Вакансии

-Разрабатывать computer vision и machine learning решения для архитектурных чертежей, технических документов, CAD и BIM-данных. -Строить пайплайны, объединяющие растровые изображения, векторную геометрию, структурированные инженерные данные, OCR и ML-модели.

Crusoe is looking for a Senior Automation Engineer Compute to build deployment testing and orchestration automation for GPU clusters.

Location: United States; Canada; United Kingdom; Australia; New Zealand 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 a Chemistry and Computational Research Specialistwith doctoral-level expertise to contribute to projects focused on training and benchmarking next-generation AI systems. You will design and evaluate chemistry problems, validate scientific reasoning, analyze experimental and computational data, and assess AI-generated research outputs for accuracy and reproducibility. Depending on your specialization, you may work with reaction mechanisms, synthesis planning, spectroscopy, molecular simulations, electronic structure calculations, or cheminformatics. The ideal candidate combines deep chemistry knowledge with hands-on laboratory or computational research experience, strong quantitative reasoning, and the ability to communicate complex scientific findings clearly. Prior AI experience is not required. SENIORITY: PhD-Level Research Specialist LANGUAGE: Professional English — C1 or higher TARGET LOCATIONS: US and Canada are our top priorities, followed by the UK, Australia, and NZ. We’re open to candidates worldwide as long as they meet the C1 English level. Key Responsibilities Design, evaluate, and critique chemistry problems, computational workflows, and scientific reasoning chains for AI benchmarking initiatives. Assess chemical reasoning involving reaction mechanisms, synthesis planning, retrosynthesis, spectroscopy, and molecular modeling. Evaluate experimental protocols, simulation parameters, and scientific software configurations for accuracy and reproducibility. Analyze chemical, spectroscopic, experimental, and simulation data to identify errors, limitations, and opportunities for improvement. Apply domain expertise to guide the development and validation of chemistry-focused AI models and scientific tools. Review AI-generated scientific outputs for correctness, completeness, methodological soundness, and consistency with established chemical principles. Document research methods, findings, limitations, and best practices to support reproducibility and knowledge transfer. Communicate complex scientific concepts clearly to technical and non-technical collaborators. Areas of Expertise Candidates should have deep expertise in at least one of the following areas: Organic synthesis and reaction mechanisms Inorganic and organometallic chemistry Physical and theoretical chemistry Analytical chemistry and spectroscopy Computational chemistry and molecular dynamics Cheminformatics and drug discovery Materials science and polymer chemistry Requirements PhD in Chemistry, Computational Chemistry, Chemical Biology, Materials Science, or a closely related field. Hands-on research experience in a laboratory setting for experimental chemistry specializations, or extensive simulation-based research experience for computational specializations. Deep expertise in at least one of the listed chemistry or computational research areas. Professional written and spoken English proficiency at C1 level or higher. Proficiency in Python and/or relevant scientific software used in your specialization. Familiarity with applicable tools such as Gaussian, ORCA, Psi4, GROMACS, LAMMPS, or RDKit. Excellent quantitative, analytical, and scientific reasoning skills. Strong written and verbal communication skills, including the ability to document and explain technical concepts. Demonstrated ability to solve complex chemistry problems rigorously and evaluate scientific results critically.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Strategic Finance Lead to provide finance leadership for our network infrastructure. In this role, you will be a key partner to our infrastructure teams, providing financial expertise and guidance to optimize our networking investments and drive strategic decision-making. In this role, you’ll develop deep expertise in the economics of networks, from the monthly cost of connectivity and colocation to the long-range planning of fiber and data center builds. You’ll build financial models that inform Anthropic’s investment decisions, own planning and forecasting processes for major cost centers, and translate complex technical dynamics into clear financial narratives for leadership. This is a high-impact role for someone who thrives at the intersection of finance and technology, and who is energized by building frameworks from scratch in a fast-moving environment. Key responsibilities Finance lead for network capex and opex, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance Build and maintain detailed bottoms-up data-driven financial models for network infrastructure, including long-range forecasts, cost driver analyses, and investment scenario modeling Develop expertise in connectivity, colocation, and equipment contracts, pricing structures, and cost drivers, and surface optimization opportunities Subject matter expert on Anthropic’s network buildout, source of truth and plan of record Support the implementation and management of financial planning and procurement tools, ensuring our models and processes scale with the organization Analyze the economics of build, lease, and service options for network capacity, including ROI across dimensions like term, route, and ownership, and distill into actionable framework for capacity planning and deployment Partner closely with network engineering teams to understand how capacity, lead times, and site readiness scale, and translate those technical dynamics into financial frameworks Minimum qualifications Exceptional analytical skills with an ability to synthesize data into compelling insights and develop complex financial operating models Extraordinary problem-solving and critical thinking abilities to come up with new frameworks for assessing profitability and capital efficiency in a rapidly evolving industry Attention to detail and patience for getting to the source of truth on complex and interconnected underlying financial and legal frameworks Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences Proven track record of partnering with technical teams to drive financial optimization initiatives Excitement about working collaboratively in a fast-paced, dynamic environment and adapt well to change Possess a bias towards action, strong work ethic, and have experience driving operational outcomes under tight timelines Strong relationship building, business judgment, process management, and communication skills Are passionate about Anthropic's mission to build safe, transformative AI systems Are passionate about the effective integration of AI tools to streamline manual finance workflows Background in network, telecom, or large-scale computing infrastructure, including data centers, cloud service providers, etc Preferred qualifications 7+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking, preferably with telecom, datacenter, or network infrastructure experience 3+ years of experience specifically in network infrastructure financial management Experience working directly with major carriers, colocation providers, or hardware vendors MBA or other advanced degree in finance, economics, or business Expertise in connectivity, equipment, or lease economics, contract structures, and pricing models Experience with capital project or long-lead equipment economics Proficiency with financial modeling tools and languages (SQL, Python, Excel) Experience building a computer, homelab, or home network from scratch The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $325,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Agile Robots SE is looking for a Senior Machine Learning Engineer Computer Vision for Robotics to develop and deploy real-time visual servoing models for robot manipulation.

