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Location: Belgrade, Serbia We're looking for a Associate Technical Director with a strong technical background and production expertise to lead the development of multiple mobile projects for one of our partners. In this role, you will be the key stakeholder for technical execution, collaborating with internal teams and external partners to ensure high-quality standards and production efficiency. You will act as an independent auditor, consultant, and technology owner, reporting directly to the Head of Engineering. This position is an excellent opportunity for a Technical Lead or Project Lead to step into a Director-level role within a well-established environment. Responsibilities: Direct technical aspects of development and production, oversee quality management. Promote best practices, technical standards, and the adoption of relevant tools. Identify technical risks early and provide proactive solutions. Define and drive the strategy for core project technology (shared engine, tools, and build system). Mentor Leads and guide Senior Engineers on technology choices, architecture, and design decisions. Make hiring decisions for Senior and Lead candidates. Contribute to the assessment of new project opportunities and bid proposals. Provide necessary support for project kickoffs, including advising on team composition. Initiate knowledge-sharing sessions for software engineers across the department. Represent and promote the Company during customer calls, on-site visits, and industry events. Requirements 7+ years of professional software development experience. 2+ years of experience leading an entire game development team of 8+ software engineers. Professional development experience in C++. Proven experience with mobile development, publishing, and platform limitations (hardware, software, and dependencies). Significant development experience in the following domains: UI, Gameplay, Engine). Significant experience fixing low-level issues (memory, multi-threading, obscure crashes). Experience with task planning, estimation, and tracking. Experience mentoring or hiring Senior engineers. Familiarity with Art and Production workflows within game development. Strong organizational and communication skills. Professional fluency in English (spoken and written). Passion for gaming. Would be a plus: Development experience in AAA games. Professional experience with Unreal Engine. Proficiency in Python, C#, Java, or TypeScript. Strong skills in performance and memory optimization. Experience with back-end development. Experience setting up CI/CD tools (e.g., TeamCity, Jenkins). Experience managing VCS branch structure, preferably in Perforce. Experience with Console development and certification (PlayStation, Xbox, Nintendo Switch). Experience working within globally distributed teams. Experience working with external outsourcing partners. Live Service game ownership experience. Product owner mindset. Deep understanding of management methodologies (Scrum, Waterfall). Benefits Cooperating with an international team of world-class professionals on exciting and challenging projects Learning & Development opportunities – mentoring, lectures, participation at industry conferences and events

Выявление процессов, которые можно автоматизировать ИИ-агентами: интервью с заказчиками, анализ текущей работы, оценка применимости и ожидаемого бизнес-эффекта. Описание сценариев агента: входные данные, доступные действия, бизнес-правила, ожидаемые результаты, уточнения у пользователя и условия передачи задачи человеку.

-Проектировать и разрабатывать микросервисы ядра на Java 17 / Micronaut (без Spring). -Работать с event-driven-обменом: вся межсервисная связь — через брокер сообщений, async-first, database-per-service, eventual consistency.

Responsibilities Execute audio, display, and video ad campaigns across multiple platforms, including DV360, The Trade Desk, Amazon DSP, and others, under the guidance of senior team members. Troubleshoot basic ad-serving and campaign-related issues.

This leader owns customer enablement across Alloy. It is a role that builds and runs the program behind enablement: capturing knowledge continuously, packaging it for the right audience at the right moment, running hands-on customer training sessions, and measuring what works.

