• Higher education in management, public administration, international relations or related fields;
• At least 3 years of experience in leadership positions;
• English language proficiency at least C1 level;
• Proven experience in organizing major government, international or corporate events;
• Successful experience in managing projects, teams, and budgets;
• Understanding current trends and the global ecosystem of artificial intelligence;
• Developed skills in strategic planning, communication and partnership management.

• Java 17, Spring Boot (Web, Data JPA, Security) — at least 3 years of commercial development

• PostgreSQL: confident SQL, schema design, query optimization

• REST API design and support, pure domain logic

• Git (feature-branch, merge request, rebase), code review, unit/integration tests

• Docker, CI/CD team work (GitLab)

It will be a plus (nice-to-have):

• IoT: real-time event processing from devices, message broker (MQTT)

• Queues/streaming (Kafka), WebSocket, high load and fault tolerance

• Embedded devices, firmware update delivery (OTA)

• Python (FastAPI) — part of the services on it

• Multitenancy, security, data isolation

Sajda is opened every day — often in the most personal moments of life. We are looking for a designer who understands this responsibility and loves painstaking work on details.

We are looking for a designer with at least 5 years of experience and released mobile applications in his portfolio: confident in Figma and able to assemble a design system that developers are comfortable working with; knowledgeable enough about iOS HIG and Material Design to feel when to follow the platform and when to move away from it; who led the product from the task statement before the iterations after the release, he worked with multilingual interfaces (Russian, Kazakh, English, Arabic — RTL, different line lengths, typography of different alphabets), explains decisions using metrics rather than personal taste, knows how to accept criticism and give it, and respects the religious context of the product.

It will be a plus: motion design (Rive, Lottie, After Effects), illustrations and icons, experience in educational products, understanding the possibilities and limitations of SwiftUI.

• 3+ years of relevant experience in the Data Engineering field
• Expertise in Spark
• Expertise in Databricks
• Experience in working with Azure Cloud
• Ability to write robust code with Scala
• Strong SQL skills
• Experience with building Data lakes, Data warehouses, and ETL solutions
• Understanding of data structures, data modeling, and software architecture
• Analytic and problem solving skills

Backend development experience in C# and .NET — from 10 years old.

Deep understanding of algorithms and data structures.

Practical experience working with performance-critical components .NET: multithreading, memory/allocations, GC, Span<T>/structs.

Higher education in computer science, mathematics or related technical fields.

Experience in trading, fintech, high frequency trading or other low latency/real-time systems.

He made real architectural decisions and trained other developers.

The intersection of working hours for at least 4 hours in the interval from 9:00 a.m. to 5 p.m. Eastern Time (EST).

Work experience of at least 10 years

English - level B2+ or higher (for communication with the team).

Available for up to 3 weeks.

Data verification:

• Having a criminal record.

• Legal status at the location.

We are looking for someone who can understand how a product should work, check if it actually works, and help the team translate customer ideas and requirements into clear development goals.

A suitable candidate should be able to: a) systematically test web products, including new features, integrations, user flows, boundary situations, and regression scenarios; b) turn business requirements, customer requests, and product ideas into understandable and manageable user stories; c) create acceptance criteria that can be tested in practice; d) identify missing details, contradictions, and unclear requirements before development begins; e) clearly document errors, including the stages of reproduction, expected behavior, actual behavior, and supporting evidence; f) prepare and maintain product documentation, technical documentation, and user documentation; g) work comfortably with developers and discuss technical issues in practice. h) perform basic product configuration and, if necessary, make minor technical changes.

Experience working with APIs, databases, SQL, scripts, non-coding tools, or basic interface/backend development skills would be a great advantage.

We do not expect this person to be a senior developer. However, they must be technically confident, willing to explore problems on their own, and able to solve simple setup or development tasks without relying on a team of engineers for every minor change.

We are looking for someone who can independently develop sales and partnerships for Orken Tech and our product, Tamga.

The right candidate should: a) have at least 2 years of experience in B2B sales, business development or partnerships; b) be comfortable with outreach, business correspondence, calls and meetings; c) know how to find and approach relevant decision-makers; d) be able to manage a longer sales cycle and follow through on commitments; e) write clear commercial proposals, emails, presentations, and applications; f) keep track of several opportunities at the same time without losing momentum; g) be proactive and comfortable working in an early-stage company where not every process is fully established

Experience with SaaS, IT services, corporate clients, government organisations, accelerators, grants, or investment funds would be an advantage. We are not looking for someone who only sends messages from a prepared contact list. This role requires initiative, good judgement and the ability to move a conversation towards a practical result

Responsibilities:

• Design and build end-to-end ML pipelines covering feature engineering, model training, backtesting, validation, reporting, and batch inference.
• Convert data science prototypes into reliable and maintainable production solutions.
• Develop a configurable ML framework using reusable components and parameter-driven workflows.
• Build and maintain Python-based ML workflows using an existing codebase.
• Support data preparation and transformation workflows in Snowflake and dbt Cloud.
• Implement data quality checks, automated testing, versioning, monitoring, and CI/CD.
• Integrate model outputs into downstream business systems and operational workflows.
• Contribute to architecture decisions and propose practical implementation approaches.
• Support production operations, troubleshooting, model refreshes, and continuous improvement.
• Collaborate with data scientists, data engineers, architects, and business stakeholders.