Location: London Workplace: Hybrid ABOUT NIANTIC SPATIAL AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. ABOUT THE ROLE You'll help build the geometric foundation of the next-generation world map — joining our World Map Research Engineering team (Geospatial Alignment) as a Research Engineer or Senior Research Engineer. This is an end-to-end applied research role that spans from strong engineering and data-systems work to R&D in 3D deep learning, transformers, and foundation models. You'll develop new algorithms, produce the research data and evaluation assets needed to advance them, and engineer the resulting capabilities into dependable production systems. The World Map team works with heterogeneous captures from phones and handheld devices, aerial imagery, LiDAR, and 360 cameras, as well as external geographic and elevation data. The central challenge is to harmonize these data sources, quantify uncertainty, and maintain consistency as the map evolves. You'll work at the intersection of cutting-edge research and scalable engineering — developing new approaches to geospatial registration, correspondence, and geometric optimization, then productionizing these technologies to directly improve Niantic Spatial's world model. What You'll Do - Geospatial Registration — Develop and advance algorithms for world-scale georeferencing and registration across imagery, 3D reconstructions, point clouds, and geographic reference data. - 3D Geometry & Correspondence — Build and improve methods spanning multi-view geometry, SfM, SLAM, feature matching, learned correspondence, bundle adjustment, point-cloud registration, and ICP. - Data & Evaluation — Create the data and evaluation flywheel for world-scale mapping — design and maintain large-scale datasets, pipelines, benchmarks, and evaluation methodologies that expose hard failure modes, accelerate research iteration, and support production. - Learning-Based 3D Reasoning — Explore and develop learning-based approaches for geospatial understanding, combining transformers and 3D foundation models with geometric priors and uncertainty modeling. - Production Robustness — Design robust solutions for challenging real-world conditions: sparse or noisy GPS, changing appearance, inconsistent reconstruction quality, large geographic extents, and imperfect reference maps. - Cross-Functional Collaboration — Partner with leading researchers in visual localization, 3D computer vision, and mapping — as well as engineering and product teams — to identify high-impact problems and turn research breakthroughs into end-to-end production systems. - Research Communication — Share results clearly through technical writing, design reviews, and internal presentations; contribute to publications and open research where appropriate. WHAT YOU'LL BRING - Bachelor's or Master's degree in Computer Science, Robotics, Machine Learning, Photogrammetry, or a closely related field — or equivalent research or industry experience. - Strong grounding in 3D computer vision, machine learning, robotics, photogrammetry, or a closely related area. - Demonstrated experience with 3D geometry and several relevant areas — multi-view reconstruction, SfM, SLAM, camera pose estimation, point-cloud registration, image-based localization, georeferencing, or sensor fusion. - The ability to formulate ambiguous real-world problems, choose the right mathematical or learning-based tools, and evaluate solutions rigorously. - Strong Python skills and experience with modern ML and scientific-computing libraries (PyTorch, NumPy, SciPy). - Strong software engineering skills — you can turn research prototypes into reliable, scalable, and maintainable systems. - A track record of taking an algorithm from research idea and experimental prototype through evaluation, benchmarking, and deployment on real-world data. - Clear written and verbal communication; able to collaborate effectively across research and engineering disciplines. NICE TO HAVE - PhD in computer vision, robotics, machine learning, photogrammetry, geodesy, remote sensing, or a related field — not required, but valued. - A strong publication record or active involvement in the research community at venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, 3DV, ICRA, or RSS. - Experience with learning-based approaches for visual or 3D understanding — transformers, point transformers, foundation models, or methods combining learned representations with explicit geometric priors. - Experience with aerial or satellite imagery, GNSS/GPS, geodesy, mapping systems, or large-scale spatial data. - Evidence of technical leadership, mentorship, or successful cross-functional delivery. COMPENSATION & BENEFITS Base salary: Competitive market rate. Compensation also includes an annual bonus, equity, and a comprehensive benefits package. LOCATION & WORK MODEL This role is based in our London office, with three days per week in office. We welcome applications from candidates who require visa sponsorship. INCLUSIVE APPLICATION We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed — you may be exactly who we're looking for. EQUAL OPPORTUNITY Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. CANDIDATE PRIVACY I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Задачи: — Участие в профессиональных тренингах — Поддержка внеклассных мероприятий — Подготовка учеников к участию в региональных мероприятиях Требования: — Опыт работы в школе — Умение преподавать на казахском и русском языках

