodologies and tools (JIRA, Confluence, etc.).

Requirements:
An experienced Product Manager with a background in the semiconductor industry with:
Proven track record of managing complex technical products end-to-end
Strong understanding of semiconductor test flows (specific knowledge of ATE platforms and system-level validation is a plus)
Background in either Yield management, Semiconductor Product engineering, System engineering, and/or data analytics
Excellent communication and stakeholder management skills
Familiarity with Agile methodologies and tools (JIRA, Confluence, etc.)

Requirements:
Proven analytical competencies
Strong communication skills
Experience working with many stakeholders and different teams
Background in Product Management, Data Analysis, Sales, Digital Marketing or Growth Management.
Proven experience in execution and full ownership of projects
Interest in mobile games
Bachelors Degree in Economics, Statistics, Industrial Engineering, Management or Business Administration.