Задачи: — Руководство проектированием, разработкой и внедрением on-premises MLOps решений для поддержки доставки моделей машинного обучения — Сотрудничество с дата-сайентистами и разработчиками для создания масштабируемых и эффективных конвейеров данных, систем обучения и деплоя моделей — Разработка и поддержка инструментов мониторинга и управления для обеспечения надежности и производительности MLOps инфраструктуры — Взаимодействие с заинтересованными сторонами для понимания их потребностей в машинном обучении и разработки соответствующих решений — Отслеживание новейших трендов и технологий в области MLOps, машинного обучения и искусственного интеллекта, обмен знаниями с командой — Наставничество младших членов команды и помощь в развитии их навыков в MLOps — Поиск и устранение проблем пользователей Требования: — Опыт работы 5+ лет в MLOps, разработке ПО, инженерии данных или смежных областях — Сильные навыки программирования на современных языках (Java, Scala, Python, Kotlin) — Практический опыт работы с Kubernetes: деплой и эксплуатация рабочих нагрузок, отладка сбоев, работа с основными концепциями (Deployments, ConfigMaps/Secrets, Services, resource limits) — Отличные коммуникативные и командные навыки — Ценность простоты и производительности кода Будет плюсом: — Понимание жизненного цикла ML-проектов — Опыт работы с MLOps платформами, такими как Kubeflow или MLFlow — Опыт с ML-фреймворками: scikit-learn, LGBM, Tensorflow, PyTorch — Опыт работы с Big Data инструментами: Spark, S3, Hadoop — Глубокие знания контейнеризации и оркестрации (Docker, Kubernetes) — Опыт DevOps и CI/CD практик — Опыт создания и масштабирования инструментов для обслуживания моделей, включая построение API с жесткими SLA — Страсть к инженерной стороне машинного обучения и масштабированию — Опыт проектирования и построения MLOps инфраструктуры, включая конвейеры данных, системы обучения и деплоя моделей, а также инструменты мониторинга и управления.

-Разработка нового и доработка существующего функционала на базе 1С Предприятие. -Написание функционала Web-service.

Location: Dubai, United Arab Emirates; London, United Kingdom; Paris, France; Rome, Italy; Russia AHS, is seeking a highly professional, discreet, and experienced Close Protection Officer / Travelling Security to provide personal security and protection for a high-profile principal during daily activities, private engagements, and international travel. The successful candidate will be responsible for maintaining a secure environment, conducting proactive risk assessments, coordinating travel security arrangements, and ensuring the principal's safety, privacy, and comfort at all times. This role requires exceptional situational awareness, sound judgement, flexibility, and the ability to operate discreetly within a private, high-net-worth environment. Responsibilities Provide close protection and personal security for the principal during daily activities, private engagements, and international travel. Conduct advance security assessments of destinations, venues, residences, hotels, and travel routes. Plan and coordinate secure movements, transportation, and travel logistics. Identify potential security threats and implement appropriate preventive measures. Maintain continuous situational awareness and respond effectively to security incidents or emergencies. Coordinate with local security teams, venue personnel, drivers, and relevant authorities when required. Protect the principal's privacy and maintain strict confidentiality regarding personal, professional, and travel-related information. Monitor changing security conditions and adapt protection arrangements accordingly. Maintain professional conduct, readiness, and flexibility in line with the principal's schedule and operational requirements. Prepare security briefings, incident reports, and relevant risk assessments as required. Requirements Proven experience in close protection, executive protection, travelling security, or a comparable personal security role. Experience protecting high-net-worth individuals, senior executives, VIPs, or private principals is highly desirable. Relevant close protection or security training and certifications. Strong knowledge of threat assessment, advance planning, secure movement, and emergency response procedures. Experience accompanying principals on international travel and operating in different security environments. Excellent situational awareness, discretion, communication, and decision-making skills. Physically fit, professionally presented, and capable of maintaining a high level of readiness. Flexible and available to accommodate international travel and changing operational schedules. High level of integrity, confidentiality, emotional control, and professionalism. Valid driving licence and strong driving skills are an advantage. First aid and emergency medical response training are preferred. This position requires the highest standards of discretion and confidentiality when handling all matters relating to the principal, their family, residences, movements, and private affairs. Personal Attributes Discreet, trustworthy, and security-conscious. Calm and composed under pressure. Proactive, observant, and detail-oriented. Adaptable to demanding schedules and international environments. Able to work independently while coordinating effectively with the principal's wider support team. Benefits Why Join AHS? Innovative Environment : Be part of a forward-thinking company that embraces innovation and creativity in the luxury real estate market. Career Advancement : Enjoy opportunities for professional growth and development, with a clear path for career progression. Exclusive Properties : Work with a portfolio of some of the most prestigious and exclusive properties in the market. Collaborative Culture : Join a team-oriented environment where collaboration and mutual support are highly valued. Client-Centric Approach : Be part of a company that prioritizes exceptional customer service and client satisfaction. Competitive Compensation : Receive a competitive salary and benefits package that rewards your hard work and dedication. Global Network : Leverage a robust network of industry contacts and high-net-worth clients. Cutting-Edge Technology : Utilize the latest sales management software and CRM systems to enhance your efficiency and effectiveness. Recognition and Rewards : Benefit from a culture that recognizes and rewards outstanding performance and achievements. Work-Life Balance : Enjoy a supportive work environment that values work-life balance and employee well-being. Please Note: Due to the high volume of applications we receive, only shortlisted candidates will be contacted. We appreciate your understanding.

