Вакансии

Location: Kolomyya, Ukraine; Drohobych, Ukraine; Berehove, Ukraine; Uzhhorod, Ukraine; Ternopil, Ukraine; Mukachevo, Ukraine Are you someone who notices the little things others might miss? Do you have a natural curiosity about the AI industry and how machine learning actually works? If so, this could be the perfect opportunity for you Join us as a Data Annotator working on a cutting-edge 3D digital twin project. You will help map and reconstruct electrical distribution networks to help prevent power grid failures and manage critical infrastructure worldwide. What you’ll be doing: Reconstructing 3D power grid networks using point cloud (LiDAR) and map (GIS) data; Placing 3D objects (poles, lines, conductors) to match real-world physical layouts; Aligning original 2D map data with 3D models; Labeling high-resolution drone photos to identify grid components and detect structural defects (e.g., equipment damage or wear). Requirements: Strong spatial reasoning and the ability to easily navigate 3D environments; English B1 (ability to read instructions, watch training videos, and communicate with teammates); High attention to detail, problem-solving skills, and a willingness to learn from feedback; PC/laptop with an Intel i7-11800H (or equivalent/better CPU), dedicated GPU (NVIDIA T1200 or better; RTX 4060 recommended), and 16 GB RAM minimum (32 GB preferred). Will be a plus: Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data; Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; What we offer: Full-time schedule (9 hours/day, including a 1-hour paid lunch break), with a fixed shift of either 09:00-18:00 or 14:00-23:00 EEST; Standart business hours 09:00/10:00 – 18:00/19:00 Kyiv time; Fully remote work; Supportive management with no bureaucracy; Competitive compensation in USD; Opportunities for long-term professional growth. Who are we? Data is the most vital resource for next-generation spatial engineering and AI applications. Label Your Data has been providing high-quality, secure, and flexible data annotation services across various global industries since 2020. Grab your chance to join us on this innovative 3D digital twin project, and send us your CV in English highlighting your spatial and technical skills. Visit our website: https://labelyourdata.com/ *We celebrate diversity and are proud to be an equal opportunity employer.

Location: Vinnytsia, Ukraine; Lutsk, Ukraine; Lviv, Ukraine; Chernivtsi, Ukraine; Rivne, Ukraine; Ivano-Frankivsk, Ukraine Are you someone who notices the little things others might miss? Do you have a natural curiosity about the AI industry and how machine learning actually works? If so, this could be the perfect opportunity for you Join us as a Data Annotator working on a cutting-edge 3D digital twin project. You will help map and reconstruct electrical distribution networks to help prevent power grid failures and manage critical infrastructure worldwide. What you’ll be doing: Reconstructing 3D power grid networks using point cloud (LiDAR) and map (GIS) data; Placing 3D objects (poles, lines, conductors) to match real-world physical layouts; Aligning original 2D map data with 3D models; Labeling high-resolution drone photos to identify grid components and detect structural defects (e.g., equipment damage or wear). Requirements: Strong spatial reasoning and the ability to easily navigate 3D environments; English B1 (ability to read instructions, watch training videos, and communicate with teammates); High attention to detail, problem-solving skills, and a willingness to learn from feedback; PC/laptop with an Intel i7-11800H (or equivalent/better CPU), dedicated GPU (NVIDIA T1200 or better; RTX 4060 recommended), and 16 GB RAM minimum (32 GB preferred). Will be a plus: Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data; Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field. What we offer: Full-time schedule (9 hours/day, including a 1-hour paid lunch break), with a fixed shift of either 09:00-18:00 or 14:00-23:00 EEST; Fully remote work; Supportive management with no bureaucracy; Competitive compensation in USD; Opportunities for long-term professional growth. Who are we? Data is the most vital resource for next-generation spatial engineering and AI applications. Label Your Data has been providing high-quality, secure, and flexible data annotation services across various global industries since 2020. Grab your chance to join us on this innovative 3D digital twin project, and send us your CV in English highlighting your spatial and technical skills. Visit our website: https://labelyourdata.com/ *We celebrate diversity and are proud to be an equal opportunity employer.

