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Requirements:
Requirements Education & Experience: M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field—with a distinct specialization in Computer Vision or Pattern Recognition. At least 3 years of proven industry experience developing algorithms in the fields of Image Processing and Computer Vision. Technical Skills:
* In-depth knowledge and hands-on experience in classic Image Processing & Computer Vision methods.
* Strong familiarity with Deep Learning frameworks and solutions for complex visual tasks.
* Extensive, hands-on experience in C and C++ programming for large-scale applications.
Advantages (Nice to Have)
* Experience implementing and deploying algorithms on low-power, Real-Time (RT) Embedded systems.
* Practical knowledge and programming experience in Python
* Practical knowledge and experience in Matlab

Requirements:
B.Sc in Industrial Engineering \\& Management or equivalent.
1+ year of experience in Project Management in a fast-paced environment.
Strong problem-solving and troubleshooting skills, with a proactive and detail-oriented mindset.
Strong communication and interpersonal abilities, fostering collaboration and relationship-building across teams. Fluent English is required.
Technical orientation, including familiarity with software development processes, data-driven thinking, and AI-based tools or workflows.
You might also have:
Familiarity with the AdTech industry.
Familiarity with the Android environment.
Familiarity with JIRA or similar project management tools.

Requirements:
3+ years of hands-on experience in data analytics.
Payments fraud experience.
Experience working with external stakeholders/merchants.
Expertise in SQL with the ability to write and optimize complex quries.
Strong analytical skills, problem-solving mindset, and ability to extract insights from large datasets.
Ability to work cross-functionally in a fast-paced, data-driven environment.
Fluent English with excellent written and verbal communication skills.
Experience with Python (Pandas, etc.) for data analysis - a plus.

Requirements:
3+ years of hands-on experience in data analytics.
Payments fraud experience.
Expertise in SQL with the ability to write and optimize complex queries.
Strong analytical skills, problem-solving mindset, and ability to extract insights from large datasets.
Ability to work cross-functionally in a fast-paced, data-driven environment.
Fluent English with excellent written and verbal communication skills.
Experience with Python (Pandas, etc.) for data analysis - a plus.

Requirements:
Experience: Minimum of 3+ years of applied Data Science experience with a proven track record across fintech domains, with experience in fraud, risk, or payments preferred.
Production Expertise: Proven, hands-on experience deploying and maintaining machine learning models in high-traffic production environments is required, with real-time experience preferred.
Data Science Tech Stack: Expert-level Python programming (Pandas, NumPy, Scikit-Learn, XGBoost/LightGBM) and exceptional SQL skills for querying massive, complex datasets.
Data Environment: Robust experience working within cloud data environments like Databricks, and querying/manipulating large-scale datasets in data warehouses like BigQuery.
Orchestration & MLOps: Practical experience with machine learning lifecycle and orchestration tools, such as MLflow and Airflow.
Business-Impact Focus: A strong ability to translate raw model results into real-world business outcomes. You know how to balance technical model performance (precision/recall) with financial impact, operational realities, and the user experience.

Requirements:
A business-oriented mindset focused on delivering results.
Sharp analytical skills to uncover insights and solve complex challenges.
A true team player-collaboration is central to innovation!
Someone who takes initiative and approaches challenges with confidence and curiosity.
2+ years of experience in Business Analyst (Gaming industry- must)
Experience building dashboards using modern BI tools
Strong ability to explain complex data concepts and insights to non-technical audiences
Extensive SQL skills and experience working with large, complex datasets
Strong presentation and communication skills and proficiency in English
You might also have:
Experience working with Cursor - an advantage.

Requirements:
Experience: 1-2 years of hands-on professional experience as a Data Scientist or Data Analyst in a data-intensive environment.
Data Science Tech Stack: Solid proficiency in Python (Pandas, NumPy, Scikit-Learn) and strong capability writing and optimizing SQL queries.
Modern Data Infrastructure: Exposure to or basic hands-on experience working within environments like Databricks and data warehouses like BigQuery.
Academic Background: Degree in a quantitative field (Computer Science, Statistics, Data Science, Industrial Engineering, or equivalent).
Business-Impact Focus: An understanding of how to look past raw model metrics (precision/recall) to appreciate the operational impact of data decisions.
Communication: Fluent English with the ability to communicate technical findings clearly to team members.
Bonus Points
Prior exposure to or hands-on projects involving machine learning models in a live, real-time production environment.
Familiarity with MLOps or orchestration tools such as MLflow or Airflow.
Previous domain exposure in FinTech, e-commerce, payments, or trust & safety.