Location: Dhahran, Saudi Arabia; Riyadh, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates We are seeking an experienced Lead Digital Solutions Analyst to support advanced AI technology initiatives and contribute to the development of next-generation AI solutions. The successful candidate will work on AI modules, scalable data pipelines, backend infrastructure, and real-time data processing systems, supporting the development of Large Language Models (LLMs), Large Time-Series Models, and Large Vision Models. Key Responsibilities Develop and implement AI modules, pipelines, solutions, and services for advanced AI technologies. Design and develop scalable backend infrastructure to support real-time data ingestion, AI model inference, and user access. Build real-time data processing components using event-driven architecture. Apply microservices and agentic AI architectures to support scalability and flexible system development. Develop data pipelines for data preprocessing, normalization, labelling, transformation, feature engineering, and storage. Support research and development initiatives for sovereign AI technologies, including Large Language Models, Large Time-Series Models, and Large Vision Models. Collaborate with cross-functional teams to develop, integrate, and optimize AI-driven solutions. Requirements Bachelor's degree in Graphic Design or an equivalent qualification, as specified for the position. Minimum 10 years of relevant professional experience in graphic design, data science, AI technologies, or a related field. Experience in AI solution development, data pipelines, or AI technology implementation. Knowledge of backend infrastructure, real-time data processing, and event-driven architectures. Familiarity with microservices, agentic AI architectures, and scalable AI applications. Understanding of data preprocessing, transformation, feature engineering, and data storage. Exposure to Large Language Models, time-series models, or computer vision technologies is an advantage. Strong analytical, problem-solving, and collaboration skills.