Location: Europe ABOUT CANTINA: Cantina is a new social platform founded by Sean Parker with the most advanced AI character creator. Our bots are lifelike, social creatures that can interact wherever people are online—across voice, video, and text. Create yourself, imagine someone new, or choose from thousands of characters to share infinitely scalable, personalized content and seamless group chat. If you’re excited about how AI can shape creativity and social interaction, come help us build what’s next.   ABOUT THE ROLE: We’re looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end—from data specs through production inference. You’ll drive the model ↔ data ↔ eval flywheel for VC and adjacent tasks (controllable TTS, voice design and more), partnering closely with research, data, and infra to ship fast, reliable, and cost-aware models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. You will thrive in this role if you: - See research and engineering as two sides of the same coin and enjoy owning work end-to-end. - Are results-oriented, flexible, and willing to pick up whatever moves the needle. - Like collaborating closely with infra, data, and product to ship measurable improvements. - Enjoy designing experiments, listening tests, and metrics that correlate with user-perceived quality. - Eager to learn every-day, find and solve unique large-scale problems. WHAT YOU’LL DO: - Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) for large-scale speech models. - Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models. - Tool Development: Develop and improve dev tooling to enhance team productivity. - Full-Stack Contribution: Contribute to the entire stack, from low-level optimizations to high-level model design. - Data Ownership: Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies. - Rigorous Evaluation: Design automated objective/subjective evaluations—listening tests, SV/WER/ASR-based metrics, robustness & bias checks, and red-team studies. - Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback. - Safety & Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology.   WHAT YOU’LL BRING: - Exceptional research/development experience with large-scale audio models (>8B parameters, >500k hours of data). - Deep hands-on experience with diffusion and/or flow-matching transformers, including practical knowledge of samplers, schedules, conditioning mechanisms, and distillation. - Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders latent/tokenizer design, reconstruction and perceptual objectives, adversarial training. - Strong experience with multi-node, multi-GPU distributed training (FSDP/DeepSpeed or equivalent). - Strong software engineering skills with a proven track record of building complex systems. - Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production-quality code. - Shipped large-scale speech/audio or multimodal generative models to production. - Background in working with large-scale ML data, and the ability to iterate on data and triangulate quality using both subjective and objective signals. - Experience with voice cloning, speech control/steerability, or expressive speech generation. - Notable publications and/or open-source contributions in speech/audio/ML. COMPENSATION: When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.   BENEFITS FOR U.S.-BASED ROLES: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: Remote, Global ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE We are hiring a AI Platform Engineer to build the execution layer for Supabase's internal AI systems. Supabase is building an AI-native internal operating system: a common way of working across the company where AI carries a meaningful share of the operational load rather than sitting alongside it as an assistant. We are standing up a new central team to build those systems, enable the teams, and embed AI operations throughout the organization. You are the engineer on that team. The execution layer is yours. You will build the platform that actually runs agents: an event-triggered queue, a headless model-agnostic runtime, durable state so work survives a restart, a human review gate, atomic rollback, and full logging of every prompt, tool call and decision so any run can be reconstructed. You will build the evaluation layer that makes any of it trustworthy, because an agent that cannot be measured cannot be trusted with anything beyond reading. And you will build the agents themselves, across everything from executive reporting down to a layer of agents that watch the platform and improve it. This is a governance-heavy environment by design, and that is the interesting part of the problem. Agents are risk-tiered from read-only internal data through to external-facing output, with review depth, evaluation requirements and human approval scaling by tier. Some capabilities are permanently off limits: an agent may read and report, it may carry a human-authored update into a system of record