Разработка вакансии

Возглавить филиал и обеспечить его выход в лидеры регионального рынка ИТ-интеграции. Опыт работы не менее 6-10 лет.

• Полное управление компанией, включая: разработку, продукт, продажи, сопровождение клиентов, маркетинг, клиентский сервис, финансы, HR, юристы; • Реализация стратегического плана бизнеса;

Задачи: — Разработка приложения на микросервисной архитектуре — Разработка программного кода в соответствии с требованиями (их пишет аналитик) — Диагностика и исправление дефектов (тестировщики находят дефекты) — Поддержка существующего кода, его анализ и оптимизация Требования: — Уверенное владение C# / .NET 5 — Опыт с Entity Framework Core — Знание PostgreSQL Желательно: — Умение правильно готовить микросервисы, знание Apache Kafka и брокеров сообщений — Знание CQRS, AutoMapper, SignalR — Опыт работы с Docker — Понимание и опыт работы с git

Location: US: San Mateo (1875 South Grant Street); CAN: Toronto (111 Richmond Street West); CAN: Vancouver (333 Seymour St); US: Washington Remote Worker Workplace: Hybrid Team: Accounting Core Location / work arrangement: San Francisco, San Mateo and Seattle (Hybrid) Employment type: Full Time About the Role Xero’s ledger is the source of truth for millions of businesses, and every product we ship is built on top of it. We are rebuilding this integrity layer for the next 20 years, and we are standing up the Vancouver engineering hub around it from day one. As Lead Engineer, you will make the architectural decisions that set the course for the platform and the team, and you will see those decisions reach every customer who depends on Xero to get their numbers right.   THE TECHNICAL CHALLENGES - Correctness at scale. Accounting data has to be consistent, auditable, and immutable. There is no “close enough,” and every change to the ledger has to preserve that guarantee across regions and regulations. - Evolving a mature system. We are adding real-time expectations to a platform that millions of businesses depend on daily. That means strengthening service boundaries and clarifying data contracts without compromising reliability. - Durable, high-throughput services. We use durable execution (for example, Temporal) to keep long-running financial workflows accurate and recoverable under load. - AI-ready data. We are structuring accounting data so it can power AI-native experiences while maintaining trust in the numbers.   IMPACT - First six months: You understand the ledger and its consumers, align the team on service boundaries and data contracts, and ship a first modernization increment with no loss of data integrity. - First twelve months: - You have set the architecture for the core accounting capabilities (general ledger, journals, chart of accounts, multi-currency). - The Vancouver engineering team has clear ownership and quality standards, thanks in part to your leadership and role modeling. - Your work reaches customers through every product built on the ledger, and the decisions made now will shape Xero for years.   OWNERSHIP You will own the technical direction for your area of the accounting platform, from design through production and on-call. You will make architectural decisions on service boundaries, data contracts, and technology choices without needing sign-off, and you will be accountable for reliability and data integrity end to end. You will also help set hiring, quality, and ownership practices for an early and growing team, which will compound over time.   WHO YOU’LL WORK WITH Bernardo Farah is the Director of Engineering for Accounting Core. He has over 10 years of SaaS software experience, including six years building platforms and growing teams at Samsara. WHAT YOU BRING MUST-HAVE: - You set the standard for your team in AI-assisted development, operational excellence, and flexible architecture. - A track record delivering highly available, distributed backend systems and designing high-throughput services under production constraints. - Depth in system architecture, API design, and both SQL and NoSQL databases - Proficiency in a modern backend stack such as C#, Java, Go, or C++, plus cloud-native platforms like AWS. - You demonstrate strong ability in breaking down complex problems into clear, actionable solutions while driving agile execution to deliver results. NICE TO HAVE: - Experience with financial, ledger, or accounting systems, or other domains where data integrity is critical - Experience with durable execution or workflow engines such as Temporal - Experience modernizing a mature system without disrupting customers   HOW WE WORK Process is a tool for impact and we adjust accordingly. We use an agile approach to ship outcomes, not to follow ceremony. Code and design reviews are where we trade ideas and hold the quality bar, and we are figuring out how to use LLMs to reduce how much code humans have to write and review by hand. Our on-call rotation draws on a healthy pool of engineers and turns incidents into learning through postmortems. Decisions are made at every level, and we make sure everyone has the strategic context to raise proposals and drive innovation.     Our Hiring Process - Stage 1: Real World coding assessment, 45 Mins - Stage 2: Systems Design assessment, 45 Mins - Stage 3: Technical Deep dive, 60 Mins - Stage 4: Values/ Future Proof, 60 Mins - Stage 5: Leadership interview, 60 mins   Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team. We are also tech stack agnostic, so please apply if you've worked with adjacent technologies. Compensation Philosophy At Xero, we value the impact and skills you bring to the team. We don’t just hire for a role; we invest in people. We believe in a Total Package philosophy - which means your value isn't just a single number on a paycheck. While base salary is a core component, we look at your compensation through a holistic lens that includes equity, performance incentives, and world-class benefits. The base salary range for this role in $206,000 to $260,000 USD Please note that this range represents base salary only. We believe in rewarding our people for their total contribution, which is why we look at compensation through a holistic lens. In addition to base pay, your total package may include: - Variable Pay: Eligibility commissions or equity based on role and performance. - Comprehensive Benefits: World-class health, wellness, and retirement programs. - Xero Perks: Inside Xero https://careers.xero.com/inside-xero/benefits-wellbeing/ Explore our full suite of benefits, from wellbeing initiatives to professional development. Individual pay is determined by various factors, including geography, level of experience, and the specific skills you bring to the role Xero uses AI to help screen applications based on job-related qualifications. These tools assist our recruiters but do not make automated hiring decisions. A human recruiter reviews all candidates before any hiring action is taken.