Location: Almaty, Kazakhstan Workplace: OnSite Software Engineer, Infrastructure Almaty, Kazakhstan Build the shared infrastructure that helps Higgsfield’s product teams ship quickly and run reliable services. You’ll own problems from finding the bottleneck to shipping a solution and supporting it in production. What you’ll do - Build shared services for queues, job scheduling, caching, configuration, and service communication. - Improve concurrency limits, resource allocation, and recovery for long-running media workloads. - Make database access, migrations, and connection management safer and faster. - Simplify service setup, testing, deployment, and production debugging. - Improve observability, investigate incidents, and reduce infrastructure cost per completed job. - Work directly with product engineers, ship focused improvements, and measure the results. Our release cycle is days, not quarters. Required - Experience running production systems on Kubernetes (K8s) and AWS, including deployments, scaling, networking, and troubleshooting. - Strong software engineering skills: you build shared services, tools, and automation that other engineers use. - Experience with databases, queues, and distributed systems, including performance debugging, safe rollouts, and recovery. - A difficult production problem you owned from an unclear starting point to a working solution. - Ability to set priorities, make practical tradeoffs, remove blockers, and ask for help when needed. - Clear communication, openness to feedback, and knowledge sharing so others can operate and extend your work. Nice to have - Cloudflare. - Infrastructure as code. - PostgreSQL, Redis, or event-streaming systems. - High-throughput media pipelines or AI workload orchestration. Interview process 1. Recruiter screen: expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, your decisions, and the results. 3. Additional technical interview, if needed. 4. Product fit interview: investigate a team’s bottleneck and plan a practical improvement, adoption, and safe rollout. 5. Offer. What we offer Competitive base pay in USD, equity, relocation support, and ownership of infrastructure used across our engineering teams.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists Our ML and analytics teams already work on fraud detection and risk analysis. This role owns the backend that turns their signals into reliable protections across accounts, credits, payments, and generation. You'll integrate risk checks into product flows, build enforcement services and operator tools, and make sure controls work correctly in production. We're looking for an engineer we can trust to take a backend problem from an unclear starting point to a working solution. What you'll actually do - Risk integrations: connect existing ML scores and risk signals to account creation, credit usage, payments, and generation flows, with clear timeouts and fallback behavior. - Enforcement services: implement configurable rules, rate limits, account restrictions, and credit or payment controls with consistent behavior across services. - Operator tooling: build APIs and workflows for reviewing cases, inspecting decision history, and safely applying or reversing restrictions. - Production reliability: handle retries, duplicate events, concurrent requests, and safe rollouts; add monitoring and audit trails so failures can be traced and fixed. - Work in other teams’ codebases to add signals or interventions without hurting their stability or architecture. - Ownership: clarify the control with ML, analytics, and operations → scope the smallest useful implementation → ship → verify production behavior and review impact with the team. Our release cycle is days, not quarters, so your first shipped protection happens fast. Must-haves 1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results. 2. You can build reliable backend services: APIs, data models, queues, transactions, idempotency, and concurrency. You can integrate external services and debug failures across the request and event lifecycle. 3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems. 4. You work with ML, analytics, and operations to turn risk requirements into clear backend behavior. You use operator feedback and customer cases to improve controls and learn unfamiliar systems quickly. 5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build. Who this is not for - You prefer problems where requirements stay stable after launch. - You prefer work centered on training models or producing analysis rather than building and operating backend services. Nice to have - Fraud prevention, payments risk, or platform abuse experience. - Integrating risk-scoring services or building rules engines and rate limiters. - Case management, appeals, and risk operations tooling. - Familiarity with Stripe. - Experience building real-time scoring, graph-based account linkage systems. - Python/Go experience. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: take an existing risk signal and an operator need, scope a backend protection, and work through failure cases and effects on legitimate customers. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of protections that preserve both company revenue and customer trust.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists An agent needs more than a model response to complete useful work. It needs tools, durable execution, permissions, context, and a way to recover when something fails. You'll build the backend that lets Higgsfield agents carry creative tasks from a user's request to a finished result. We're looking for an engineer we can trust with a problem: work out what is worth building, build it, and carry it through to users. What you'll actually do - Agent execution: build orchestration for multi-step tasks, tool calls, streaming updates, and cancellation. - Durable workflows: implement checkpoints, resumability, retries, and recovery without duplicating actions. - Tools and integrations: connect agents to generation, editing, and external services through clear, validated interfaces. - Execution boundaries: enforce user permissions, tenant isolation, resource limits, and approval requirements for consequential actions. - Evaluation and observability: trace failures, build regression cases, and improve task completion, latency, and cost. - Ownership: understand a real user task → define success and build evaluation cases → scope the simplest useful workflow → ship → measure completion, reliability, and dollar impact → improve from failed runs. Our release cycle is days, not quarters, so your first shipped agent capability happens fast. Must-haves 1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results. 2. You can build reliable agent execution: state machines, concurrency, queues, recovery, model APIs, secure tool calls, and repeatable evaluations. You learn unfamiliar tools quickly and understand what you ship. 3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems. 4. You investigate real user tasks and failed agent runs, use feedback to choose what to automate, and stop workflows that do not help users finish their work. 5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build. Who this is not for - You prefer deterministic application behavior without investigating model uncertainty. - You prefer prototyping without owning evaluation, recovery, and production reliability. Nice to have - Production agents, workflow engines, or developer tools. - High-throughput systems with heavy traffic, large data volumes, or many long-running jobs. - Agent context management, memory, subagents, or parallel tool calls. - Sandboxed execution and scoped authorization. - Multimodal workflows involving images, video, or audio. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: scope a useful tool-using workflow, evaluate failures, and explain when user feedback would lead you to change or stop it. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of systems that turn AI capabilities into completed creative work.