What we expect:

• 6–8 years of experience in machine learning engineering, software engineering, data engineering, or a related field.
• Strong Python software engineering skills, including experience with reusable and object-oriented code.
• Experience building production ML pipelines.
• Hands-on experience with traditional ML methods and libs (pandas, NumPy, scikit-learn, PyTorch).
• Hands-on experience with Docker.
• Strong SQL and data engineering skills.
• Practical experience with Snowflake and dbt Cloud.
• Experience working with AWS.
• Experience with Git-based CI/CD workflows, such as GitHub Actions.
• Understanding of testing, monitoring, versioning, reproducibility, and production support.
• Strong communication, ownership, troubleshooting, and problem-solving skills.

Nice to have:

• Experience with scheduled batch prediction pipelines.
• Experience building configurable frameworks that support multiple products or business units.
• Familiarity with CRM or other downstream business-system integrations.
• Familiarity with Kubernetes, workflow orchestration, or infrastructure as code.
• Exposure to generative AI or LLM-based applications.
• Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments.

Responsibilities:

• Develop predictive models that generate insights, recommendations, and business signals.
• Perform data discovery, exploratory data analysis, feature engineering, and feature selection.
• Build classification, regression, clustering, segmentation, recommendation, and forecasting models.
• Design and execute model validation, experimentation, and backtesting methodologies.
• Evaluate model performance and translate results into clear business recommendations.
• Develop reusable modeling frameworks and reproducible Python workflows.
• Work with data stored in Snowflake and transformations developed in dbt Cloud.
• Partner with ML engineers to containerize, deploy, monitor, and improve models in production.
• Support model retraining, performance monitoring, and continuous improvement.
• Translate business questions into analytical hypotheses, measurable objectives, and practical solutions.
• Communicate findings, assumptions, risks, and business implications to technical and non-technical stakeholders.
• Collaborate with data engineers, ML engineers, product teams, and business stakeholders.

What we expect:

• 6–8 years of experience in data science, applied machine learning, statistics, or a related field.
• Strong Python and SQL skills.
• Hands-on experience with traditional ML methods and libs (pandas, numpy, scikit-learn, pytorch).
• Strong knowledge of predictive modeling, statistical analysis, experimentation, and model evaluation.
• Experience designing validation and backtesting frameworks.
• Practical experience with Snowflake and cloud-based analytics platforms.
• Experience taking models from experimentation through production deployment.
• Familiarity with Docker, data engineering concepts, and MLOps practices.
• Strong analytical thinking, communication, stakeholder management, and problem-solving skills.

Nice to have:

• Experience developing models that generate customer-level insights or recommendations.
• Familiarity with AWS and dbt Cloud.
• Knowledge of causal inference, experimentation, or optimization methods.
• Exposure to generative AI, LLM-based applications, graph analytics, or RAG.
• Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments.

Design and produce a comprehensive Low Level Design (LLD) for the target Microsoft 365 environment.

Plan and deliver an end-to-end Microsoft 365 tenant-to-tenant migration.•Build and configure a new Microsoft 365 tenant.

Migrate workloads including: Microsoft 365 users Groups and Teams SharePoint Intune-managed devices

Configure and validate: Conditional Access Multi-Factor Authentication (MFA) Intune Configuration & Compliance Policies Role-Based Access Control (RBAC)

Job Specification for Microsoft365 Tenant Migration pg.

2oEnterprise Applications and Single Sign-On (SSO) Data Loss Prevention (DLP)

Produce migration plans, run books and communication plans.

Review licensing and recommend the most appropriate Microsoft licensing model.

Troubleshoot migration issues and provide post-migration support.

Produce comprehensive handover and operational documentation.

Manage project delivery, timelines, dependencies and stakeholder communications throughout the engagement.

Proven experience delivering end-to-end Microsoft 365 tenant-to-tenant migrations.

Strong experience producing Low Level Design (LLD)documentation for Microsoft 365 environments.

Excellent Microsoft 365 administration experience, including: Entra ID (Azure AD)

Exchange Online SharePoint Online Microsoft Teams , Conditional Access Microsoft Defender

Experience configuring Identity, Security and Compliance services.

Strong understanding of Microsoft licensing.

Experience using migration tools (e.g. Bit Titan Migration Wiz or similar).

Demonstrable project management experience, including planning, risk management, stakeholder management and delivery coordination.

Job Specification for Microsoft365 Tenant Migration pg. 3

Excellent technical documentation skills, including design documents, migration run books, implementation guides and handover documentation.

Strong troubleshooting and problem-solving abilities.

Excellent communication skills with both technical and non-technical stakeholders.

Must-Have Experience:

Low Level Design (LLD)

End-to-end Microsoft 365 tenant migration delivery

Project management

Technical documentation

Migration planning and execution

Stakeholder engagement Desirable

Microsoft certifications (Microsoft 365, Azure or Security).

Experience delivering large-scale enterprise migrations.

Experience working within regulated environments.

Knowledge of Microsoft security and compliance best practices.