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Location: Tiranë, Albania; Durrës, Albania; Elbasan, Albania; Shkodër, Albania; Vlorë, Albania; Korçë, Albania Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. 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 B2 (ability to read instructions, watch training videos, and communicate effectively); 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: Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data. 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: New York, United States Who We Are At OKX, we believe the future will be reshaped by crypto and blockchain technology. We operate a leading global crypto platform and build products and services designed to expand access to the digital-asset ecosystem. Across our global organization, we value ownership, sound judgment, collaboration, innovation, and the ability to operate effectively in a fast-moving and continuously evolving environment. Recruiting should insert the current approved OKX corporate “Who We Are” language when the position is posted. About the Team The Fraud Investigations Team (FIT) is a First Line of Defense function within OKX’s Risk organization responsible for identifying, assessing, investigating, and helping manage significant internal and external fraud risks affecting the company, its customers, personnel, and operations. FIT conducts and supports complex investigations involving digital assets, internal and external fraud, employee misconduct, insider threats, unauthorized access or misuse of information, vendor and third-party misconduct, account compromise, social engineering, collusion, conflicts of interest, and other significant fraud-related matters. The team works closely with Legal, HR, Information Security,Engineering, Physical Security, Compliance, Finance, Operations, and other functions across OKX. About the Opportunity We are looking for an experienced Senior Analyst, Blockchain Investigations & Fraud Intelligence to join FIT. This is first and foremost a blockchain investigations role requiring significant hands-on expertise tracing digital assets across complex blockchain ecosystems. The successful candidate must be capable of independently conducting sophisticated on-chain investigations, developing and testing attribution hypotheses, identifying relationships among wallets and entities, following assets through multiple chains and protocols, and translating highly technical blockchain activity into clear investigative findings. Blockchain analysis is a specialized investigative discipline. Accordingly, we are seeking someone who understands not only how to operate commercial tracing platforms, but also the underlying blockchain architecture, transactional mechanics, attribution methodologies, clustering techniques, tracing limitations, and evidentiary considerations necessary to reach reliable conclusions. The role extends beyond on-chain analysis. The Senior Analyst will combine blockchain intelligence with enterprise data, system logs, transactional records, open-source information, and other evidence to support complex fraud and insider-risk investigations. The position will also provide analytical support to the Global Physical Security Team (PST) on selected protective-intelligence and threat-assessment matters. The Senior Analyst will directly manage one Analyst and will be expected to serve as a subject-matter resource for blockchain investigations and analytical methodology across FIT. What You’ll Be Doing Blockchain Investigations & Digital-Asset Intelligence Lead and conduct complex blockchain investigations and transaction tracing across multiple wallets, counterparties, entities, blockchains, tokens, protocols, and digital-asset ecosystems. Trace the origin, movement, conversion, layering, consolidation, and ultimate disposition of digital assets , including activity spanning multiple intermediaries and blockchain environments. Conduct investigations using tools such as Chainalysis Reactor , TRM Labs, Elliptic, or comparable blockchain intelligence platforms , while understanding the methodologies and limitations underlying platform-generated attribution. Analyze activity involving centralized exchanges, self-hosted wallets, decentralized exchanges, cross-chain bridges, mixers, privacy-enhancing technologies, DeFi protocols, smart contracts, stablecoins, NFTs, OTC activity, gambling platforms, and other relevant ecosystems . Trace assets across multiple chains and cross-chain transactions , identifying continuity of funds where technically supportable and clearly documenting assumptions or limitations where definitive attribution is not possible. Analyze transaction graphs, address relationships, behavioral patterns, clusters, counterparties, timing, amounts, transaction sequencing, and other relevant blockchain indicators. Understand and appropriately apply wallet-clustering and attribution methodologies , including the limitations and potential for false attribution associated with particular heuristics. Independently evaluate blockchain intelligence rather than relying solely on automated labels, risk scores, or vendor-generated attribution. Corroborate on-chain findings, where appropriate, with internal account records, KYC / KYB information, transaction data, access information, open-source intelligence, legal-process returns, or other available evidence . Identify relationships among blockchain addresses, OKX accounts, external counterparties, individuals, organizations, vendors, affiliates, and other relevant entities. Reconstruct complex transaction flows and create clear fund-flow diagrams, transaction maps, timelines, and visualizations that allow investigators and nontechnical stakeholders to understand the movement of assets. Analyze blockchain activity associated with suspected fraud , theft, account takeover, social engineering, insider activity, collusion, payment diversion, asset misappropriation, or other misconduct . Identify new wallets, counterparties, entities, or transactional patterns that may generate additional investigative leads. Clearly document the methodology, assumptions, confidence level, and limitations associated with blockchain findings. Distinguish between confirmed attribution , vendor attribution, analytical inference, behavioral similarity, and an unverified investigative hypothesis . Avoid presenting blockchain proximity, exposure, clustering, or a commercial risk score alone as proof of ownership, control, intent, or misconduct. Maintain current knowledge of emerging blockchain technologies, protocols, tracing methodologies, obfuscation techniques, fraud typologies, and developments affecting blockchain attribution or investigations . Fraud Investigations & Investigative Intelligence Conduct and support investigations involving internal and external fraud , employee misconduct, insider threats, vendor and third-party misconduct, collusion, conflicts of interest, asset misappropriation, unauthorized access, credential misuse, and other significant fraud risks . Combine blockchain findings with off-chain evidence to develop a comprehensive investigative picture rather than treating blockchain activity in isolation . Develop investigative hypotheses and objectively test those hypotheses against available evidence, including information that supports, contradicts, or fails to establish the hypothesis. Conduct timeline reconstruction, link analysis, relationship mapping, pattern analysis, clustering, and comparative analysis across individuals, accounts, wallets, devices, systems, transactions, and entities. Support investigations involving account takeover, impersonation, social engineering, business-email compromise, payment diversion, affiliate misconduct, and trusted-party abuse , particularly where a digital-asset, employee, vendor, or enterprise nexus exists. Analyze vendor, affiliate, partner, and other third-party activity for indicators of billing irregularities, undisclosed relationships, conflicts of interest, unusual payments, control circumvention, or other potential misconduct. Support investigative interviews by developing transaction timelines, identifying inconsistencies or information gaps, organizing evidence, and identifying appropriate areas for follow-up. Enterprise Data & Insider-Risk Analytics Analyze appropriately authorized information including system and access logs, authentication records, audit trails, customer-account activity, KYC / KYB information, transaction records, payment information, case-management records, vendor information, and relevant security telemetry . Correlate blockchain activity with enterprise data to identify possible connections among wallets, accounts, employees, customers, vendors, devices, transactions, and other relevant entities . Support investigations involving suspected unauthorized access, information misuse or exfiltration, credential compromise, control circumvention, unauthorized disclosure, or abuse of privileged access. Identify anomalous behavior or access patterns that may warrant additional investigation. Develop repeatable analytical methodologies capable of processing and correlating information from disparate systems. Use appropriate scripting, database querying, data