once a human consents, and it may initiate contact within a strict budget, but it may never autonomously write a commitment (an owner, a due date, a status) into a shared work system. Your job is to make that structurally impossible rather than merely forbidden. You will be the only engineer on this platform. You will close open architecture decisions yourself, own the infrastructure end to end, and instrument the system so it reports its own return. WHAT YOU'LL BE RESPONSIBLE FOR In this role, you'll: - Ship the agent platform to production. An event-triggered queue, a headless model-agnostic runtime (choosing the runtime is an open decision you will close), durable state that survives a failed run, a human review gate, atomic rollback, and complete run logging in the warehouse. - Own the evaluation layer, and switch on the gate that depends on it. Golden suites with behavioral assertions rather than intuition, judge criteria with a written rubric, safety cases that must pass on every run, and a CI gate that blocks a regression from merging. This is the precondition for every agent that does anything beyond read internal data. - Build and register the agent portfolio. Reporting, drafting, linting, triage and question-answering agents across the executive, team-lead and individual-contributor layers, plus a meta layer that observes the platform and improves it. - Enforce governance in code. Risk tiers the pipeline actually enforces, least-privilege credentials per agent, tool-permission gates, a decision audit log, and autonomy classes where the dangerous class has no code path rather than a warning label. Nothing runs without a registered owner, tier, tool grant and human gate. - Design how the system contacts people. A hard interruption budget per person, message bundling instead of a stream of pings, and a structure that gives something useful before it asks for anything. Adoption depends on this more than on any other single design choice. - Own the platform tooling. The compiler and validator, inventory integrity, and the paths that distribute context and capabilities into the repositories and chat surfaces where work happens. - Compute the operating measures from production data. A pipeline from raw system activity through to a computed maturity grade per team, defensible enough that a team can dispute the result and be answered with the query rather than an opinion. - Instrument the platform's own return. A ledger that logs the work each agent absorbs and computes the monthly figure, so the value of the system is a measurement rather than a claim. HOW YOU'LL THINK RECURSIVE THINKING You build the generator, not the artifact. When you need thirty agents, you do not write thirty agents; you build the inventory, the compiler and the distribution path that makes the thirty-first cost an afternoon, then a meta layer whose job is to watch the platform, find its drift and file the fix. The evaluation layer is the same move applied to trust. You are not checking whether one agent is correct today. You are building the machine that decides whether every future agent is allowed to ship, which means the suite has to be right in a way the agent does not, and the thing that grades has to be graded too. INVERSION THINKING You start from the failure and work backward to the design. The rule is that an agent may never autonomously write a commitment into a shared work system. The weak implementation is an instruction in a prompt. The strong one is that the credential in the agent's tool grant physically cannot set an owner, a due date or a status, so no amount of clever input, prompt injection or model error produces the forbidden write. You reach for the second one first. Same for evaluation. Before writing a suite you enumerate how the agent can be wrong: an update that invents progress that did not happen, one that quotes a private channel into a public digest, one that is accurate and reads as an accusation, one that credits the wrong person. Then the suite is that list, each case caught before the agent ships rather than after it embarrasses someone. AI-NATIVE EXECUTION You use agentic tools on real work, in files and repositories, with the same rigor you apply to anything else you ship. You have a setup of your own and can describe it mechanically: what triggers it, what it is allowed to touch, where the human approves, what it logs, and how you found out the one time it went wrong. That experience is this job, generalized. You are building for async engineers across 40+ countries who will judge the platform by whether it saves them an hour or costs them one, so you are your own first user and your own harshest reviewer. YOU MIGHT BE A GOOD FIT IF YOU MUST HAVE - Have shipped production LLM agent systems that other people depended on. Not demos, not internal showcases. Systems with operational history, real users and at least one incident you can talk through. Prompt engineering on its own does not clear this