• Build high-performance edge services in Go. • Design offline-first and cloud-to-edge architecture.

- Профилировать пайплайн от начала до конца и находить реальные узкие места в алгоритмах, C-коде и Db2; - Строить базовые метрики производительности и регрессионные проверки, чтобы доказывать безопасность каждого изменения;

{COMPANY} is looking for an AI Strategist to deploy its platform, advise financial-services customers, and drive measurable value and commercial growth.

{COMPANY} is looking for a Frontend Engineer Agents to build agent-facing web and mobile interfaces, backend APIs, and high-quality real-time product experiences.

Cerebras Systems is looking for a Head of Developer Relations to lead developer advocacy, create technical content, and grow developer adoption.

ElevenLabs is looking for a Systems Architect to build AI-powered revenue operations systems and Salesforce automations.

SpAItial is looking for an ML Inference Engineer to build and operate scalable inference services and production APIs.

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren’t designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren’t built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabric team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world’s top containerd maintainers. As Engineering Manager for Storage Products on the Runtime Fabric team, you will lead the engineers who build and run the storage products behind that stack: the Baseten Delivery Network (BDN), which sits in the cold start path of every model on the platform, the snapshotters and filesystems that expose model weights and container images to a running container, and the storage that model deployment and training need next. The team is advancing the next generation of caching for inference workloads, from the origin tier to the GPU host. You will own reliability for the area as a measured outcome, report to the head of Runtime Fabric, and stay close to the code through design and code review. If you’ve managed systems engineers and have hands-on experience with caching, content-addressable storage, or distributed filesystems, we’d love to talk. EXAMPLE INITIATIVES - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Extending BDN from model weights to container image layers, training checkpoints, and deployment artifacts - Lazy-loading snapshotters and block-level delivery (EROFS, FUSE, ublk) so a container can start before the full image or model has arrived RESPONSIBILITIES Team Leadership and Culture - Hire and grow a team of 5 to 10 systems engineers with storage, caching, and Linux expertise - Run the team’s planning and delivery: scope work against the Runtime Fabric roadmap, set priorities, and ship on a predictable cadence - Provide regular coaching, feedback, and career development support to your direct reports - Own on-call health for the team’s services, including escalation paths and follow-through on incidents Technical Direction - Guide the architecture and evolution of the Baseten Delivery Network: the tiered caching and weight delivery product that makes cold starts 2-3x faster and eliminates thundering herd failures during burst scaling events - Shape storage products tailored to Baseten’s workloads: extend BDN from model weights to container images, training checkpoints, and deployment artifacts, and define the interfaces that model deployment, training, and customers use to reach them - Oversee the on-host side of delivery: lazy-loading snapshotters, EROFS and overlayfs layouts, and block-level delivery (FUSE, ublk) for multi-gigabyte files - Own reliability of the delivery path as a measured outcome: end-to-end instrumentation from snapshotter initialization to first inference request, targets for cold start and cache behavior, tolerance for failing upstream registries and object stores, and safe rollout of changes to a path every customer depends on - Make the delivery path work across heterogeneous clusters and cloud providers, each with its own object store and network - Review designs and code across the area, and take on hands-on work where it unblocks the team - Champion the team’s contributions back to containerd and the snapshotter ecosystem alongside the maintainers on the Runtime Fabric team Cross-Functional Partnership - Act as the point of contact for storage across Baseten, ensuring model deployment, training, and platform teams have the integration support they need - Optimize requirements for the underlying storage platforms with the infrastructure team: object storage, local NVMe and block storage, and network bandwidth per cluster, so that capacity and provider decisions account for what the delivery path needs - Manage the team’s dependencies in both directions: sequence work that model deployment, training, and infrastructure teams block on, and negotiate interfaces and timelines with the teams and upstream projects the storage path depends on - Work with the head of Runtime Fabric and product stakeholders to prioritize storage investments based on customer impact and infrastructure reliability - Communicate team progress, technical trade-offs, and incidents clearly to the team and to leadership REQUIREMENTS - Experience managing a team of engineers in a systems, infrastructure, or storage context, including hiring and performance management - Hands-on background in distributed storage systems, content-addressable storage, or large-scale caching infrastructure - Strong systems programming background in Go, Rust, and/or C/C++, with the ability