Requirements:
Experience: 5+ years as a Software Engineer, with 1-2 years hands-on building and shipping AI/LLM-powered systems to production.
Engineering Fundamentals: Strong backend engineering skills with sound software engineering principles - APIs, testing, and clean architecture.
Agentic Systems: Hands-on experience designing and building LLM-powered agents using modern agentic frameworks (e.g., LangChain, LangGraph, Claude/OpenAI Agents SDK), including experience building MCP servers.
Production LLM: Proven track record deploying agentic applications to production - managing latency, cost, reliability, and failure modes.
Evaluation \\& Observability: Experience building evaluation frameworks and LLM observability tooling (e.g., Langfuse or similar).
Cloud \\& Infrastructure: Hands-on with cloud platforms (GCP/AWS), containerization (Docker, Kubernetes), and CI/CD pipelines.
AI Tooling: Fluency with modern AI coding tools (Cursor, Claude Code, Copilot) and agentic workflows - leveraging AI to accelerate the full software development lifecycle.
Cross-Functional Collaboration: Ability to partner with Data Scientists, ML Engineers, Product Managers, and Analysts to translate requirements into production systems.
Ownership \\& Urgency: Strong sense of ownership and urgency, comfort with ambiguity, ability to operate independently and move fast.

Requirements:
Experience building backend services at scale
Proficiency in Golang, and relational databases (e.g., MySQL)
Familiarity with cloud infrastructure and observability tools (Kubernetes, Ray, etc.)
Understanding of API design, distributed systems, and system reliability
Strong collaboration and communication skills in a remote-first team environment
You might also have:
Experience in ad tech, programmatic advertising, or real-time bidding systems
Background with infrastructure-as-code (e.g., Terraform)
Familiarity with networking, caching, or real-time data pipelines.

Requirements:
3+ years of experience as a Front-end Developer, with a strong focus on the Angular Framework.
Proficiency in TypeScript, JavaScript, and CSS (experience with SASS/LESS is a plus).
Deep knowledge of performance optimization techniques and browser troubleshooting.
Active engagement with AI development tools (Copilot, Cursor, Claude, etc.) with a strong emphasis on prompt engineering.
Critical thinking skills, a sense of ownership, and a team-player mentality.
Excellent interpersonal and communication skills.
Proven experience in Backend development and full-stack ownership; we are open to any programming language for the Backend.

Requirements:
BSc in Computer Science or a related degree from a recognized institution, or a strong track record in full stack development with advanced technical skills.
4+ years of experience in software engineering, with demonstrated delivery ofproduction features across both frontend and backend.
Strong proficiency with modern frontend frameworks such as React, Angular, or Vue, including TypeScript, component design, and state management for complex data-driven UIs.
Proficiency in one or more modern backend languages such as Python, Kotlin, Java, Go, C#, or equivalent, with the ability to adapt to new tools and technologies.
Solid understanding of RESTful APIs, HTTP, authentication/authorization flows, and integration of third-party tools and services.
Experience designing and consuming APIs that power rich, interactive frontend experiences.
Familiarity with distributed systems and cloud-native architecture (e.g., Kubernetes, microservices).
Working knowledge of data stores and messaging systems (e.g., PostgreSQL, Elasticsearch, Snowflake, Kafka, or Redis) sufficient to reason about performance and data flow end-to-end.
Experience with cloud platforms such as AWS, Azure, or GCP, and with modern CI/CD and frontend build/deployment workflows.
Strong problem-solving skills, with experience debugging issues across the full stack-from browser devtools to server logs and traces.
A proactive approach to task prioritization and a history of owning features from design through deployment with minimal supervision.
Prior experience working in the cybersecurity industry or with security-centric data pipelines and protocols is an advantage.
Bonus: Experience building developer-facing tools, SDKs, low-code/configuration UIs, or AI-assisted experiences

Requirements:
BSc in Computer Science or a related degree from a recognized institution, or a strong track record in server-side development with advanced technical skills.
6+ years of experience in software engineering with a demonstrated ability to work on large-scale projects and solve complex technical problems.
Proficiency in one or more programming languages such as C/C++, C#, Java, Go, or Python, with the ability to adapt to new tools and technologies.
Solid experience building scalable, distributed systems with an understanding of microservices architecture and API design.
Experience with cloud platforms such as AWS, Azure, or GCP, with knowledge of best practices for deploying and maintaining cloud-based services.
Strong problem-solving skills, with experience debugging and resolving production issues in complex systems.
Ability to prioritize tasks, manage workload efficiently, and contribute to the technical growth of the team.