visualization, and analytical technologies to efficiently analyze large or complex datasets. Investigative Reporting & Evidence Prepare clear, concise, and well-supported blockchain investigation reports, investigative memoranda, executive summaries, transaction-flow diagrams, link charts, timelines, and other analytical products . Explain complex blockchain concepts and transaction activity in plain language suitable for investigators, senior management, Legal, regulators, or law enforcement , as appropriate. Clearly distinguish among allegations, investigative leads, known facts, third-party attribution , analytical judgments, assumptions, information gaps, and substantiated conclusions . Ensure analytical conclusions are proportionate to the evidence and do not imply greater certainty than the underlying blockchain or other data supports. Maintain sufficient documentation to allow significant blockchain findings to be reviewed, reproduced, and understood by another qualified analyst . Preserve and handle investigative records in accordance with applicable evidence-preservation, chain-of-custody, confidentiality, privacy, access-control, and need-to-know requirements . Support appropriately authorized law-enforcement, regulatory, litigation, or legal matters in coordination with the appropriate company functions. Protective Intelligence & Physical Security Support Provide analytical support to PST on selected matters involving threats or concerning activity directed toward employees, executives, offices, events, or other company interests. Conduct authorized open-source, link, timeline, blockchain, financial, or other analytical research where relevant to understanding the identity, relationships, capabilities, or activity associated with a potential threat. Assist in evaluating available information relating to credibility, corroboration, intent, capability, access or opportunity, targeting, escalation, timing, and other relevant indicators . Prepare objective analytical products identifying known facts, analytical judgments, material information gaps, uncertainties, and appropriate confidence levels. Support PST’s assessment while preserving PST’s responsibility for protective-security decisions and operational response . Leadership & Development Directly manage and develop one Junior Analyst, including work allocation, coaching, technical development, quality assurance, and review of analytical work product . Serve as a FIT subject-matter resource for blockchain investigations and on-chain analytical methodology . Review blockchain analysis for technical accuracy, appropriate methodology, corroboration, reasonable attribution, and evidentiary support. Train and mentor junior personnel in transaction tracing, blockchain intelligence platforms, analytical reasoning, documentation, and investigative methodology. Help establish consistent standards for blockchain investigations, attribution , documentation, quality assurance, and reporting . Participate in time-sensitive investigations affecting a global organization, including occasional work outside normal business hours when required. What We Look For In You 7+ years of relevant investigative or analytical experience , with meaningful professional experience specifically conducting cryptocurrency or blockchain investigations . Demonstrated hands-on expertise independently conducting complex blockchain tracing investigations , rather than solely reviewing blockchain alerts or commercial risk scores. Advanced proficiency with one or more blockchain intelligence platforms such as Chainalysis Reactor , TRM Labs, Elliptic, or comparable technology . Strong understanding of how blockchain intelligence platforms derive attribution, clustering, exposure, and risk information—and the limitations associated with those methodologies . Demonstrated understanding of blockchain fundamentals, including wallets and addresses, transactions, UTXO and account-based models, tokens, smart contracts, block explorers, transaction fees, confirmations, and blockchain-specific transactional structures . Strong understanding of digital-asset ecosystems including centralized exchanges, self-hosted wallets, DeFi , DEXs, stablecoins, cross-chain bridges, mixers, privacy-enhancing mechanisms, and other relevant technologies . Demonstrated ability to trace assets across multiple chains, protocols, and intermediaries and recognize when technical limitations prevent definitive continuity or attribution. Experience conducting transaction-graph analysis, wallet attribution , clustering, counterparty analysis, transaction-flow reconstruction, and investigative link analysis . Ability to critically assess blockchain attribution and distinguish among technical facts, commercial vendor intelligence, analytical inference, and unsupported assumptions . Experience integrating blockchain intelligence with off-chain evidence and enterprise information to develop investigative conclusions. Strong knowledge of fraud-investigation principles including corroboration, source evaluation, evidence preservation, timeline development, hypothesis testing, and documentation. Experience analyzing large or complex datasets and familiarity with tools such as SQL , advanced Excel, Python, Splunk, or comparable data-analysis technologies . Ability to clearly explain technically complex blockchain findings to audiences that may have little or no blockchain expertise. Strong investigative writing skills and demonstrated ability to produce accurate, concise, and defensible analytical products. Sound judgment and ability to work effectively where evidence is incomplete, conflicting, or evolving. Demonstrated discretion when handling sensitive employee, customer, investigative, security, or company information. Demonstrated experience mentoring, supervising, or reviewing the work of junior analysts or investigators. Nice to Haves Experience conducting blockchain investigations within a cryptocurrency exchange, blockchain analytics company, law-enforcement agency, regulatory organization, financial institution, intelligence function, or investigative consulting environment . Experience investigating digital-asset matters involving fraud proceeds, theft, account compromise, insider activity, social engineering, asset tracing, or complex cross-chain movement . Experience supporting asset recovery, law-enforcement referrals, subpoenas/legal process, civil litigation, regulatory inquiries, or other matters requiring defensible blockchain analysis . Experience investigating insider threats, employee misconduct, unauthorized access, data exfiltration, credential compromise, vendor fraud, conflicts of interest, or trusted-party abuse. Experience with OSINT, digital forensics, enterprise logs, security telemetry, or identity and access-management information . Experience creating custom blockchain analytics through APIs, SQL , Python, blockchain explorers, node data, or other raw-data sources , rather than relying exclusively on commercial graphical interfaces. Relevant blockchain-specific training or certifications, including certifications associated with Chainalysis , TRM Labs, or comparable blockchain-analysis platforms . Professional certifications such as CFE, CFCS, CAMS, GIAC, or comparable investigative, fraud , financial-crime, cybersecurity, or intelligence credentials . What Success Looks Like Success in this role requires significantly more than knowing how to enter an address into a blockchain analytics platform. The successful candidate should be able to receive a complex transaction, wallet, allegation, or investigative question and independently determine how to trace the activity, which chains and protocols are involved, what the available data establishes, what additional information is needed, what attribution can reasonably be made, and where the technical or evidentiary limitations prevent a definitive conclusion . The individual should be able to move seamlessly between on-chain and off-chain evidence , recognizing that a blockchain transaction may establish movement of assets without necessarily establishing the identity, knowledge, intent, or conduct of the person behind a wallet. They should also be capable of converting a highly technical blockchain investigation into a concise and defensible explanation that an investigator, attorney, executive, regulator, or law-enforcement partner can understand and act upon. At the same time, this person must be sufficiently versatile to apply the same investigative discipline to internal fraud , insider risk, enterprise data, third-party misconduct, and protective-intelligence matters when required. The hierarchy is much clearer this way: blockchain investigations are the specialized core competency; fraud /investigative intelligence is the broader mission; enterprise analytics and PST support are complementary capabilities. That should materially improve the candidate pool versus a title that makes blockchain expertise appear interchangeable with general data analytics. OKX Statement: OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. The salary range for this position is $143,000 - $214,000 The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site. 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 .