Lambda is looking for a Staff Product Manager Compute to define, launch, price, and improve cloud compute products.

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.

Location: Brazil; Argentina; Colombia; Chile; Peru; Uruguay 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.

Location: India; Australia; Japan; Singapore; Philippines; New Zealand 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.

Location: United States; Panama; Guatemala; Mexico; Costa Rica; Canada 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.

Location: San Francisco; New York City Workplace: Hybrid In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and a growing share of them meet us first on their phone. The Growth team owns the product loops that help people discover, adopt, and build lasting habits around our most important AI experiences — and on mobile that means owning everything from the App Store listing to the first task a user finishes to the moment they upgrade. As an Android growth engineer at Perplexity, you'll work across the full mobile funnel — install, activation, onboarding, push and lifecycle messaging, conversion, retention, and in-app purchase moments — for Perplexity, Comet, and Computer on Android. Engineers are responsible for end-to-end projects: rebuilding onboarding as a series of experiments, wiring in-app purchase and paywall surfaces to our billing systems, shipping notification experiences people actually keep enabled, and turning ASO and deep-link work into measurable adoption. Growth at Perplexity goes beyond incremental funnel optimization. The team sits close to the core product — we translate behavioral signals, model outputs, and fast experimentation into durable product surfaces used across consumer and enterprise workflows. You'll move fast, run many experiments in parallel, and own the outcome end-to-end, while respecting the constraints mobile brings: release cycles, store review, and version fragmentation. WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Design, build, and own growth surfaces across the mobile funnel — install, activation, onboarding, lifecycle, conversion, retention, and paid upgrade moments — on Android. - Lead experiments end-to-end, from hypothesis and instrumentation through implementation, analysis, and rollout, shipping many in parallel despite app release cadence. Build the flag-driven and server-driven patterns that let us test without waiting on a store release. - Own in-app purchase and paywall surfaces: billing integrations, subscription and credit purchase flows, entitlement correctness, and pricing and packaging experiments. - Build push and lifecycle notification experiences that earn their opt-in — permission prompts, targeting, timing, deep links back into the right task, and the instrumentation to prove they drive retention rather than churn. - Make cross-platform surfaces feel native. Partner with web and design engineers so onboarding, upsells, and in-task nudges are consistent across web, iOS, and Android - Partner with rest of Growth to optimize app store performance and attribution - Hill-climb on the metrics that matter: install-to-activation, D1/D7/D30 retention, notification opt-in and engagement, paid conversion, and habit formation, instrumented with clean data and trustworthy experiment readouts. - Partner closely with Product, Design, Data Science, Monetization, Marketing, and the core Mobile team to translate behavioral signals into durable product surfaces. QUALIFICATIONS - 3+ years of professional mobile engineering experience shipping consumer apps at meaningful scale on Android. - Strong native skills — Kotlin/Jetpack Compose — and the willingness to flex into other parts of the stack to unblock yourself and others. - Experience owning a full release cycle: build and release tooling, phased rollouts, store review, crash and regression monitoring, and rolling back safely. - Strong execution: you ship many experiments and product improvements in parallel and drive them to a clear outcome. - Familiarity with A/B testing and experimentation platforms (Eppo, Statsig, Optimizely, or in-house equivalents) especially inside a versioned app. - Comfort data-informed decision-making — you can pull, segment, and interpret your own funnel data. - Strong product judgment; you translate user behavior and growth opportunities into simple, effective technical solutions. - Self-motivated with strong ownership instincts; you propose experiments, ship features ahead of schedule, and drive improvements without asking for permission. - Genuine interest and adoption of AI products and willingness to learn quickly. NICE TO HAVE - Direct experience on a growth or experimentation-heavy team - Deep experience with in-app payments - Experience with mobile attribution and measurement stacks (AppsFlyer, Adjust, Branch) and paid mobile acquisition. - ASO experience, including store listing experiments and localized metadata. - Comfort reaching into the backend or web stack to unblock yourself end-to-end. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and a growing share of them meet us first on their phone. The Growth team owns the product loops that help people discover, adopt, and build lasting habits around our most important AI experiences — and on mobile that means owning everything from the App Store listing to the first task a user finishes to the moment they upgrade. As a mobile growth engineer at Perplexity, you'll work across the full mobile funnel — install, activation, onboarding, push and lifecycle messaging, conversion, retention, and in-app purchase moments — for Perplexity, Comet, and Computer on iOS. Engineers are responsible for end-to-end projects: rebuilding onboarding as a series of experiments, wiring in-app purchase and paywall surfaces to our billing systems, shipping notification experiences people actually keep enabled, and turning ASO and deep-link work into measurable adoption. Growth at Perplexity goes beyond incremental funnel optimization. The team sits close to the core product — we translate behavioral signals, model outputs, and fast experimentation into durable product surfaces used across consumer and enterprise workflows. You'll move fast, run many experiments in parallel, and own the outcome end-to-end, while respecting the constraints mobile brings: release cycles, store review, and version fragmentation. WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution, and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Design, build, and own growth surfaces across the mobile funnel — install, activation, onboarding, lifecycle, conversion, retention, and paid upgrade moments — on iOS. - Lead experiments end-to-end, from hypothesis and instrumentation through implementation, analysis, and rollout, shipping many in parallel despite app release cadence. Build the flag-driven and server-driven patterns that let us test without waiting on a store release. - Own in-app purchase and paywall surfaces: billing integrations, subscription and credit purchase flows, entitlement correctness, and pricing and packaging experiments. - Build push and lifecycle notification experiences that earn their opt-in — permission prompts, targeting, timing, deep links back into the right task, and the instrumentation to prove they drive retention rather than churn. - Make cross-platform surfaces feel native. Partner with web and design engineers so onboarding, upsells, and in-task nudges are consistent across web, iOS, and Android - Partner with rest of Growth to optimize app store performance and attribution - Hill-climb on the metrics that matter: install-to-activation, D1/D7/D30 retention, notification opt-in and engagement, paid conversion, and habit formation, instrumented with clean data and trustworthy experiment readouts. - Partner closely with Product, Design, Data Science, Monetization, Marketing, and the core Mobile team to translate behavioral signals into durable product surfaces. QUALIFICATIONS - 3+ years of professional mobile engineering experience shipping consumer apps at meaningful scale on iOS. - Strong native skills (eg. Swift/SwiftUI/Objective-C) — and the willingness to flex into other parts of the stack to unblock yourself and others. - Experience owning a full release cycle: build and release tooling, phased rollouts, store review, crash and regression monitoring, and rolling back safely. - Strong execution: you ship many experiments and product improvements in parallel and drive them to a clear outcome. - Familiarity with A/B testing and experimentation platforms (Eppo, Statsig, Optimizely, or in-house equivalents) especially inside a versioned app. - Comfort data-informed decision-making — you can pull, segment, and interpret your own funnel data. - Strong product judgment; you translate user behavior and growth opportunities into simple, effective technical solutions. - Self-motivated with strong ownership instincts; you propose experiments, ship features ahead of schedule, and drive improvements without asking for permission. - Genuine interest and adoption of AI products and willingness to learn quickly. NICE TO HAVE - Direct experience on a growth or experimentation-heavy team - Deep experience with in-app payments - Experience with mobile attribution and measurement stacks (AppsFlyer, Adjust, Branch) and paid mobile acquisition. - ASO experience, including store listing experiments and localized metadata. - Comfort reaching into the backend or web stack to unblock yourself end-to-end. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Разрабатывать и исследовать ML-модели для генерации изображений и визуализации интерьерных/строительных решений на основе товаров Лемана ПРО. Проектировать и реализовывать end-to-end пайплайны для PoC: от сбора и подготовки данных до обучения, оценки и демонстрации результатов.

• 5+ лет опыта в Computer Vision и Deep Learning. • Глубокая экспертиза в Python и современных CV-фреймворках.

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.