bar. - Design evaluations, not spot checks. You build golden sets, write behavioral assertions, define judge rubrics, set pass thresholds and gate CI on the result. You can explain why "we reviewed a bunch of outputs and they looked good" is not evaluation. - Have done deep API work against the systems work actually lives in, and have authored MCP servers. You know the specific failure modes of those APIs, not just that they exist. - Own infrastructure end to end in Python on GCP, with a cloud warehouse and infrastructure as code. You provision, deploy, monitor and roll back your own systems, and you close architecture decisions rather than routing them onward. - Have taste about how software contacts humans. You treat every notification as spending a limited amount of trust. STRONG SIGNAL - Public work in this space. An open-source agent framework, an MCP server, an evaluation harness, or writing on agent reliability that other practitioners cite. - LLM observability and cost instrumentation. Tracing agent runs, attributing spend per run, and building the queries that turn raw logs into a report someone acts on. - You have built an internal platform that non-engineers adopted voluntarily, and can describe what you changed after watching them use it. WHAT SUCCESS LOOKS LIKE - The platform is boring. Agents run on a schedule and on events, state survives restarts, failed runs roll back cleanly, and every run can be reconstructed from its log. - Nothing ships unevaluated. Every registered agent has a real suite with safety cases, the gate blocks regressions, and when someone challenges an output the answer is a test case rather than an argument. - The dangerous action is impossible, not discouraged. An audit of any agent's credentials shows it cannot perform the writes it is not allowed to perform, and the audit log makes every consequential decision traceable. - Teams pull the platform instead of being pushed. Agents get adopted because the reports are useful and the contact is rare and well-timed, and each team ends up with at least one workflow that runs automatically. - The platform reports its own value. The work absorbed is measured and published, so the case for expanding it is made with data rather than enthusiasm. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Location: Remote Workplace: remote At Offchain, we aren’t just building products: we’re leading a movement.    As pioneers in blockchain scalability and security, we're at the forefront of transforming how the world interacts with decentralized applications. We're laying the foundation that will define the next generation of digital commerce, governance, and human interaction. This involves tackling real-world challenges that come with scaling blockchain technology, without compromising on its core principles: decentralization, security and transparency.    At the center of this vision is our people. Our team is made up of thinkers and doers that embrace new challenges and seek solutions that push existing boundaries. If you’re energized by solving unprecedented problems, and believe in the role that decentralized systems will play in creating a more equitable digital future, then we want to hear from you.    Why Offchain?   Offchain is setting the pace for the entire Ethereum ecosystem. We built the Arbitrum stack that powers Arbitrum One, the most widely adopted Ethereum scaling solution that exists today.   Arbitrum’s ecosystem is undergoing tremendous growth with hundreds of projects and dApps on Arbitrum One today. Over 100 different teams have used Offchain technology to build their own Arbitrum chains. Major players in the space, Robinhood, BlackRock, Ethena Labs, Securitize, Aave, and Apechain are all using the Arbitrum stack.   Arbitrum’s thriving ecosystem wouldn’t exist without our advanced technology stack. Arbitrum, Prysm, ZeroDev. These aren’t just product names. These are tools that are actively reshaping what's possible on Ethereum and advancing its core infrastructure.   To top it all off? We’re backed by $124 million in funding. We’ve demonstrated consistent execution with billions in secured value, thousands of supported projects, and infrastructure processing millions of transactions seamlessly. The Role: The Developer Platform team builds KMS, the key-management and signing service behind ZeroDev's embedded, non-custodial wallets. These are smart-account / account-abstraction wallets that developers integrate directly into their applications. End users retain control of their keys, while KMS security orchestrates wallet creation, authentication and signing on top of a third-party signing provider. You'll own production Go services and the cryptographic recovery and trust-model systems around them, working in a small, high-ownership team. This is security-critical infrastructure with a high review bar and external security audits. You should already be comfortable with applied-cryptography fundamentals such as public-key