Location: San Francisco, CA 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 Real-World Test Lab (RWTL) Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls — their devices, their environments, their hardest conditions, and their definition of success — and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring a Hardware Operations Engineer with a robotics specialism, reporting to the Director of the Real-World Test Lab, to own the physical layer of our evidence. You'll manage our fleet of capture devices and robots, engineer the test environments and the instrumentation inside them, support the captures our data programs depend on, and run physical test sessions, including the real-robot side of our sim-to-real work. A physical run only counts as evidence if the hardware is characterized, the environment is controlled, the ground truth is trustworthy, and someone can reproduce the run months later. You'll build what makes that possible: fixtures, ground-truth references, calibration and data-offload tooling, and the integrations that feed physical runs into the same automated evaluation system as everything else. You engineer the conditions, not just the setup. When a physical result didn't match expectations, you've worked out whether the hardware, calibration, environment, or system under test was responsible. Then you built the rig, reference, or logging that kept the question from coming back. You know an uninstrumented physical test is an anecdote, and in the Lab you'll be the person who can say with authority whether a strange result is real. What Success Looks Like - 30 days: Fleet inventory and characterization baseline complete, safe operating procedures defined for current spaces, and first instrumentation gaps identified. - 60 days: First physical robot run executed with ground-truth instrumentation, documented well enough to repeat, with results in the Lab's evaluation system. - 90 days: Test environments in regular use with controlled, documented conditions; capture support running smoothly with our data acquisition team; and the physical side of sim-to-real running on a standing instrumented protocol. What You'll Do - Own and Characterize the Fleet - Manage our capture devices, sensors, and robots end to end: inventory, calibration, firmware, maintenance, logistics, and spares. Characterize what each platform can and cannot do, so a device's limits are a known quantity rather than a surprise inside a result. - Engineer the Physical Test Environments - Design, build, and operate the spaces we test in, covering layout, lighting control, markers, obstacle configurations, and survey-grade ground truth references, across our office, rented or workplace-services-supported space, and partner or customer sites. Make each environment a controlled variable rather than an improvisation. - Build the Instrumentation - Create the rigs, mounts, references, and measurement setups that turn a physical run into quantitative data: trajectory ground truth, positional accuracy references, timing and synchronization across sensors, and automated condition logging. - Integrate Physical Runs Into the Evaluation System - Work with the AI Automation Engineer so physical results flow into the same scorecards and comparisons as software-only evaluations, through automated data offload, run metadata, and structured condition capture rather than a spreadsheet and a folder of files. - Run the Physical Test Sessions - Execute robot runs and device-in-the-loop tests: robot bring-up, teleoperation, scripted trials, and the repetition that makes a result statistically meaningful rather than anecdotal. - Own the Physical Half of Sim-to-Real - When a scenario has been evaluated in simulation, engineer and execute its physical counterpart so the comparison is valid, matching environment, route, lighting, sensor configuration, and robot setup, and instrumenting the run so divergence is explainable rather than mysterious. - Own Safety - Define and maintain safe operating procedures for robots and powered equipment in our test spaces, and coordinate with workplace services, IT, Legal, and site owners on access and safety requirements. - Automate Your Own Work - Script the repetitive parts, including configuration, calibration checks, data offload, and condition logging, so setup time falls and a colleague can run a session without you. What You'll Bring - Hands-on engineering experience with robotic hardware, covering bring-up, integration, teleoperation, troubleshooting, and maintenance. Mobile or wheeled platforms preferred. - Built test rigs, fixtures, or instrumentation that produced quantitative measurements of a physical system's behavior. - Designed and run structured physical experiments, including ground truth methodology, and documented conditions rigorously enough for someone else to reproduce them. - Worked with sensor calibration, multi-sensor synchronization, and coordinate frame conventions, and understand how errors in each propagate into a result. - Strong Python and command-line proficiency, with a track record of automating hardware configuration, data offload, or test execution. - Managed hardware fleets operationally: inventory, firmware, calibration schedules, logistics, and repair coordination. - Practical safety experience operating powered equipment or robots around people. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Worked with ROS or ROS 2, including writing nodes or integrating sensor drivers. - Operated NVIDIA Isaac Sim or Isaac Lab as a user, running scenarios someone else authored. - Worked with professional capture hardware such as terrestrial laser scanners, NavVis or Leica systems, LiDAR, 360 cameras, or drones. - Established survey-grade or motion-capture ground truth for localization or navigation evaluation. - Supported photogrammetry, Gaussian splat, or 3D reconstruction capture workflows. - Run test operations at customer or partner sites, with the coordination and discretion that requires. Competencies - Engineering judgment about physical systems. You reason about error sources: calibration drift, timing offsets, mounting rigidity, lighting variation, floor surface. When results disagree, you form a hypothesis and design the measurement that settles it. - Hands-on and unfazed. You'd rather be in the space with the robot than reading about it. Cables, mounts, batteries, firmware, and a session that starts at 7am are all part of the job. - Meticulous about conditions. You instrument rather than remember. You know the value of a physical test lives in how precisely its conditions were captured. - Safety-minded without being slow. You take real responsibility for operating robots around people, and you build procedures where the safe path is also the fast path. - Builds for other people. Your fixtures, scripts, and procedures get used by colleagues without you in the room. - Comfortable in an unfinished environment. Much of this does not exist yet. You'll be selecting equipment, designing the first rigs, and defining how a space gets configured, with support but without a playbook. Compensation & Benefits Base salary range of $142,200 to $193,000. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three 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: San Francisco, CA 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 Real-World Test Lab Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls - their devices, their environments, their hardest conditions, and their definition of success - and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring an AI Automation Engineer, reporting to the Director of the Real-World Test Lab, to build the system that produces our evidence. Today our evaluations are manual, inconsistent, and slow. You'll design and own the automation that runs them end to end on every relevant release, with no human driving it, turning one-off experiments into an always-on service the whole company relies on. This role is about owning the evidence, not executing a test plan. You'll decide how each workflow gets exercised, and you'll be measured on whether the company can trust the results, not on how much automation exists. The work counts when it keeps running correctly months later, without you in the loop. You believe evaluation is engineering, not process. You've built systems that test other systems, and you know the difference between a script that works on your laptop and infrastructure a team can trust. When a result couldn't be reproduced, you fixed the tooling instead of arguing about the number. What You'll Do - Build the Evaluation Machine - Own the automation that executes Lab evaluations end to end: environment setup, run orchestration, artifact capture, and result collection. Make reruns free so we test constantly rather than occasionally. - Make Results Comparable - Instrument scorecards so a result can be compared across product versions, devices, and capture conditions. A number without its lineage is not evidence. - Automate the Agent-Driven Layer - Build the agent workflows that exercise priority customer use cases at realistic scale, across the graded difficulty spectrum from easy to frontier, and be honest about where agents cannot yet replace human judgment. - Kill Manual Work Permanently - Convert one-off experiments into standing protocols that run on every relevant release. Automate recurring inspection wherever it can be automated, and route what genuinely cannot to scalable human review. - Make Failures Actionable - Produce diagnostics precise enough that a finding reaches its owner with a reproducible case and data attached. Findings that need re-investigation before anyone can act on them are half-finished. - Keep Data From Being the Bottleneck - Work with the AI Data Manager so every run is reproducible from a known dataset state, without anyone downloading and re-uploading data by hand. What Success Looks Like - 30 days: One priority workflow evaluated end to end with no manual steps, with results in a comparable scorecard. - 60 days: Evaluations trigger automatically on relevant releases, with diagnostics that route failures to the right owners. - 90 days: Three priority workflows under standing automated evaluation, with version-over-version comparison for leadership. What You'll Bring - Built and maintained production-grade automation or test infrastructure that other engineers relied on daily. - Experience evaluating systems where correctness is graded rather than binary, meaning quality, accuracy, or latency thresholds rather than pass/fail assertions. - Strong Python, with fluency in orchestration, CI-style pipelines, cloud storage, and reproducible environments. - Worked with backend services and APIs you did not own, integrating against them without becoming a bottleneck for their team. - Written up a technical finding clearly enough that a non-author could act on it without a meeting. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Built agent-based or LLM-driven automation for a task that previously required human judgment. - Worked on evaluation or benchmarking for computer vision, 3D reconstruction, or spatial systems. - Instrumented dashboards or scorecards that leadership used for release decisions. - Operated data provisioning or registry infrastructure across multiple environments and access models. Competencies - Intellectually honest. You design tests that produce answers people can trust, and you refuse to let a benchmark imply more than the evidence supports — including when the honest answer is inconvenient for your own work. - Pragmatic. You find the fastest path to a defensible result without going through one-way doors that undermine scaling. You have no patience for building infrastructure nobody has asked for yet. - AI-forward by instinct. You reach for agents and LLM-driven automation before you reach for headcount, and you're rigorous about verifying what they produce. - Builds for other people. You've maintained something after the initial excitement wore off. Your tooling is documented, your failures are legible, and colleagues use what you build without asking you to run it for them. Compensation & Benefits Base salary range of $158,400 to $210,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three 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: India Workplace: remote Job Overview  Welo Global is hiring an SDET (Software Development Engineer in Test) to bring deep technical rigor to middleware-layer testing. This role requires strong technical expertise across gRPC-Web, Proto3, HTTP/2, JSON-RPC/REST, proxy-based traffic inspection, and API scripting. The primary responsibility is to observe and reconstruct the network interactions generated by the onboarding UI, including request/response structures, schemas, headers, identifiers, Enums, and client-injected parameters. This is primarily an API/network analysis and evidence-generation role rather than a conventional UI automation or regression-testing role. The resource will produce sanitized network evidence and controlled, benign tracer replay scripts for downstream backend validation. Project Details Title: SDET - API/Middleware Rate: $9.50/hr Start Date: 26th October Duration: 5 Weeks Commitment: 35 Hours per Week Location: India (Remote) Job Type:Freelance (with the possibility of full time employment based on performance and project needs in all opportunity) Responsibilities • Design, build, and maintain automated API test suites covering gRPC-Web, Proto3, HTTP/2, and JSON-RPC/REST-based services • Export clean, sanitized HAR/network evidence while maintaining traceability between UI actions and corresponding network requests • Map relevant schemas, headers, identifiers, routing information, and client-injected parameters • Use proxy tools such as Mitmproxy, Charles Proxy, and browser DevTools to inspect, intercept, and validate network traffic between client and server • Develop and maintain API automation scripts using Python, Postman, and cURL for functional and regression testing • Analyze protocol-level request/response behavior to identify defects related to serialization, encoding, and transport • Inspect and validate request payload structure, including system-level headers (e.g., auth tokens, routing identifiers) and internal/hidden parameters, ensuring correct handling under both valid and malformed conditions • Collaborate with backend and middleware engineers to define testable contracts and edge-case scenarios • Continuously improve test automation frameworks for reliability, speed, and maintainability • Document technical findings, automation coverage, and known protocol-level limitations Required Qualifications • Strong hands-on expertise of 3-5+ years with gRPC-Web, Proto3, HTTP/2, and JSON-RPC/REST protocols • Proficiency with proxy/traffic inspection tools including Mitmproxy, Charles Proxy, and browser DevTools • Solid scripting/programming skills in Python, with practical use of Postman and cURL for API automation • Experience designing and maintaining automated test suites for middleware or API-layer services • Working understanding of API request structure, including headers, auth tokens, and internal/system parameters, and how to test for their correct handling • Understanding of software engineering practices as applied to test automation (version control, CI integration, code review) • Strong debugging skills at the network/protocol level • Experience analysing browser-generated network traffic and reconstructing API behaviour is strongly preferred • Experience with HAR analysis, API schema reconstruction, or controlled API replay is strongly preferred • Ability to work within approved staging/test environments and follow defined data-handling and test-authorization requirements is required #L1-CC1 Why join Welo Data?   ✨ Limitless Flexibility: Work on projects that fit your schedule while collaborating with a global leader in AI data services and localization.   🌱 Limitless Growth: Apply your skills, access diverse content types, develop through structured learning, and explore career paths that can lead to permanent roles.   🌍 Limitless Support: Be part of a global community with real-time assistance from our Community Experience team.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.     We can’t wait to meet you!     About Welo Data   Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.    At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

Location: India Workplace: remote Overview   We are seeking a Lead SDET (Software Development Engineer in Test) to provide end-to-end technical governance across all QA layers - frontend, middleware, and backend - for a complex, multi-layered onboarding platform. This role owns the architecture of API contract testing and the data modeling of complex entity relationships (e.g., hierarchical/parent-child style structures), while ensuring that quality assumptions made at one layer (such as client-side validation) are independently verified at every downstream layer rather than trusted at face value. The ideal candidate combines strong technical leadership with the ability to set and enforce delivery governance across cross-functional teams.   Main Responsibilities   • Provide technical governance across frontend, middleware, and backend testing layers   • Establish and enforce QA delivery standards, evidence requirements, review processes, and quality gates   • Review frontend constraint dictionaries and FSM/state-model outputs for completeness and consistency   • Review API schema reconstructions, network evidence, and tracer replay outputs for technical quality and traceability   • Coordinate with QA Analysts, SDETs, and Test Operations Associates to align technical execution with delivery timelines   • Review test architecture decisions, validation approaches, and coverage strategies   • Coordinate dependency resolution, evidence rework, and cross-layer reconciliation throughout the engagement   • Act as the escalation point for cross-layer technical discrepancies and evidence-quality issues   • Compile and quality-check the raw technical evidence dossiers produced by the workstreams   • Identify evidence gaps, inconsistencies, or areas requiring rework before handoff to client stakeholders   • Report on delivery health, technical risks, evidence quality, dependencies, and unresolved gaps   • Prepare the technical evidence package for handoff to the client team responsible for final modelling and logic-gap assessment   • Support technical readout preparation by ensuring that findings are traceable to empirical evidence   Project Details   • Title: Lead SDET • Start Date: 26th October • Duration: 4 Months • Location: India (Remote) • Job Type: Contractual (with the possibility of a Full-time employment extension based on performance and project needs)   Qualifications   • Proven experience of 8+ years in a QA leadership role spanning multiple testing layers (frontend, middleware, backend)   • Demonstrated expertise in API contract testing architecture and governance   • Practical experience with knowledge graph or entity-relationship data modeling and its application to test/data traceability   • Strong understanding of layered system architectures and the importance of independently verifying quality at each layer rather than relying on upstream assumptions   • Strong track record of technical delivery governance, including setting standards and quality gates   • Excellent cross-functional leadership and stakeholder communication skills   • Deep technical grounding across QA disciplines (manual, automation, systems-level testing) to credibly guide teams at every layer   • Experience mentoring or managing SDETs and QA Analysts   • Experience leading complex multi-week technical QA, API validation, or security-assessment engagements is strongly preferred   • Experience establishing evidence/traceability models across complex technical workflows is preferred   • Familiarity with knowledge graphs, entity-relationship models, or structured technical dependency/evidence modeling is preferred; deep knowledge-graph engineering expertise is not required   • Ability to synthesize technical evidence into concise stakeholder-ready findings and handoff materials   #L1-CC1 Why join Welo Data?   ✨ Limitless Flexibility: Work on projects that fit your schedule while collaborating with a global leader in AI data services and localization.   🌱 Limitless Growth: Apply your skills, access diverse content types, develop through structured learning, and explore career paths that can lead to permanent roles.   🌍 Limitless Support: Be part of a global community with real-time assistance from our Community Experience team.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.     We can’t wait to meet you!     About Welo Data   Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.    At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

Location: Chișinău, Moldova; Bălți, Moldova; Cahul, Moldova; Comrat, Moldova; Orhei, Moldova Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. 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: Madrid, Spain Workplace: hybrid Are you ready to join our digital revolution journey?    At Aleph, we’re not just part of the digital advertising landscape—we’re shaping its future. Representing the world’s leading platforms, including TikTok, Amazon, Google, and nearly 55 others, we operate in 130+ markets across new and existing geographies.   Our mission is to empower advertisers and brands to unlock the full potential of these platforms' advertising capabilities. By fostering long-lasting partnerships, we create limitless opportunities for people and businesses to advertise effectively at both local and global levels.   With a presence spanning continents, Aleph offers you the chance to be part of a fast-growing, innovative team where your work makes a direct impact. If you’re ambitious, forward-thinking, and eager to thrive in a dynamic, global environment, Aleph is the perfect place to build your career. We are looking for an experienced and operationally sharp Security Operations & Incident Response Analyst (L3) to join Aleph's global IT Security team. Reporting to the Global CISO, you will be the first line of defence when incidents occur and the engine behind the team's threat detection and response capabilities. You will own the end-to-end incident response process, lead threat hunting and intelligence activities, and manage the vulnerability and identity governance programmes — ensuring Aleph is both able to detect threats quickly and respond to them effectively across a complex, globally distributed environment. What you'll do: Incident Response Own and coordinate the end-to-end incident response process : identification, triage, containment, eradication, recovery, and post-incident review (lessons learned). Serve as the primary point of contact for security incidents escalated from IT Operations, the Security Engineer, and external sources. Maintain and continuously improve incident response playbooks for the most relevant threat scenarios (ransomware, phishing, account compromise, data breach, insider threat, etc.). Manage the security incident log and register : track all incidents, document timelines and actions, and produce trend analysis and reporting for the CISO. Coordinate with external SOC or MDR providers where applicable: review daily reports, validate alert quality, and manage escalation workflows. Data Breach Management Lead data breach investigations : scope the breach, gather and preserve evidence, assess PII exposure, and coordinate response with Legal, Privacy, and HR. Produce breach investigation reports with findings, root cause, and recommendations. Threat Hunting & Intelligence Conduct proactive threat hunting across the environment: develop hypotheses based on threat intelligence, search for indicators of compromise (IoCs), and investigate anomalous behaviour. Manage the Threat Intelligence function : track relevant threat actors, TTPs (MITRE ATT&CK), and sector-specific threat campaigns; integrate intelligence into SIEM/XDR detection rules and hunting queries. Produce threat intelligence summaries and briefings for the CISO and relevant stakeholders. Vulnerability Management Own the vulnerability management programme : schedule and execute periodic vulnerability scans across infrastructure, endpoints, and cloud environments. Analyse scan results, prioritise findings by risk and exploitability, and coordinate remediation with IT Operations within agreed SLAs. Track remediation progress, produce vulnerability metrics, and report status to the CISO. Validate remediation effectiveness through re-scanning and spot-checks. Identity & Access Management (IAM) Manage periodic access reviews : coordinate with system owners and HR to review and certify user permissions across critical systems, ensuring least privilege is maintained. Oversee the Privileged Access Management (PAM) programme: define PAM policies, monitor privileged account usage, and review access rights for administrator-level accounts. Investigate and respond to identity-related anomalies and access policy violations. What we are looking for: 3–5 years in a SOC analyst, incident response, or security operations role, with at least 1–2 years at L3 level is a plus. Experience implementing or managing IAM and PAM solutions Experience working within international or multinational environments. Hands-on experience with incident response engagements (internal or consulting) is strongly valued. Relevant certifications: GCIH, GCFE, GCFA, CEH, CompTIA CySA+ , or equivalent. OSCP is a plus. Strong hands-on experience with SIEM platforms (alert triage, rule writing, query development) and EDR/XDR tools . Solid knowledge of the MITRE ATT&CK framework and its application to threat hunting and incident response. Experience conducting vulnerability scans using tools such as Tenable Nessus, Qualys, Rapid7, or similar. Familiarity with IAM and PAM concepts and platforms (e.g. CyberArk, BeyondTrust, Azure PIM, or equivalent). Experience with digital forensics and incident response (DFIR) methodologies: evidence collection, log analysis, and timeline reconstruction. Knowledge of threat intelligence platforms and feeds (e.g. MISP, VirusTotal, threat intel feeds). Understanding of ISO 27001 incident management controls, NIS2 incident reporting obligations, and PCI DSS requirement 12.10 . Calm and decisive under pressure. Strong investigative mindset with structured problem-solving approach, excellent documentation skills. Ability to communicate incident status and findings clearly to both technical teams and executive stakeholders. Collaborative and proactive, comfortable working asynchronously across time zones. English : full professional proficiency (C1/C2) — primary working language. Spanish : professional proficiency is a plus. In line with the EU Pay Transparency Directive, we are committed to fair and open compensation practices. For this role, the minimum gross annual base salary is EUR 48,000 EUR. In addition to base salary, this role includes a variable component, paid annually. The final offer will reflect your experience, skills, and the scope of the role.   #Aleph Why Join Us?   Aleph is a place of many cultures, perspectives, and talents. We support each other, creating an environment of giving and receiving. We value partnership and communication because we believe it takes a group of people to achieve great things. We are energized by our ever-changing industry, our curiosity keeps us learning and seeking out new opportunities.     We stay flexible and adaptable, and believe in moving with the speed of change. We encourage everyone to strive for more, providing our internal talent with growth opportunities and the ability to learn together.    #ALEPH

Location: Tuzla, Bosnia and Herzegovina; Zenica, Bosnia and Herzegovina; Mostar, Bosnia and Herzegovina; Sarajevo, Bosnia and Herzegovina; Travnik, Bosnia and Herzegovina Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. 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 B2 (ability to read instructions, watch training videos, and communicate effectively); 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: Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data. 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: Skopje, North Macedonia; Bitola, North Macedonia; Prilep, North Macedonia; Veles, North Macedonia; Kumanovo, North Macedonia; Štip, North Macedonia Do you enjoy precise, detail-oriented work and have an eye for spatial accuracy? This role puts those skills to use on a project at the intersection of geospatial data and AI. As a Data Annotator on our project, you will support building digital 3D models of power grids and other critical infrastructure. These models help energy companies analyze network conditions, predict risks, and plan maintenance using AI and physics-based simulations. You will help reconstruct electrical distribution networks in 3D by combining LiDAR point cloud data, GIS maps, and drone imagery – contributing directly to the accuracy and reliability of these digital twins. 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 B2 (ability to read instructions, watch training videos, and communicate effectively); 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: Background in GIS, Geodesy, Cartography, Land Management, Civil Engineering, or a related field; Any basic understanding of power grids (poles, transformers, wires) or prior experience with LiDAR data. 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: Kyiv, Ukraine; Cherkasy, Ukraine; Kropyvnytskyi, Ukraine; Uman, Ukraine; Poltava, Ukraine; Dnipro, 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 B2 (ability to read instructions, watch training videos, and communicate effectively); 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: Remote Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE Open to hiring remote — we also have offices in New York, San Francisco, Seattle, London, Paris, and Tel Aviv. Runway is hiring a Detection & Response Engineer to own how we find and stop attacks against our infrastructure, our research environment and our products. Securing a company that trains and serves frontier video models is a different problem from securing a typical SaaS product. The environment includes research compute, large training datasets, a fast-moving build pipeline and engineers who work inside AI-assisted tooling every day. Each of those changes what an attack looks like and what you need to see to catch it. You'll join the Security team and build our detection and response program the way an engineer would: detections as code, response as automation, evidence as something you can query. This is a role with real ownership: you'll own the detection program end to end, from what we log to how quickly we close an incident. You'll report to the head of security, partner with engineers across platform and research, and shape how this function grows from here. WHAT YOU'LL DO - Own detection and response end to end: what we log, what we alert on, how we triage and how we recover - Write and tune detections as code across multiple cloud environments, Kubernetes, identity systems, endpoints and SaaS, and measure them on coverage and precision rather than alert volume - Lead incident response from the first alert through containment and forensics, then write the post-incident review people actually read - Build automation that takes toil out of triage, including enrichment, correlation, containment actions and evidence collection, and use LLM-based tooling where it holds up under audit - Monitor AI agents and developer tooling operating inside our environment, and turn that into concrete telemetry and controls - Partner with platform and research engineers so new systems ship with logging and response playbooks in place on day one - Run threat hunts and tabletop exercises against the parts of the environment that worry you most, and fix what you find - Turn incident and detection metrics into evidence for SOC 2, ISO 27001 and enterprise customer security reviews, working with our GRC team - Participate in an on-call rotation for security incidents WHAT YOU'LL NEED - Hands-on incident response experience: you've triaged live alerts, led investigations and written up what happened afterward - Experience building and tuning detections in a modern SIEM, ideally managed as code - Working knowledge of how attackers move through cloud and Kubernetes environments (IAM abuse, container escape, credential theft, supply chain compromise) and what that leaves behind in logs - Comfort writing Python, Typescript, Rust or another language to automate response work and connect security tools - Familiarity with at least one major cloud platform and with Kubernetes at the level of audit logs, RBAC and workload identity - Clear writing. Incident timelines, detection documentation and updates to leadership are all part of the job - Judgment about what to alert on, what to automate and when to wake someone up EVEN BETTER IF YOU HAVE - Experience monitoring GPU or HPC-style infrastructure, or research environments with large datasets - Experience building detections or guardrails for AI agents, LLM tooling or MCP servers - Cloud forensics experience: disk and memory acquisition, cloud audit trail reconstruction, chain of custody - Published open source detection content Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: San Francisco, CA 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 Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Senior Computer Vision Engineer to join our Embodied AI team, focused on 3D scene understanding and semantics. A reconstructed environment is only useful to a robot once it knows what is in it: which surfaces are floor, which objects can be grasped, moved, or opened, where one room ends and another begins. You'll work hand in hand with our Research Scientists to take advances in open-vocabulary perception, 3D semantic labeling, and scene graph construction and turn them into reliable capabilities that embodied AI teams can use in production. This is an applied research role. You'll live at the boundary between a research prototype and a production pipeline: adapting methods so they hold up on messy customer captures, lifting 2D semantic signals into geometrically consistent 3D, defining what "semantically correct" means for a downstream policy, and feeding what you learn back into the research agenda. You understand that the difficult part is often not the core method, but the messy inputs, edge cases, operational constraints, and downstream requirements surrounding it. You care about quality, cost, latency, and reliability, and you know that a system is only successful when people can depend on it. This is a hands-on engineering role for someone who wants to build, ship, and own outcomes. You'll help shape both the technology and the product, while remaining close to the code and the problems our customers are trying to solve. What You'll Do - Productionize 3D Scene Understanding Capabilities - Turn research prototypes in open-vocabulary segmentation, 3D semantic and instance labeling, affordance prediction, and scene graph construction into reliable pipeline components and services that operate across varied customer data and environments. - Own End-to-End Output Quality - Ensure that reconstructed environments carry labels, instances, and relationships that are consistent, complete, and correct enough for downstream simulation and policy learning, and define what "correct enough" means for each customer workflow. - Bridge Research and Production - Work day to day with the Embodied AI Research Scientist: pressure-test new methods on real customer data, identify where they break, and bring production and customer constraints back into research planning to prioritize the advances that matter most. - Make Systems Robust to the Real World - Diagnose failures caused by capture quality, scene complexity, scale, calibration, coordinate conventions, and other assumptions that prototypes often leave implicit. - Build Evaluation and Quality Infrastructure - Create datasets, regression tests, quality gates, and benchmarking tools that help the team measure whether changes improve the system. - Improve Performance, Throughput, and Cost - Profile and optimize GPU and distributed workloads, reduce unnecessary reruns, and help establish the economics of running reconstruction at scale. - Work Across the Product Boundary - Partner with Embodied AI product and engineering teams to understand customer requirements and deliver capabilities that fit real training, evaluation, and deployment workflows. Help evolve the representations, tooling, and operational systems that allow reconstructed environments to move reliably into customer applications. What You'll Bring - 5+ years of computer vision experience and a bachelor's degree or equivalent, - Significant experience building and operating production computer-vision, machine-learning, graphics, or data-processing systems. - Deep hands-on experience with scene understanding: semantic, instance, or panoptic segmentation; open-vocabulary detection and segmentation; or vision-language models applied to perception. - Experience taking 2D perception into 3D, such as multi-view label fusion, 3D semantic segmentation, instance tracking across views, or scene graph construction over reconstructed geometry. - Experience delivering reliable computer-vision or 3D systems used by other teams or customers, including the evaluation that proved they worked.. - Practical command of 3D and spatial data, including geometry, camera models, coordinate frames, calibration, and metric scale. - Strong Python and PyTorch skills, with the ability to work in C++ or other performance-oriented environments when needed. - Experience with cloud infrastructure, GPU workloads, distributed processing, or large-scale data pipelines. Nice to Have - Hands-on experience with 3D reconstruction, photogrammetry, structure from motion, Gaussian splatting, neural rendering, or meshing. - Experience with SLAM, visual positioning, localization, or large-scale mapping systems. - Experience with robotics, simulation, or embodied AI applications, in particular how semantic labels are consumed by a policy or a simulator. - Built evaluation or benchmarking infrastructure for perception or reconstruction systems. - Experience optimizing large-scale GPU inference workloads for cost, throughput, or latency. - A publication record or contributions to widely used open-source perception codebases. - Advanced degree in computer vision, robotics, machine learning, or a related field. Competencies - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here Syndrome and analysis paralysis. You find the fastest path to a working capability without one-way doors that undermine scaling. - Strong systems instincts. You understand that production quality includes reliability, observability, cost, latency, maintainability, and usability—not just algorithmic accuracy. - Comfort with ambiguity. You can make progress when the problem, data, and requirements are still evolving. Compensation & Benefits Base salary range of $229,500 to $255,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three 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: 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 Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. Niantic Spatial's R&D Team in London is seeking a Research Scientist to push the frontiers of Spatial AI, advancing our Large Geospatial Model as a dedicated member of the Embodied AI group. You will invent and develop algorithms and systems that sit at the cross-section of computer vision, machine learning, AI, graphics, and robotics. We're passionate about discovery, so we're looking for scientists who want to learn, publish, teach, and deploy every new invention. What You'll Do - Develop New Spatial Representations - Develop new spatial representations that embodied AI can learn from, train in, and act on. - Advance Real-to-Sim Pipelines - Advance real-to-sim pipelines connecting real-world observations, 3D reconstruction, simulation, and robotic policy learning. - Solve Emerging Spatial Problems - Solve emerging problems that relate to spatial intelligence, 3D scene representation, training data, model efficiency, and interactive systems. - Take Capabilities Through to Evidence - Take new capabilities through to evidence: what changed for the policy, not only what changed in the reconstruction. - Build Prototypes - Build proof of concept prototypes, initially for internal use, where some will need to run at production scale on customer data. - Collaborate Across Research and Product - Collaborate closely with researchers, engineers, and product partners to bring novel models to production. - Publish Your Work - Publish and present your work. What You'll Bring - A PhD in computer vision, robotics, graphics, machine learning, or a related field, or equivalent research experience, with a publication record at top venues. - Substantial expertise in robotics or embodied AI, including experience in sim-to-real transfer, domain randomization, policy evaluation, and simulation-based learning. - Deep experience with 3D scene representations: Gaussian splatting, neural fields, meshes, point clouds, or implicit representations. - You have applied generative or diffusion models to 3D data, such as scene completion, inpainting, relighting, or novel view synthesis from sparse capture. - You have worked on 3D semantics, open-vocabulary scene understanding, or scene graphs. - Proficiency in Python and Deep Learning libraries such as PyTorch. - GPU or graphics programming experience, such as custom CUDA kernels, shaders, or differentiable rendering. - A track record of contributing to widely used open-source research codebases. Nice to Have - Proficiency in C++. Compensation & Benefits Base salary range of £103,500 to £202,500. 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. 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: United Kingdom; Ireland; Cyprus; Portugal; Poland Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. Kraken's Market Surveillance function is responsible for detecting, investigating and reporting market abuse across our regulated trading venues, spanning spot crypto markets, crypto futures, tokenised equities, OTC markets, and consumer trading. As our licensing footprint and product range grow, so does the scale and complexity of the surveillance programme behind them. We're hiring a Principal Compliance Associate to take on the function's most complex casework, and help shape how we detect and cover market abuse as the business scales.   THE OPPORTUNITY - Own complex investigations end to end, writing findings up to a standard a regulator can rely on, and present conclusions to a range of stakeholders. - Lead or contribute to periodic threshold and model reviews, recalibrating surveillance rules and alert thresholds as trading behaviour, products and market structure evolve. - Support the design, build-out and integration of surveillance platform capability, including onboarding new products, venues and data sources onto the surveillance system. - Contribute to market abuse risk assessments, helping identify and score risk across products, jurisdictions and entities, and translate findings into surveillance coverage. - Use AI and automation tools responsibly to speed up evidence-gathering, case reconstruction and detection-model development, always with human judgement over the final call. - Support conflicts of interest, information barrier, and personal account dealing matters across Markets Compliance, extending beyond surveillance casework where buy-side or asset management experience is directly relevant.     WHAT YOU BRING - Experience investigating market abuse or trading conduct inside a firm subject to market conduct regulation, such as an exchange, broker-dealer, trading venue, or comparable regulated trading business. - A track record running investigations end to end, including writing findings up to a standard a regulator can rely on and presenting conclusions to stakeholders. - Working knowledge of core market abuse typologies e.g. spoofing, wash trading, insider trading, front running, ramping. - Experience with, or strong working knowledge of, threshold and model calibration, surveillance platform integration, market abuse risk assessments, and audit remediation. - Comfort using generative AI and other automation tools to improve the speed and quality of investigative work, while maintaining the human oversight regulated casework requires. - Familiarity with a surveillance platform (such as Scila, Nasdaq SMARTS, Eventus, or NICE Actimize) and comfort with SQL or a similar query tool for evidence-gathering. - Clear, evidence-first written communication - your case files, escalations and regulatory drafts will sometimes be read by auditors and regulators without you in the room to explain them. - Exposure to crypto-asset markets is welcomed but not required. What matters most is regulated-market investigation experience; strong candidates from traditional securities or derivatives markets are encouraged to apply.     NICE TO HAVES - E-comms surveillance experience.     Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: San Francisco, CA; Sunnyvale, CA Workplace: Hybrid At Niantic Spatial, we’re building the future of physical AI. Powered by a proprietary database of over 30 billion posed images, our groundbreaking mapping technology unlocks a new dimension of interaction and spatial intelligence that helps both humans and machines better understand, represent, navigate, and engage with the real environment. Join us as we build the real-world foundational models for physical AI, so people and machines can work efficiently and safely together. As a Senior Computer Vision Engineer on the Applied Algorithms team, you will own significant parts of our Localization technology. As a member of this team, you will be responsible for building the Map representing a living geospatial world model, as well as the centimeter-level accuracy Visual Positioning System (VPS) that allows people and robots to explore the real world. Part of the role will be bridging the gap between R&D and production, turning complex geospatial data into a persistent sense of space and enabling the next generation of spatial AI. RESPONSIBILITIES - System Architecture: Design, develop, and maintain production-grade computer vision systems that power Niantic Spatial’s VPS (Visual Positioning System) and 3D mapping pipelines. - Algorithmic Innovation: Refine and scale algorithms for our VPS system including, SfM (Structure from Motion) and Feed Forwards models, efficient feature and descriptor extraction to have the best possible accuracy and recall. Moving algorithms from research concepts to hardened production code that can scale for our map of the world. - Performance Engineering: Optimize complex ML and CV code for maximum efficiency in cloud and mobile environments, ensuring low latency and high-performance execution on GPU/CPU. - Benchmarking & Evaluation: Create and own the tools and frameworks used to evaluate the quality of our spatial grounding and 3D maps against ground-truth data. - Technical Leadership: Lead technical design reviews, mentor junior engineers, and serve as a team anchor for resolving complex technical disagreements within the mapping stack. - Cross-Functional Delivery: Collaborate with Product, Research, and Operations teams to ensure that state-of-the-art computer vision solutions translate into delightful user experiences. REQUIREMENTS - Education: BS, MS, or PhD in Computer Science, Robotics, Computer Vision, or a related technical field (or equivalent professional experience). - Years of Experience: 5+ years of experience developing and shipping algorithms for image processing, computer vision, or 3D reconstruction. - Coding Proficiency: Expert-level proficiency in python and/or C++. - Domain Expertise: Proven track record in designing solutions for Structure from Motion (SfM), VPS or 3D mapping.. - Frameworks & Tools: Deep experience with Deep Learning frameworks (PyTorch or JAX) and version control (Git). - Required in-office days: 3 days per week Plus If: - Experience in planning and leading technical projects from inception to production. - Significant contributions to open-source CV libraries (OpenCV, COLMAP, etc.). - Experience with CUDA or shader programming for performance optimization. Candidate Privacy Policy 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. If required by law, by submitting my job application I consent to the processing of my information as described in that Notice, including processing information I voluntarily disclose to Niantic Spatial, such as health or medical information, race or ethnicity data, and sexual orientation data and, in limited circumstances sharing information with third parties such as references and other third parties that assist in the hiring process. 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.

Location: Bratislava, Slovakia; Košice, Slovakia; Žilina, Slovakia; Prešov, Slovakia; Nitra, Slovakia; Trnava, Slovakia 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 B2 (ability to read instructions, watch training videos, and communicate effectively); 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: Poznań, Poland; Wrocław, Poland; Łódź, Poland; Lublin, Poland; Szczecin, Poland; Rzeszów, Poland 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.