Location: Almaty, Kazakhstan Workplace: OnSite Almaty, Kazakhstan · Trust & Safety Engineering Why this role exists Higgsfield builds tools for AI creators: creative workflows, collaborative projects in Cinema Studio, and a community for sharing work. We need a backend engineer who combines deep database and architecture expertise with the initiative to own product outcomes, from the first idea to production. What you'll actually do - Build AI creation workflows, Cinema Studio collaboration, and community features: sharing, discovery, contests, profiles, and follows. - Own features and bugs through release and follow-up. Define API contracts and coordinate frontend work to deliver the complete feature. - Deliver responsive UX: live progress, timely updates, and clear failure recovery, even when it takes more engineering effort. - Remove database and service bottlenecks under high traffic; improve correctness, latency, and reliability. - Define success metrics, build dashboards and alerts, and track adoption and system health after launch. Must-haves 1. Deep database expertise: data modeling, indexes, query plans, partitioning, transactions, and locking. You diagnose production bottlenecks and understand the trade-offs behind your fixes. 2. Strong architecture judgment: service boundaries, APIs, asynchronous workflows, caching, and failure handling. Hands-on Kubernetes and CI/CD experience, from design and testing to deployment and debugging. 3. A track record of shipping and operating backend systems across multiple projects, including high-traffic workloads. You can explain your decisions and measurable results. 4. API security: authentication, object-level authorization, and tenant isolation. You prevent IDOR in reads and writes, including resource IDs in request bodies, and test access across users and workspaces. 5. You've built or studied social networks and collaborative tools, and can explain design trade-offs in feeds, follow graphs, notifications, sharing permissions, real-time sync, and concurrent edits. 6. High agency and ownership: you find worthwhile problems, propose improvements, remove blockers, and follow through without waiting for assignments. 7. Low ego: you welcome direct feedback, admit mistakes, change your mind with evidence, and help wherever the team needs you. 8. Ambition and optimism: hard goals and rapid growth energize you. You challenge assumptions constructively and commit to making ambitious ideas work. 9. Energy for an intense pace, shifting priorities, and urgent launches or production issues that can require work outside regular hours. Our tech stack - Languages and frameworks: Python (FastAPI), Go (Gin), and TypeScript (React/Next.js on the frontend). - Data: PostgreSQL and Redis; analytical databases such as BigQuery or ClickHouse. - Messaging: Kafka, Amazon SQS, and RabbitMQ; event-driven services and asynchronous workers. - AWS: S3, DynamoDB, ECR, and Secrets Manager. - Infrastructure: Docker, Kubernetes on Amazon EKS, Helm, Argo CD, and GitHub Actions. - Observability: Prometheus, Grafana, OpenTelemetry, and Sentry. Interview process 1. Recruiter screen: role expectations, logistics, and fit. 2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you. 3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions. 4. Product fit interview: turn a user problem into a small first release, decide what to leave out, and explain how feedback would change the solution. 5. Offer. What we offer Competitive base in USD, equity, relocation support, and ownership of product experiences that directly shape how people create with AI.

🔥Проект - Building and scaling a multi-asset trade and portfolio management platform with strong backend focus including designing, developing, and maintaining backend services, APIs, and data pipelines.