cryptography, signatures and key management. You don’t need to be a cryptographer or have prior experience with areas like MPC or TEEs, but you should be able to reason about cryptographic systems and their security implications. As the platform evolves, you'll also help expand it beyond interactive consumer wallets toward programmatic and automated signing, and programmable transaction policies. What you'll work on: Backend services: build and operate Go services that power wallet creation, authentication, and signing at scale Key recovery and the committee trust model: distributed key generation and secret sharing that keep the service non-custodial, with recovery authority split across independent committees so no single party holds a user's key Trusted Execution Environments: reconstructing and operating on key material under hardware isolation and remote attestation Authentication and signing-provider integration: the user-facing auth methods that gate signing (passkeys / WebAuthn, OAuth, OTP, sessions, 2FA), and integrating with a third-party signing provider (authorization and policy flows, scoped credentials, quorum / consensus approvals) Security review and hardening: writing design docs and decision records, working directly with external security auditors, and turning a high review bar into shipped code Production operations on Kubernetes: observability and alerting, secrets and certificate management, on-call, and the compliance controls the domain requires (sanctions screening, PII-safe handling) Who you are: Strong backend engineer who has shipped and operated production services in Go (or an adjacent systems language and is eager to go deep in Go) Security-first by default: You naturally think about threat models, blast radius and key custody, and write code that holds up to security-critical review Comfortable with applied-cryptography: You understand fundamentals such as public-key cryptography, signatures and key management, and can reason about how they apply to production systems. You don't need to be a cryptographer! Solid on distributed systems and API design: You’re comfortable reasoning about idempotency, failure modes and clean service boundaries Operationally experienced: You’ve worked with production infrastructure and are comfortable with Kubernetes, observability and incident response Clear written communicator: You can explain technical decisions through design docs and decision records, and work effectively in a collaborative, review-heavy environment. Nice-to-have You don't need to have worked with all of these. Experience in one or more would be valuable. Trusted Execution Environments (TEE) such as AWS Nitro Enclaves, Intel SGX / TDX or similar Threshold cryptography / MPC, including DKG, FROST or other threshold signatures, verifiable secret sharing or resharing Account abstraction, including ERC-4337, EIP-7702, smart accounts or embedded / non-custodial wallets Custody or signing infrastructure such as Turnkey or Fireblocks, either as an integrator or builder HSMs, YubiKey / PIV or secure-element integrations Third-party security audits and driving remediation through to completion Authentication technologies such as WebAuthn / passkeys and OAuth / OIDC, or experience with the Go crypto ecosystem Perks: Remote-first global workforce + NY office Professional reimbursement program (facilitates industry conference attendance, certifications, and more) Medical, dental & vision coverage (US + some other countries) 401k retirement plan + company match (US only) Wellness stipend Home office set up / ergonomic equipment program Attention Offchain Job Seekers:   This role cannot be performed in California, or Colorado.   Please be advised that there has been a rise in fraudulent recruiter activities, particularly within the Web3 space. If you would like to confirm whether someone is an Offchain employee or the legitimacy of an offer you received, please email jobs@offchainlabs.com   At Offchain, we are committed to building a welcoming and supportive workplace for all employees, regardless of their background or identity. We strive to create an environment where everyone feels valued and has an equal opportunity to succeed and thrive. We encourage candidates from all walks of life to apply and join our team.