to engage credibly in code reviews and architectural discussions - Working knowledge of the Linux storage stack: filesystems, the page cache, block devices, and mounts - Understanding of how container images are structured, stored, and delivered at scale - Strong written and verbal communication skills, with the ability to influence without authority across teams NICE TO HAVE - Contributions to containerd/containerd, snapshotter projects (stargz, soci, nydus, overlaybd), distribution/distribution, or closely related open-source projects - Familiarity with lazy-loading snapshotters or peer-to-peer image distribution - Experience with EROFS, FUSE, ublk, or io_uring - Experience building or operating CDN, object storage, or large-scale caching infrastructure - Experience running storage services on Kubernetes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Bangladesh; Brazil; India; Colombia; Egypt; Ghana 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 experienced Mechanical or Aerospace Engineering Expertto lead a team of technical trainers developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for engineering accuracy and reproducibility, and ensure automated graders reliably assess technical outcomes. This role combines advanced engineering expertise, computational modeling, technical quality assurance, and team leadership to help evaluate and improve next-generation AI systems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead and mentor a team of 5–10 technical trainers, ensuring consistent task quality, productivity, and timely delivery. Review engineering tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests. Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics. Ensure tasks reflect realistic mechanical and aerospace engineering workflows and require meaningful, multi-step technical reasoning. Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability. Validate computational environments, simulation tools, solvers, and dependencies to ensure reproducible results. Review automated graders to ensure they assess meaningful engineering outputs, including stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins. Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations or simulations. Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices. Requirements PhD, postdoctoral experience, or equivalent advanced technical expertise in Mechanical Engineering, Aerospace Engineering, or a closely related discipline. Strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave. Proficiency in Linux and command-line environments. Hands-on expertise in at least one major area, such as FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, guidance, navigation and control (GNC), or propulsion modeling. Strong understanding of engineering simulation, numerical methods, computational modeling, and technical validation. Experience reviewing complex technical work, engineering simulations, computational models, or research outputs. Ability to assess engineering assumptions, numerical accuracy, solver convergence, and computational reliability. Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for precise technical feedback and documentation.

Location: Pakistan; Indonesia; Kenya; Turkey; Nigeria; Vietnam 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 experienced Mechanical or Aerospace Engineering Expertto lead a team of technical trainers developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for engineering accuracy and reproducibility, and ensure automated graders reliably assess technical outcomes. This role combines advanced engineering expertise, computational modeling, technical quality assurance, and team leadership to help evaluate and improve next-generation AI systems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead and mentor a team of 5–10 technical trainers, ensuring consistent task quality, productivity, and timely delivery. Review engineering tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests. Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics. Ensure tasks reflect realistic mechanical and aerospace engineering workflows and require meaningful, multi-step technical reasoning. Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability. Validate computational environments, simulation tools, solvers, and dependencies to ensure reproducible results. Review automated graders to ensure they assess meaningful engineering outputs, including stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins. Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations or simulations. Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices. Requirements PhD, postdoctoral experience, or equivalent advanced technical expertise in Mechanical Engineering, Aerospace Engineering, or a closely related discipline. Strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave. Proficiency in Linux and command-line environments. Hands-on expertise in at least one major area, such as FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, guidance, navigation and control (GNC), or propulsion modeling. Strong understanding of engineering simulation, numerical methods, computational modeling, and technical validation. Experience reviewing complex technical work, engineering simulations, computational models, or research outputs. Ability to assess engineering assumptions, numerical accuracy, solver convergence, and computational reliability. Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for precise technical feedback and documentation.