Identify, generate, qualify, and close new business for customers and prospects in a defined territory. Responsible for managing the full sales lifecycle, and building the go-to-market.

Own the value plan for each account in your portfolio, connecting the business problem that led the customer to buy Mixpanel with the outcomes they measure. Build relationships with business and technical stakeholders, aligning Mixpanel's capabilities to what customers care about most.

Location: United States About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking experienced U.S.-licensed attorneys with tax law expertise to support the training and evaluation of next-generation AI systems. You will analyze tax law scenarios, review AI-generated legal analyses and documents, identify errors or gaps in legal reasoning, and provide structured feedback to improve accuracy and completeness. This role is ideal for attorneys with strong legal judgment, excellent written communication, and experience interpreting complex legal issues. Prior AI experience is not required. SENIORITY: Experienced Legal Professional LANGUAGE: Excellent written English LOCATION: Remote — United States only Key Responsibilities Analyze tax law scenarios, identify key legal issues, assess risks, and apply sound legal judgment. Review AI-generated legal analyses, arguments, and documents for legal accuracy, completeness, and consistency. Identify legal errors, missing information, unsupported conclusions, and weaknesses in legal reasoning. Evaluate the application of relevant federal and state tax laws to complex factual scenarios. Provide clear, structured feedback and corrections to improve AI-generated legal outputs. Apply consistent review standards while maintaining strong attention to detail and professional judgment. Requirements Juris Doctor (J.D.) degree from a U.S. law school. Active license to practice law in at least one U.S. state or the District of Columbia. More than 3 years of substantive legal practice, preferably with experience in tax law. Strong legal reasoning, issue-spotting, and legal document review skills. Excellent written English communication and the ability to explain complex legal concepts clearly. Strong analytical skills, attention to detail, and the ability to work independently.

Location: United Kingdom; Germany; Poland; South Africa; United Arab Emirates; Egypt About Gramian Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an accomplished Scientific Research Expert with deep expertise in computer science, computational physics, or related theoretical and mathematical disciplines to contribute to an advanced AI research project. In this role, you will work with frontier AI models and agents to investigate open research problems, evaluate theoretical and computational results, and establish rigorous standards for measuring scientific progress. You will help guide multi-step research workflows involving proofs, algorithms, numerical experiments, simulations, and high-performance computing, while documenting model limitations and identifying promising directions for further investigation. Prior AI industry experience is not required; exceptional research expertise and rigorous scientific judgment are the priorities. SENIORITY: Principal / Research Leader LANGUAGE: Excellent written English LOCATION: Remote — Worldwide Key Responsibilities Identify and formulate foundational open problems, theoretical bounds, and computational challenges where progress can be rigorously demonstrated. Guide AI models and agents through complex, multi-step research workflows involving mathematical proofs, algorithm development, numerical experiments, and high-performance simulations. Validate research results using proof verification, computational reproduction, formal methods, and other rigorous evaluation techniques. Assess the novelty, correctness, and scientific significance of research outputs against established findings and current literature. Prepare concise research memos documenting attempted solutions, partial progress, model limitations, and recurring reasoning failures. Recommend promising research directions, subfields, and open problems suitable for investigation using advanced AI models and computational tools. Apply critical judgment when reviewing technical work beyond your immediate research specialization. Help establish evaluation standards that distinguish genuine scientific progress from plausible but unsupported results. Requirements Approximately 7–10+ years of active research experience in computer science, mathematical physics, computational physics, or a closely related discipline. Strong record of scholarly contributions, including publications in leading conferences, journals, or other recognized research venues. Deep hands-on experience with computational research methods, such as numerical analysis, simulation, algorithm implementation, or high-performance computing. Demonstrated ability to evaluate technical claims rigorously, verify results, and identify gaps in mathematical or computational reasoning. Strong familiarity with the research literature and established results in your field. Excellent analytical, technical writing, and research communication skills. Ability to work independently, assess ambiguous problems, and communicate findings clearly.