Location: San Francisco, CA; US - Houston, TX (Remote) 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 As a Solutions Architect at Niantic Spatial, you’ll own technical solutioning from early customer discovery through commercial structuring and delivery. This role serves as the primary technical partner to Business Development, Sales, and strategic customers. We welcome candidates from backgrounds in Solutions Engineering, Customer Engineering, Technical Consulting, Solution Architecture, or technical pre-sales roles. As the primary technical counterpart for strategic commercial customers, you’ll lead discovery and align development to reusable, platform-aligned capabilities rather than one-off builds — translating operational needs into architectures that integrate cleanly into existing enterprise systems, field workflows, and robotic platforms. You’ll partner closely with Product Management so customer requirements shape the roadmap, and you’ll be central to developing, closing, and implementing new business across priority verticals — with a focus on Energy and Industrial — leveraging Niantic Spatial solutions such as Intelligent Field Operations, Reconstruction, Semantics, and Robotics. What You’ll Do Customer architecture & technical leadership - Own the technical relationship and technical success for assigned commercial and strategic accounts from discovery through implementation, with priority focus on Energy customers leveraging Intelligent Field Operations and Semantics. - Design end-to-end solution architectures (logical and physical) covering deployment, scaling, reliability, safety, and security across cloud, edge, and device environments. - Lead technical workshops to capture operational objectives, requirements, and success criteria, and translate them into implementation-ready designs tailored to field environments. Solution development & commercial proposal support - Provide technical inputs to customer proposals, pilots, statements of work (SOWs), and commercial agreements. - Lead technical solution documentation — architecture diagrams, integration approaches, deployment models, security considerations, and implementation plans. - Partner with Sales/BD on technical differentiators, value narratives, demonstrations, and scoping assumptions aligned to customer ROI and operational impact. Integration into enterprise & operational ecosystems - Ensure solutions integrate into customer environments — identity systems, data platforms, GIS/geo services, robotics stacks, enterprise integration patterns, observability, and device constraints. - Define integration patterns, APIs, and data flows across cloud, edge, and on-device systems; document operational runbooks and deployment/upgrade strategies suited to distributed field operations. Product feedback loop - Communicate customer needs, gaps, and technical requirements to Product Management and Engineering, influencing roadmap and prioritization with structured feedback from engagements, pilots, and deployments. - Provide structured input on emerging use cases across Intelligent Field Operations, Semantics, and Robotics. Delivery partnership - Collaborate with delivery teams and partners to ensure architectures are implemented as designed; support escalations, performance optimization, field validation, and post-launch adoption. - Support pilots and early deployments, ensuring measurable operational outcomes and scalable production transitions. - Maintain a set of repeatable demos for commercial prospects; use demo feedback to inform proposals and the product roadmap. What You’ll Bring - 8+ years in Solutions Architecture, Solutions Engineering, Customer Engineering or Systems Engineering, or related customer-facing technical roles supporting enterprise or industrial customers. - Demonstrated experience developing solution architectures and contributing to commercial proposals, pilots, or customer-facing technical documentation. - Strong architecture fundamentals across cloud and hybrid deployments, edge computing, networking, identity, security controls, and operational monitoring; enterprise integration (APIs, data pipelines, event-driven systems); and edge/device-constrained, distributed systems operating in real-world field conditions. - Experience supporting customers in at least one of: Intelligent Field Operations (utilities, energy, telecom, logistics, asset inspection, industrial automation); robotics platforms (mobile robots, drones, autonomy stacks, perception/localization); or geospatial, mapping/GIS, spatial computing, or AI-driven perception systems. - Ability to translate operational needs into implementable architectures and explain tradeoffs to both technical and non-technical stakeholders. - Excellent written communication, with the ability to produce high-quality technical documentation and customer-facing materials. Nice to Have - Experience selling into Energy verticals, and Oil & Gas specifically. - Experience with robotics software stacks (e.g., ROS/ROS2), autonomy systems, SLAM/localization, or sensor fusion. - Experience deploying AI/ML or perception systems in real-world operational environments. - Familiarity with safety, reliability, and operational constraints in industrial or field-based systems. - Prior experience partnering with Product Management to turn customer requirements into roadmap outcomes. Compensation & Benefits $171,000 - $215,000 · annual bonus · equity · comprehensive benefits Location & Work Model San Francisco Bay Area or Houston, TX (remote). If in San Francisco: Hybrid — at least 3 days per week in office. 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.