Location: Bangladesh; Brazil; Colombia; Egypt; Ghana; India 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 experienced Computer Science, Electrical Engineering, or Computer Engineering Expert to lead a team of technical trainers developing realistic, terminal-based tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for technical accuracy, reproducibility, and grading reliability, and ensure they reflect authentic software, computational, and electrical engineering workflows. This role combines advanced technical expertise, computational problem-solving, quality assurance, and team leadership to help evaluate and improve next-generation AI systems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead and mentor a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely task delivery. Review technical tasks end to end, including problem statements, codebases, circuit netlists, hardware description languages (HDL), datasets, computational environments, reference solutions, and automated tests. Validate tasks involving high-performance computing (HPC), parallel computing, algorithms, distributed systems, compilers, operating systems, databases, machine learning systems, GPU computing, circuit design, signal processing, power systems, and embedded systems. Ensure tasks reflect realistic software engineering, research, and electrical engineering workflows requiring meaningful, multi-step technical reasoning. Verify technical correctness across algorithm complexity, numerical accuracy, memory management, concurrency, circuit laws, power balance, signal processing, timing constraints, and system stability. Validate compilers, simulation tools, software dependencies, computational environments, and build processes to ensure reproducible results. Identify unreliable tests caused by nondeterministic behavior, race conditions, hardware-dependent performance thresholds, or simulation convergence issues. Review automated graders to ensure they assess meaningful technical outputs, including functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior. Identify technical inaccuracies, flawed assumptions, incorrect tolerances, and ways tasks could be bypassed without genuine computation or engineering analysis. Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices. Requirements PhD, postdoctoral experience, or equivalent advanced technical expertise in Computer Science, Electrical Engineering, Computer Engineering, or a closely related discipline. Strong programming skills in C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or hardware description languages (HDL). Advanced proficiency in Linux and command-line environments. Hands-on expertise in at least one major area, such as parallel computing, systems programming, scientific software development, circuit simulation, signal processing, power systems, or digital hardware design. Strong understanding of algorithms, computational systems, numerical methods, software testing, or electrical engineering principles. Experience reviewing complex codebases, technical implementations, engineering simulations, or research outputs. Ability to evaluate algorithm correctness, computational performance, numerical accuracy, concurrency behavior, and technical reliability. Strong analytical judgment and the ability to identify technical errors, edge cases, race conditions, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for precise technical feedback and documentation.

Location: Turkey; Nigeria; Kenya; Pakistan; Indonesia; Vietnam 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 experienced Computer Science, Electrical Engineering, or Computer Engineering Expert to lead a team of technical trainers developing realistic, terminal-based tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for technical accuracy, reproducibility, and grading reliability, and ensure they reflect authentic software, computational, and electrical engineering workflows. This role combines advanced technical expertise, computational problem-solving, quality assurance, and team leadership to help evaluate and improve next-generation AI systems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead and mentor a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely task delivery. Review technical tasks end to end, including problem statements, codebases, circuit netlists, hardware description languages (HDL), datasets, computational environments, reference solutions, and automated tests. Validate tasks involving high-performance computing (HPC), parallel computing, algorithms, distributed systems, compilers, operating systems, databases, machine learning systems, GPU computing, circuit design, signal processing, power systems, and embedded systems. Ensure tasks reflect realistic software engineering, research, and electrical engineering workflows requiring meaningful, multi-step technical reasoning. Verify technical correctness across algorithm complexity, numerical accuracy, memory management, concurrency, circuit laws, power balance, signal processing, timing constraints, and system stability. Validate compilers, simulation tools, software dependencies, computational environments, and build processes to ensure reproducible results. Identify unreliable tests caused by nondeterministic behavior, race conditions, hardware-dependent performance thresholds, or simulation convergence issues. Review automated graders to ensure they assess meaningful technical outputs, including functional correctness, performance, frequency response, waveforms, timing, efficiency, and system behavior. Identify technical inaccuracies, flawed assumptions, incorrect tolerances, and ways tasks could be bypassed without genuine computation or engineering analysis. Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices. Requirements PhD, postdoctoral experience, or equivalent advanced technical expertise in Computer Science, Electrical Engineering, Computer Engineering, or a closely related discipline. Strong programming skills in C/C++, Rust, Python, Julia, Fortran, MATLAB/Octave, or hardware description languages (HDL). Advanced proficiency in Linux and command-line environments. Hands-on expertise in at least one major area, such as parallel computing, systems programming, scientific software development, circuit simulation, signal processing, power systems, or digital hardware design. Strong understanding of algorithms, computational systems, numerical methods, software testing, or electrical engineering principles. Experience reviewing complex codebases, technical implementations, engineering simulations, or research outputs. Ability to evaluate algorithm correctness, computational performance, numerical accuracy, concurrency behavior, and technical reliability. Strong analytical judgment and the ability to identify technical errors, edge cases, race conditions, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for precise technical feedback and documentation.

Location: Bangladesh; Brazil; Colombia; Egypt; Ghana; India 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 experienced Chemical Engineering Expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for technical accuracy, reproducibility, and grading reliability, and ensure that each task reflects authentic chemical engineering workflows. This role combines advanced chemical engineering knowledge, computational modeling, technical quality assurance, and team leadership to improve how AI systems solve complex engineering problems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead, mentor, and coordinate a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely delivery. Review engineering tasks end to end, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests. Validate tasks involving reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering. Ensure tasks reflect realistic chemical engineering workflows and require meaningful, multi-step technical reasoning. Verify mass and energy balances, thermodynamic consistency, property data, unit handling, numerical accuracy, and solver convergence. Validate computational models, stiff ODE/DAE solvers, tolerances, initial conditions, dependencies, and simulation results for reproducibility. Review automated graders to ensure they assess meaningful engineering outputs, including conversion, yield, selectivity, purity, energy consumption, and process constraint satisfaction. Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations. Provide actionable technical feedback, track revisions, and ensure issues are resolved before task approval. Onboard trainers, allocate assignments, monitor quality and throughput, resolve technical blockers, and maintain documentation and best practices. Requirements PhD, postdoctoral experience, or equivalent advanced technical expertise in Chemical Engineering. Strong programming skills in Python, Julia, C/C++, or MATLAB/Octave. Proficiency in Linux and command-line environments. Hands-on expertise in at least one major area, such as process modeling, reaction kinetics, thermodynamic modeling, process simulation, or optimization. Strong understanding of chemical engineering fundamentals, numerical methods, computational modeling, and technical validation. Experience reviewing complex technical work, chemical process simulations, computational models, or research outputs. Ability to evaluate mass and energy balances, thermodynamic assumptions, numerical accuracy, solver convergence, and computational reliability. Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for precise technical feedback and documentation.

Location: Pakistan; Indonesia; Kenya; Nigeria; Turkey; Vietnam 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 experienced Chemical Engineering Expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for advanced AI training and evaluation. You will oversee a pod of approximately 5–10 trainers, review tasks for technical accuracy, reproducibility, and grading reliability, and ensure that each task reflects authentic chemical engineering workflows. This role combines advanced chemical engineering knowledge, computational modeling, technical quality assurance, and team leadership to improve how AI systems solve complex engineering problems. CONTRACT: Contractor assignment, 4 weeks COMMITMENT: Hourly, up to 40h/week LOCATIONS: Remote - Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam PROCESS: AI Interview NOTES: PhD Degree is mandatory! Key Responsibilities Lead, mentor, and coordinate a team of 5–10 technical trainers, ensuring consistent quality, productivity, and timely delivery. Review engineering tasks end to end, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests. Validate tasks involving reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering. Ensure tasks reflect realistic chemical engineering workflows and require meaningful, multi-step technical reasoning. Verify mass and energy balances, thermodynamic consistency, property data, unit handling, numerical accuracy, and solver convergence. Validate computational models, stiff ODE/DAE solvers, tolerances, initial conditions, dependencies, and simulation results for reproducibility. Review automated graders to ensure they assess meaningful engineering outputs, including conversion, yield, selectivity, purity, energy consumption, and process constraint satisfaction. Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass genuine engineering calculations. Provide actionable technical feedback, track revisions, and ensure issues are resolved before task approval. Onboard trainers, allocate assignments, monitor quality and throughput, resolve technical blockers, and maintain documentation and best practices. Requirements PhD, postdoctoral experience, or equivalent advanced technical expertise in Chemical Engineering. Strong programming skills in Python, Julia, C/C++, or MATLAB/Octave. Proficiency in Linux and command-line environments. Hands-on expertise in at least one major area, such as process modeling, reaction kinetics, thermodynamic modeling, process simulation, or optimization. Strong understanding of chemical engineering fundamentals, numerical methods, computational modeling, and technical validation. Experience reviewing complex technical work, chemical process simulations, computational models, or research outputs. Ability to evaluate mass and energy balances, thermodynamic assumptions, numerical accuracy, solver convergence, and computational reliability. Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for precise technical feedback and documentation.