Location: Philippines, Remote; Argentina, Remote; LATAM, Remote; APAC, Remote Workplace: Remote ABOUT TENKI We started Tenki on the belief that compute is the new digital oil. As global demand for compute power accelerates, scalable and tradable compute is set to become one of the most valuable markets of our lifetime. Our goal is to become the leaders in harnessing, refining, and trading compute-unlocking a new asset class for the world’s most important digital resource. Tenki connects producers of compute with a growing universe of consumers. Producers get transparent pricing, predictable settlement, and access to global demand. Consumers get simple, developer-friendly access to high-quality compute at competitive prices. We’re currently building the consumer side, starting with GitHub Actions, enabling developers to offload workflows directly through Tenki. Soon, we’ll expand to a broad suite of cloud services like Virtual Machines, Databases, AI Agents, and more. As we expand, our focus will broaden beyond consumers to include the supply side, enabling producers to offer compute through Tenki and later the development of financial instruments that support a more efficient and tradable compute market. ABOUT THE ROLE We are looking for a Golang Engineer to join a small but talent dense team building the future of compute markets. Although the role is remote, we need team members who can reliably work within our core time zones in LATAM (GMT-3) or the Philippines (GMT+8), and you should be fully comfortable communicating in English across our globally distributed team. This Position will report to the Tenki Engineer Manager. In this role, you’ll help build the core infrastructure that powers Tenki’s. You will: - Architect, maintain, and evolve our core gRPC API services, based on ConnectRPC - Design and operate a private, programmable microservices fabric that securely connects our microservices across the platform - Manage identity services on top of the Ory stack: Kratos, Keto, and Hydra - Develop DDoS mitigation strategies - anticipating and countering adversaries. - Build high-performance Golang gRPC services from the ground up, built to scale to millions of users - and eventually billions. - Define and implement infrastructure following immutable principles, enabling full tear-down, failover, and rapid reconstruction. - Drive ideas from concept to reality by writing clear Engineering Requirement Documents and translating them into actionable plans and measurable outcomes. - Collaborate with our Applications (TypeScript) and Platform teams to expose robust, well-designed APIs for internal and future external consumers. ABOUT YOU - You are a proficient Golang engineer: You have deep experience building high-performance, concurrent applications and know how to squeeze performance out of the language when scaling to millions of users. - You live and breathe APIs: You have a strong track record of architecting and maintaining gRPC services (bonus points for ConnectRPC) and creating robust, documented contracts for internal and external consumers. - You understand Identity & Auth: You have implemented or managed identity services (Ory stack: Kratos, Keto, Hydra, or similar OIDC/OAuth2 providers) and understand the complexities of securing user data. - You have a "Systems" mindset: You aren’t just an application developer; you understand the underlying overlay networking (e.g., WireGuard, service mesh) that connects microservices securely. - You build for resilience and security: You have experience anticipating adversarial behavior (DDoS) and implementing mitigation strategies, perhaps leveraging eBPF or traffic shaping techniques. - You practice Immutable Infrastructure: You design systems where servers are cattle, not pets - enabling full tear-down, failover, and rapid reconstruction without manual intervention. - You define the standard: You don't just write code; you drive the engineering process by writing clear Engineering Requirement Documents and translating abstract concepts into actionable technical plans. - You implement with care: You build the monitors, define the error boundaries, and document operational expectations so that the platform remains maintainable by others long after you’ve pushed the code. - You thrive in ambiguity: You can set direction in an early-stage environment where priorities shift and clarity must be created, not awaited. - You bring grit and ownership: You dive deep into problems, ship pragmatic solutions, scale them as demand grows, and replace them when the time comes. We are building a startup within a startup. Tenki was born within Luxor http://www.luxor.tech as we expand our vision from mining compute to generalized compute. Learn more about how we work and our principles here https://www.notion.so/Luxor-Culture-ed37647662cd4060834afb9db7f543a1?pvs=21. At Tenki we believe that meaningful contributions can be made by anyone. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Tenki welcomes all! Tenki does not accept unsolicited headhunter and agency resumes. Tenki will not pay any third-party agency or company that does not have a signed agreement with Tenki. HOW WE USE AI IN OUR HIRING PROCESS We use AI tools to support certain parts of our hiring process, and we believe in being transparent about how they’re used. During your application, AI may assist in reviewing CVs, qualifications, and assignments by providing additional insights, but it does not make decisions, every application is evaluated at each step by a member of our hiring team. We also use AI to transcribe interviews so our team can stay focused on the conversation rather than note-taking. Any voice recordings are automatically deleted within 15 days. In addition, AI helps us keep candidates informed about their application status and helps us understand how our process is working so we can improve it over time. In all cases, AI is used to support efficiency and consistency, not to replace human judgment. If you have any questions about how we use these tools or your data, or if you would prefer to opt out of any of these features, please include them in the dedicated section of the application form, and we’ll follow up accordingly.

Location: Hong Kong, Hong Kong SAR Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity You will join our Data & Analytics team, which owns two core data domains end to end: • Public market data — trades, quotes, funding, and full order-book data continuously captured from global crypto exchanges at petabyte scale. • Proprietary trading data — orders, fills, positions, balances, and settlement activity streamed from internal desks and systems. We are one team rather than separate engineering and analytics functions. The same people build pipelines, model data, validate its correctness, and answer the business questions it supports. You will see data problems through end to end: from the exchange connection or internal source through to the analysis produced from it. This is an exciting time to join. We are rebuilding the platform on ClickHouse, Apache Iceberg, and Kafka while continuing to support live trading. The work combines substantial platform design with hands-on ownership of business-critical data. What You’ll Be Doing • Build and operate pipelines that bring market and trading data into our platform, including ingestion, parsing, normalization, validation, and storage. • Build and extend Python- and SQL-based datasets and data models used by trading desks, quants, research, and analytics teams. • Own data correctness through source reconciliation, data-quality and completeness checks, gap and duplicate detection, backfills, and replays. • Investigate discrepancies end to end. Trace unexpected numbers through the pipeline to the source and fix root causes rather than symptoms. • Onboard new exchanges, venues, products, and internal data sources, addressing real-world external-feed behaviour including authentication, rate limits, disconnects, missing history, and schema changes. • Support data users through query support, data access, APIs, and client libraries. • Operate what you build, including monitoring, alerting, and incident response for owned pipelines and datasets. • Contribute to the migration toward ClickHouse, Iceberg, Kafka, and Kubernetes by running new and legacy paths in parallel, reconciling results, and cutting over safely. • Use AI coding assistants and LLM tooling to improve development, debugging, and data investigation, while applying sound judgement and independently validating outputs. • Depending on team needs and your strengths, develop deeper expertise in either real-time platform and pipeline engineering or proprietary trading-data datasets and analysis. Both are core to the team. What We Look For In You • Bachelor’s degree or above in Computer Science, Engineering, or a related quantitative field. • 3–5 years of hands-on experience in data engineering, software engineering, or analytics engineering. • Strong production-quality programming skills in Java, Python, or both. • Sound data-modelling judgement. You can design schemas that scale with evolving data and use cases, including keys, granularity, partitioning, and schema evolution. • Ability to reason about query behaviour and performance over large datasets. • Demonstrated production ownership. You have designed, delivered, and operated a pipeline, service, or dataset that other teams depend on, including its reliability, monitoring, and failure modes. • Rigour in data correctness. You validate outputs before they reach users, cross-check against independent sources where possible, and treat silent data errors as serious defects. • Structured problem-solving under uncertainty. You can decompose ambiguous data discrepancies, form and test hypotheses, and reach defensible conclusions while clearly stating assumptions and outstanding verification needs. • Strong initiative and persistence. You identify gaps, act without waiting for direction, work through difficult problems, and get up to speed quickly on unfamiliar systems and domains. • Strong communication skills in both Chinese and English. Nice to Have • Experience in crypto, market data, trading systems, or trading operations. • Strong Java systems-engineering capability, including JVM and concurrency fundamentals, profiling, performance tuning, and reliable high-throughput services. • Strong Python data-engineering capability, including pandas, Polars, PyArrow, or Spark; experience with vectorisation, memory behaviour, and processing datasets larger than memory. • Experience delivering tested, packaged Python tooling that other teams depend on. • Depth in trading-data analysis, such as reconstructing positions from fills, balances from transfers, or PnL across settlement or expiry boundaries. • Experience reconciling derived trading data against authoritative sources and resolving discrepancies between systems. • Experience with real-time streaming pipelines, ideally Kafka, including ordering, gap detection, checkpoints, restart recovery, and replay. • Hands-on experience with time-series or analytical databases, including partitioning, retention, and query-performance tuning at scale. • Exposure to Apache Iceberg, Parquet, Spark, gRPC, Kubernetes, or cloud data infrastructure. • Experience building connectors to external REST or WebSocket APIs. Working Model • Hong Kong, onsite (in-office). Perks & Benefits • Competitive total compensation package. • Learning and development programs and education subsidy for employees’ growth and development. • Various team-building programs and company events. • Wellness and meal allowances. • Comprehensive healthcare schemes for employees and dependents. • More that we would love to tell you about during the process. Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .