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• Participation in professional trainings. • Support for extracurricular activities.
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разработка ПО на Python с использованием FastAPI, PostgreSQL. отличное знание Python.
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Location: California Workplace: onsite Role Overview We are looking for a Hardware Lab Technician to own the physical side of a large-scale robot data collection operation. You’ll keep the fleet running, build what’s next, and be the person the lab calls when something stops working. This is a hands-on role across research and low-volume production where embodiments, grippers, and camera rigs change fast—and the hardware has to keep up. Day-to-day teleoperation is handled by a dedicated operator team you support; you maintain what they run on and help ensure data quality through reliable, well-calibrated hardware. Project Details Location: 100% Onsite (Santa Clara, CA, US) Employment: Full-time W-2 Shifts: Monday–Friday, 7AM - 3:30PM or 9AM - 5:30PM Start Date: ASAP Contract Duration: 12-month contract with possibility of extension Rate: $40 per /hour What You’ll Do Build, wire, and bring up data collection stations — robot arms, multi-camera rigs, workstations, teleoperation hardware, and cable management that survives daily operator use. Keep the fleet running: daily checks, preventive maintenance, calibration routines, and diagnosing faults on arms, hands, and sensors. Swap and integrate end-effectors and grippers, dexterous hands, force/torque and tactile sensors, and RGB-D cameras. Run calibration and firmware procedures across the fleet, and catch drift before it reaches the data. Assemble and iterate prototype hardware coming out of our mechanical and electrical engineers — printed parts, off-the-shelf components, vendor-fabricated parts, and custom harnesses. Soldering, crimping, connectorization, harness building, and PCB rework support at the bench. Own the lab's physical state: spares and consumables inventory, parts kitting, bench and tool organization, and shipping, returns, and RMAs with vendors. Support teleoperators on hardware issues during live collection — triage fast, fix or escalate, and get the station back up. Document what you do. Build sheets, maintenance logs, calibration records, and hardware SOPs the next technician can follow. Help bring up new embodiments and new stations alongside engineers and researchers. What we need to see 3+ years hands-on technician experience in a lab, prototyping, or low-volume build environment — robotics, medical devices, aerospace, semiconductor equipment, or similar. AS in a technical field, a relevant trade or technical certificate, or equivalent hands-on experience. Mechanical assembly fundamentals: fasteners and torque, bearings, belts, linkages, and the ability to read CAD and mechanical drawings (Onshape, SolidWorks, or similar). Electrical hands: soldering including basic SMD rework, crimping and connectorization, harness building, and confident use of a multimeter and oscilloscope. Comfortable in Linux at the command line — SSH into a workstation, run a calibration script, read a log, and tell us what it said. Experience with motors, encoders, and sensor integration, and an understanding of what a bad ground or a marginal cable does to a data stream. Methodical and self-documenting. An undocumented fix is a future outage. Comfortable with ambiguity and frequent change, and able to prioritize when more than one lab needs you at the same time. Able to work on-site in Santa Clara, with flexibility on shift coverage as the labs run extended hours. Ways to stand out from the crowd Humanoid or bimanual platforms (Unitree, Fourier, ALOHA/ARX-class rigs) and dexterous hands. Maintenance and calibration on collaborative or industrial arms — UR, Franka, xArm, ARX, or equivalent. Multi-camera rig build and calibration; RealSense, ZED, or Orbbec-class depth cameras. Running and maintaining FDM or SLA printers, and designing your own simple fixtures and adapters. Light scripting in Python or bash to automate a repetitive bench or calibration task. Experience in a high-throughput lab or production line where uptime or yield was a number someone tracked. Vendor-facing experience: RMAs, lead times, and spares planning. Job reference: #L1-CC1 Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment. To know more details (Click here) In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
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Figure is looking for a Mechanical Engineer Structures Robot Hands to design, validate, and scale robot-hand structural hardware.
120 000 – 250 000 $
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Locus Robotics is looking for a Lead Robotics Software Engineer to lead robotic software development, product integration, deployment, and engineering teams.
130 000 – 190 000 $
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Locus Robotics is looking for an Onsite Support Engineer Robotics to monitor robotic fleets, troubleshoot systems, optimize workflows, and support customer operations.
50 000 – 90 000 $
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Key requirements: experience with at least one modern language such as Java, Python, C++, or C#.
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разработка и прототипирование электронных систем; интеграция датчиков и полезной нагрузки;
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Location: Santa Clara, CA Workplace: onsite About Welo Data Welo Data, a Welo Global brand, is the multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally. They deliver the human judgment, data infrastructure, and evaluation systems that ensure AI models perform reliably across languages, cultures, and real-world contexts, at every stage from training through deployment. Its global network of 500,000+ vetted experts spans 300+ languages and locales, enabling high-quality multilingual data creation and structured model evaluation across the full spectrum of modern AI applications — from large language models and voice and speech systems to agentic workflows and robotics and embodied AI. This breadth of linguistic, cultural, and domain expertise enables Welo Data to address critical AI development challenges, including safety, bias, inclusivity, and cross-lingual reliability. A unified global operating model, led by specialized program and quality experts and grounded in assessment-driven talent selection, localized rubrics, and continuous calibration, ensures consistent performance across languages, domains, and modalities. Underpinning all of this is NIMO™ (Network Identity Management and Operations), Welo Data's proprietary identity and fraud-prevention framework. Built to maintain data integrity and workforce trust across a global contributor base, NIMO combines advanced verification, continuous monitoring, and structured QA to ensure every dataset is accurate, traceable, and culturally grounded. welodata.ai Role Overview You own a shift. Not a zone of it, not a function within it — the whole thing. Roughly 140 operators, 13 Cell Leads, and 3 Operations Supervisors collecting robot demonstration data, and you are the single person accountable for what that shift produces, how good it is, and whether everyone goes home safe. The shift you own runs whether or not the Production Manager is in the building. That's the job: your shift should be indistinguishable in output and quality from the one before it and the one after it. What You Will Do Own your shift's production plan end to end — accepted episodes, first-pass acceptance, utilization, and labor efficiency against target. Manage 2–3 Operations Supervisors; own their performance, their development, and the quality of the Cell Lead bench underneath them. Run shift start-up, mid-shift review, and a documented handoff — you receive the shift before yours and hand off cleanly to the shift after. Make the real-time calls: redeploying staff when a cell goes down, resequencing work when a task type stalls, flexing coverage when attendance comes in short. Own safety on your shift — daily walks, protocol enforcement, incident response, and the expectation that your supervisors use: their stop-work authority. Partner with Data Quality on your shift's acceptance rate; drive root cause into retraining and process rather than into a rework queue. Escalate equipment and rig issues to Lab Engineering and keep staffed-but-idle hours visible. Handle performance management and employee relations escalations from your supervisors, partnering with HR. Hold California meal, rest, and overtime compliance across every non-exempt employee on your shift. Report your shift's performance and variance daily, with the explanation and the fix, not just the number. What Good Looks Like Your shift hits plan without overtime surprises or last-minute heroics. Handoffs are clean enough that the next shift starts producing immediately. Your supervisors make decisions without calling you, and your Cell Leads are being prepared for supervision. Quality on your shift doesn't vary from the other shifts — consistency is the whole point of this layer. Problems reach the Production Manager as "here's what happened and here's what I did," not as an open question. Basic Qualifications 5+ years in production, manufacturing, warehouse, or lab operations, including 2+ years managing supervisors or team leads. Experience with full accountability for a shift or a production area of 75+ hourly employees. Track record owning daily output and quality targets, and explaining variance credibly. Experience with performance management, attendance, and employee relations for a non-exempt workforce. Working knowledge of California wage and hourly requirements for non-exempt employees. Available to own an assigned shift (day, swing, or night) onsite in Santa Clara. Preferred Qualifications Robotics, hardware, AI data collection, advanced manufacturing, or technical lab background. Experience in a quality-gated operation where output is inspected before it counts. Promoted from a supervisor role, or has promoted supervisors from their own team. Comfort pulling and interpreting your own shift data from dashboards or spreadsheets. Continuous improvement background — Lean Six Sigma, or equivalent practical experience. Bilingual (English/Spanish). Work Environment and Physical Requirements Onsite robotics lab and warehouse environment; the majority of your shift is spent on the floor. Assigned shift, with occasional cross-shift coverage during ramps, launches, and handoff issues. Must be able to stand and walk the floor for extended periods. Must be able to occasionally lift and/or move up to 25 lbs. Why This Role Matters Consistency across shifts is what turns a lab into an operation. This role is the reason the third shift produces like the first one, and the reason problems get solved on the floor instead of escalating. Benefits Included in the Offer: - Friendly Working Environment - IT Equipment - Social Activities - Global Mobility Policy - Employee Referral Program - Employee Assistant Program - Medical, Dental, and Vision Insurance - HSA & FSA - 401(k) retirement - Short & Long Term Disability Insurance - Accident, Critical Illness, Hospital Indemnity Insurance - Telemedicine Benefit - Annual Leave - Paid Public Holidays - Maternity/Paternity Leave Hourly Pay: $71-$81/hour. Job Reference: #LI-JC1
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Location: Santa Clara, CA Workplace: onsite About Welo Data Welo Data, a Welo Global brand, is the multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally. They deliver the human judgment, data infrastructure, and evaluation systems that ensure AI models perform reliably across languages, cultures, and real-world contexts, at every stage from training through deployment. Its global network of 500,000+ vetted experts spans 300+ languages and locales, enabling high-quality multilingual data creation and structured model evaluation across the full spectrum of modern AI applications — from large language models and voice and speech systems to agentic workflows and robotics and embodied AI. This breadth of linguistic, cultural, and domain expertise enables Welo Data to address critical AI development challenges, including safety, bias, inclusivity, and cross-lingual reliability. A unified global operating model, led by specialized program and quality experts and grounded in assessment-driven talent selection, localized rubrics, and continuous calibration, ensures consistent performance across languages, domains, and modalities. Underpinning all of this is NIMO™ (Network Identity Management and Operations), Welo Data's proprietary identity and fraud-prevention framework. Built to maintain data integrity and workforce trust across a global contributor base, NIMO combines advanced verification, continuous monitoring, and structured QA to ensure every dataset is accurate, traceable, and culturally grounded. welodata.ai Role Overview We're hiring a Senior Manager, Robotics Lab Operations to run the floor. You'll own day-to-day execution across our Santa Clara robotics labs — managing the Lead layer, driving throughput and quality across a 100+ person hourly workforce operating on multiple shifts, and serving as the operational point of contact for the client. This is a hands-on production leadership role. You're on site, on the floor, and accountable for whether the work ships on time, at quality, and safely. You'll build the management structure that makes a large hourly team run well: clear shift coverage, real supervision, consistent standards, and a team that wants to stay. What You Will Do Lead the team Manage a team of Leads and Supervisors across multiple shifts; own their performance, development, and coverage model. Oversee 100+ full-time hourly data collection associates, operators, and lab technicians. Own staffing: headcount planning, scheduling, shift structure, attendance, overtime, and surge coverage. Partner with recruiting and workforce management on hiring ramps, onboarding, and time-to-productivity. Handle performance management and employee relations on the floor, partnering with HR on escalations. Build a floor culture where standards are clear, feedback is normal, and attrition stays low. Drive operations Own daily, weekly, and monthly production targets across all lab programs — throughput, quality, and utilization. Run the operating cadence: shift handoffs, daily standups, huddles, escalation paths, and a shift-to-shift continuity model that actually holds. Track and report on KPIs — output per shift, quality scores, rework, downtime, fill rate, and labor efficiency. Identify bottlenecks and lead continuous improvement across workflows, lab layout, equipment usage, and staffing models. Partner with engineering and program teams on lab setup, new program launches, and capacity planning. Ensure labs stay safe and compliant in partnership with the Robotics Safety & Compliance Lead; enforce protocols on the floor. Own the client relationship Serve as the primary operational contact for the client on-site — status, escalations, change requests, and performance reporting. Translate client requirements into clear, executable floor instructions and quality standards. Represent operations in business reviews with clear, data-backed reporting on delivery and risk. What Good Looks Like Shifts run consistently whether or not you're in the building. Hit targets without heroics — predictable throughput, stable quality, controlled labor cost. Leads those who are growing into stronger managers. Low attrition and high attendance on a large hourly team. A client who hears about issues from you first, with a plan attached. Safety and compliance treated as part of production, not a separate conversation. Basic Qualifications 7+ years in operations, production, or manufacturing management, including 3+ years managing managers or supervisors. Direct experience leading 100+ hourly employees in an onsite production, lab, warehouse, fulfillment, or manufacturing environment. Proven experience running multi-shift operations, including shift scheduling, coverage, and handoff management. Strong track record owning operational KPIs — throughput, quality, utilization, labor cost. Experience with workforce planning, performance management, and employee relations for an hourly workforce. Clear communicator who can move between floor-level direction and executive or client-facing reporting. Must be able to work onsite in Santa Clara, with flexibility to support multiple shifts as needed. Preferred Qualifications Experience in robotics, hardware, AV/AI data collection, advanced manufacturing, or technical lab environments. Experience as the operational owner of a client or customer relationship, including SLA and business review ownership. Background in a high-growth or rapidly scaling operation — standing up new sites, lines, or programs. Familiarity with Lean Six Sigma, or other continuous improvement methodologies. Comfort with operational tooling and data — WFM systems, dashboards, ticketing, or scripting/SQL to pull your own numbers. Experience managing a non-exempt workforce under California wage and hourly requirements. Bilingual (English/Spanish) a plus for floor communication. Work Environment and Physical Requirements Onsite robotics lab and warehouse environment in Santa Clara. Regular floor presence across shifts; occasional early, late, or weekend coverage during ramps and launches. Must be able to stand and walk the floor for extended periods. Must be able to occasionally lift and/or move up to 25 lbs. Fast-paced environment with evolving operational needs. Why This Role Matters Our labs are where the data actually gets made. This role makes that work predictable at scale — building the management layer, the operating rhythm, and the team that lets us take on more without losing quality, safety, or our people. Benefits Included in the Offer: - Friendly Working Environment - IT Equipment - Social Activities - Global Mobility Policy - Employee Referral Program - Employee Assistant Program - Medical, Dental, and Vision Insurance - HSA & FSA - 401(k) retirement - Short & Long Term Disability Insurance - Accident, Critical Illness, Hospital Indemnity Insurance - Telemedicine Benefit - Annual Leave - Paid Public Holidays - Maternity/Paternity Leave Hourly Pay: $90-$110/hr. Job Reference: #LI-JC1
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Location: Santa Clara, CA Workplace: onsite Role Overview We are looking for a Senior Software Engineer to own the systems that power a large-scale data collection operation, including the collection platform, operator tooling, data pipeline, and fleet infrastructure. This is an engineering role. Day-to-day teleoperation is performed by a dedicated operator team that you direct — you build what they run on, and you own what comes out of it. Project Details Location: 100% Onsite (Santa Clara, CA, US) Employment: Full-time W-2, Monday–Friday, 9:00 AM–5:00 PM Start Date: ASAP Contract Duration: 12-month contract with possibility of extension Rate: $105/hour What You’ll Do Design, build, and maintain the software behind our data collection stations — teleoperation stack, multi-camera recording, and session tooling. Deploy and upgrade that stack across the fleet without stopping collection; keep workstations, containers, and networking healthy. Own the data pipeline end to end: automated validation, conversion into our dataset format, upload, metadata, and versioning. Build the QA tooling that catches dropped frames, stream desync, bad calibration, and mislabeled episodes before data reaches training. Direct a team of teleoperators — define task protocols and SOPs, onboard them on new tasks and embodiments, review session quality, and unblock them daily. Own fleet reliability: calibration and firmware pipelines, sensor and end-effector integration, root-cause analysis of recurring faults, and vendor escalation. Bring up new stations and new embodiments; report throughput, yield, and data health to the research team. What we need to see MS in CS, Robotics, EE/ME, or a related field (or BS with equivalent hands-on experience). 3+ years building software for real robot systems — not simulation only. A system you designed and shipped that other people depended on daily, and that you kept running. Strong Python and Linux; Docker, git, CI, and SSH-based fleet administration. Robot middleware and real-time multi-sensor recording — ROS 2 or equivalent vendor SDKs. Experience supporting a data collection or teleoperation operation: you have built the tools operators depend on and owned throughput and quality numbers. Comfortable around robot hardware — arms or humanoids, dexterous hands, RGB-D cameras, and the calibration that keeps them honest. Able to lead operators without formal authority: you write clear SOPs, train people, and communicate status without being asked. Ways to stand out from the crowd Humanoid or bimanual platforms (Unitree, Fourier, ALOHA/ARX-class rigs) and dexterous hands. XR teleoperation: Quest / PICO / Vision Pro, motion-capture gloves, whole-body retargeting. Imitation-learning data tooling — LeRobot, HDF5/Zarr episode stores, dataset versioning, S3 at TB–PB scale. Built internal dashboards or tooling for a production line or high-throughput lab. Open-source contributions to robotics data or teleoperation tooling. #L1-CC1 Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment. To know more details (Click here) In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
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Location: Philippines; India; Mexico City, Mexico; Mexico; Cairo, Egypt Workplace: remote About the Role We are looking for a detail-oriented QC Reviewer to ensure the quality and consistency of robot manipulation video annotations produced by our annotation team. You'll review labeled video segments against a detailed style guide and reference examples, catch errors or inconsistencies, and provide clear, constructive feedback to annotators. This role is critical to maintaining the accuracy and reliability of training data used for robotics AI models. What You'll Do - Review completed annotations of robot manipulation videos across three levels of labeling detail (atomic motion, skill/subtask, task/goal). - Cross-check annotator descriptions against all three camera views (overhead and both wrist-mounted cameras) to verify accuracy of described actions, object identification, and contact/grasp details. - Verify full coverage of each video — confirm there are no gaps in labeling, including idle or pause moments. - Check that descriptions accurately reflect what actually happened in the video, including failures, drops, or slipped grips — flagging any instances where outcomes were inaccurately described or "smoothed over." - Evaluate annotations for adherence to the style guide: correct vocabulary usage, spatial/directional accuracy, consistent terminology for objects and actions, and appropriate language variation (avoiding repetitive phrasing). - Identify recurring errors or patterns of confusion among annotators and report them to the team lead for calibration purposes. - Provide specific, actionable feedback on rejected or revised annotations, referencing the style guide and reference examples. - Participate in periodic calibration sessions with the team and client to align QC standards with evolving guidelines or edge-case resolutions. - Maintain a QC log or tracking sheet documenting review outcomes, common error types, and annotator performance trends (as required by the project). What We're Looking For Required: - Excellent written English and strong reading comprehension — you'll be evaluating precise, nuanced language choices, not just checking for typos. - Exceptional attention to detail — able to catch subtle mismatches between video content and written description (e.g., a mislabeled grasp type, an incorrect object part, a missed failure event). - Strong grasp of spatial/mechanical description (left/right, above/below, object parts like handles, lids, edges) to verify annotator accuracy. - Ability to apply a detailed, structured style guide consistently and make sound judgment calls in ambiguous or edge-case scenarios. - Comfort giving clear, specific, and constructive feedback to annotators (written feedback, not just pass/fail marks). - Reliable, self-directed work habits, with the ability to work independently while meeting review turnaround expectations. Nice to Have: - Prior experience in a QC, editing, proofreading, or annotation review role. - Experience with video annotation, data labeling, or transcription QA specifically. - Familiarity with robotics terminology (grippers, end-effectors, manipulation). - Experience with annotation tools such as Label Studio, including review/approval workflows. #L1-CC1 Why Join Welo Data? ✨ Limitless Flexibility Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy. 🌱 Limitless Growth Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise. 🌍 Limitless Support Be part of a global contributor community with responsive guidance and support. 💡 Real Impact Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills. How to Apply? Apply now by answering a few quick questions to join our database and become part of our growing community. 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.
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Location: Philippines; India; Cairo, Egypt; Mexico City, Mexico; Mexico Workplace: remote About the Role We are looking for detail-oriented annotators to help label robot manipulation videos for AI training purposes. You'll watch short videos of robots performing manipulation tasks (filmed from three synchronized camera angles) and produce precise, structured, natural-language descriptions of the actions taking place. This work directly supports the development of robotics AI models and requires strong written English, sharp observational skills, and the discipline to follow a detailed style guide consistently. What You'll Do 1. Watch short robot manipulation videos, each filmed from three synchronized camera views (an overhead view and views from each of the robot's two wrist-mounted cameras). 2. Break each video into time segments and write clear, natural-language descriptions for each segment. 3. Apply labels at three levels of detail for each applicable segment: - Atomic motion (a few seconds) — a single small movement (e.g., "close fingers around the red handle") - Skill / subtask (several seconds to ~20 seconds) — a complete, meaningful action (e.g., "pick up the red block by its edge") - Task / goal (up to ~1 minute) — the overall purpose of a sequence of skills (e.g., "place all blocks in the container") 4. Ensure every moment of video is covered by a label at two or more of these levels — no gaps, including idle or pause moments. 5. Accurately describe exactly what happens, including when something doesn't go as planned (a dropped object, a failed grasp, a slipped grip). Precision matters more than making the robot look successful. 6. Cross-reference all three camera angles: use the overhead view to understand the overall scene and object identity, and the close-up wrist views to confirm exact contact and grasp details. 7. Follow a detailed style guide covering vocabulary for actions, spatial relationships, object descriptions, and manner of movement, applying it consistently across many episodes. 8. Participate in periodic calibration sessions to align your labeling with the team and the client's reference examples. What We're Looking For Required: 1. Strong written English — you'll write dozens of short, precise descriptive sentences per video and need to vary your language rather than repeating the same phrases. 2. Sharp attention to detail — able to distinguish small differences (a successful grasp vs. a fumble, a push vs. a drag, which specific object part is being touched). 3. Comfort following a detailed, structured style guide and applying it consistently, even in ambiguous or edge-case scenarios. 4. Basic comfort with spatial/mechanical description (left/right, above/below, naming object parts like handles, lids, or edges). 5. Reliable, self-directed work habits — this is often heads-down work with periodic check-ins rather than close supervision. Nice to Have: 1. Prior experience with video annotation, data labeling, transcription, or QA work. 2. Familiarity with robotics terminology (grippers, end-effectors, manipulation) — helpful but not necessary, as the style guide is self-contained. 3. Experience with annotation tools such as Label Studio. #L1-CC1 Why Join Welo Data? ✨ Limitless Flexibility Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy. 🌱 Limitless Growth Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise. 🌍 Limitless Support Be part of a global contributor community with responsive guidance and support. 💡 Real Impact Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills. How to Apply? Apply now by answering a few quick questions to join our database and become part of our growing community. 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.
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Location: New York, NY Workplace: OnSite 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. ABOUT THE ROLE *Open to candidates based near our NYC office or those willing to relocate. Building general world models — systems that understand and simulate reality across tasks, modalities, and domains — requires closing the loop between learned representations and real-world action. We're looking for a Robotics Engineer to bring our video-native foundation models onto real hardware: deploying world-model-based policies on real robots and making them work in the real world. You will work across the full stack of robot learning — from data collection and task design, to policy deployment, to physical evaluation. This is a hands-on, execution-oriented role at the intersection of foundation models, learned robot policies, and hardware. You'll bring deep robotics domain expertise and help us ship world-model-based robot policies end-to-end, with applications ranging from manipulation to mobile robotics. WHAT YOU’LL DO - Own the deployment loop for learned policies (VLAs, diffusion policies, World Action Models) on real robot arms: inference serving, action decoding, controller integration, latency budgets, and safety limits - Diagnose real-world policy failures — determining whether the problem is data coverage, camera/proprioception mismatch, or execution — and partner with the research team to fix it at the right layer - Design demonstration data collection protocols (task setup, camera placement, teleop conventions) that produce data our world models can actually learn from — working with our existing teleop and lab infrastructure - Partner with research to run controlled experiments connecting world model representations, data composition, and fine-tuning recipes to physical success rates - Define and run physical evaluation protocols so results are trustworthy and comparable across policy iterations - Adapt our policy recipe to partner hardware and new embodiments WHAT YOU’LL NEED - You have personally deployed software on real robot hardware and iterated to make it work — whether learned policies, motion planning, classical control, or perception-driven manipulation. You can walk through a specific system you shipped, what broke on the physical robot that didn't break in sim or testing, and how you fixed it. - Fluency in the software-to-robot interface: action/command spaces, control frequencies, observation pipelines, calibration, and how each affects real-world behavior - Comfort working at the intersection of software and physical systems: you can reconfigure a robot workspace and trace a policy failure in the same afternoon - Bonus: direct experience deploying learned policies (VLAs, diffusion policies) on real hardware; experience with video/multimodal generative models or world models 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
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Location: Santa Clara, CA Workplace: onsite About Welo Data Welo Data, a Welo Global brand, is the multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally. They deliver the human judgment, data infrastructure, and evaluation systems that ensure AI models perform reliably across languages, cultures, and real-world contexts, at every stage from training through deployment. Its global network of 500,000+ vetted experts spans 300+ languages and locales, enabling high-quality multilingual data creation and structured model evaluation across the full spectrum of modern AI applications — from large language models and voice and speech systems to agentic workflows and robotics and embodied AI. This breadth of linguistic, cultural, and domain expertise enables Welo Data to address critical AI development challenges, including safety, bias, inclusivity, and cross-lingual reliability. A unified global operating model, led by specialized program and quality experts and grounded in assessment-driven talent selection, localized rubrics, and continuous calibration, ensures consistent performance across languages, domains, and modalities. Underpinning all of this is NIMO™ (Network Identity Management and Operations), Welo Data's proprietary identity and fraud-prevention framework. Built to maintain data integrity and workforce trust across a global contributor base, NIMO combines advanced verification, continuous monitoring, and structured QA to ensure every dataset is accurate, traceable, and culturally grounded. welodata.ai Role Overview: We're hiring a Robotics Safety & Compliance Lead to own safety, risk, and compliance across our robotics operations — and to lead the function as it scales. This is a builder-leader role: you'll set the standard, establish the frameworks, and grow the program (and eventually the team) that keeps our labs and data collection environments safe, compliant, and audit-ready. You'll be the senior voice on safety in the room with operations, engineering, and EHS — setting direction rather than waiting for it, and building practical frameworks that support both speed and control. What You Will Do Own safety and compliance end to end across robotics labs and data collection environments. Set the safety strategy and roadmap as programs scale across sites, and define what "good" looks like for the function. Develop and implement safety standards, SOPs, and risk mitigation frameworks. Conduct risk assessments across different lab setups (humanoid, teleoperation, motion capture, etc.). Serve as the escalation point and decision-maker on safety risk — including the authority to pause work when conditions require it. Lead incident response processes, reporting, and root cause analysis. Conduct regular audits and maintain audit readiness across sites. Build and lead safety training, onboarding, and a safety champion network across lab teams. Influence senior stakeholders and report on safety posture, risk trends, and program maturity to leadership. Hire, mentor, and grow safety and compliance support as the program expands. Partner with engineering on safe system design — cell layout, e-stops, guarding, interlocks, and operating envelopes. Balance operational speed with safety and compliance requirements. What Good Looks Like Clear, practical safety frameworks that teams actually follow. A safety culture the is owned by the organization, not one that depends on one person policing it. Strong risk awareness without slowing down execution. High audit readiness and clean compliance posture. Proactive identification and mitigation of safety risks. Credibility with engineering — seen as a technical partner, not a gate. Strong partnership with operations and engineering teams. Basic Qualifications 5+ years of experience in safety, compliance, or EHS roles (technical or lab environments preferred). Demonstrated leadership experience — owning a program, leading cross-functional initiatives, or managing/mentoring others. Experience developing and implementing safety programs or frameworks from the ground up. Strong understanding of risk assessment and incident management. Ability to translate standards into practical, operational processes. Clear communication and proven ability to influence senior and technical stakeholders. Familiarity with safety standards (e.g., ISO frameworks such as ISO 10218, ISO/TS 15066, ANSI/RIA R15.06). Preferred Qualifications Experience in robotics, manufacturing, industrial, or lab-based environments. People management experience, or experience building a function and its first hires. Software or technical background as a plus — comfort with ROS, robot control software, teleoperation and motion capture systems, or scripting (e.g. Python) to analyze incident and sensor data. Experience building or automating compliance tooling — audit tracking, incident dashboards, or safety checklists integrated into lab workflows. Experience supporting high-growth or rapidly scaling operations. Background working with cross-functional technical teams. Work Environment and Physical Requirements Onsite lab environment (robotics lab, warehouse, or similar setup). Must be able to stand for extended periods during audits and inspections. Must be able to occasionally lift and/or move up to 50 lbs. Fast-paced environment with evolving operational needs. Why This Role Matters As robotics programs scale, safety and compliance become critical to sustainable operations. This role leads how we operate responsibly, reduce risk, and build systems that scale without compromising safety. Benefits Included in the Offer: - Friendly Working Environment - IT Equipment - Social Activities - Global Mobility Policy - Employee Referral Program - Employee Assistant Program - Medical, Dental, and Vision Insurance - HSA & FSA - 401(k) retirement - Short & Long Term Disability Insurance - Accident, Critical Illness, Hospital Indemnity Insurance - Telemedicine Benefit - Annual Leave - Paid Public Holidays - Maternity/Paternity Leave Hourly Pay: $65-$75/hr. Job Reference: #LI-JC1
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Location: Remote; Seattle, WA; London; New York, NY; San Francisco, CA 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. WHY THIS MATTERS Runway is building AI to simulate the world. We think world models, not language models alone, are the path to general-purpose simulation: systems that experience the world, learn from their mistakes, and change how stories get told, how science gets done, and how the next frontiers of humanity are reached. Applied AI is where that research meets a customer with a deadline. Every one of the world's largest studios, brands, and platforms hits a moment where Runway stops being a demo and becomes the way they actually make things. Our team exists for that moment, and we organize around one question: what's blocking this customer from production, and how do we remove it? ABOUT THE ROLE This is a role for people who want to own a problem, not an account. You'll sit with the biggest studios, brands, and Fortune 100 companies in the world, figure out what's actually standing between them and production, and build whatever removes it. Some weeks that's a workflow. Some weeks it's a plugin or an integration nobody has written yet. Some weeks it's getting a room of executives to make a decision they've been putting off. Your work will be on screen: Emmy-winning shows, Oscar-winning films, Super Bowl commercials, the stuff people actually watch. And the things you build for one customer tend to become product for all of them. Our team's first Shopify plugin started as a customer blocker and was in engineering's hands within a few weeks. We treat this team as R&D for that reason, not as a cost center. We have offices in NYC, San Francisco, Seattle, and London. NO TWO WEEKS ARE THE SAME, BUT YOU CAN EXPECT TO: - Find the real problem: sit with the creative, technical, and executive teams at a customer, map how they actually work, and locate the blocker between them and production. Usually it's one of three things: a missing integration, an unproven pipeline, or a stakeholder who isn't convinced yet. - Build the first of its kind: the demo that shows a studio head or a Fortune 100 CMO something nobody has shown them before. Working proofs of concept on the customer's own brand, footage, or catalog, often built in a day or two before the meeting, and the best of them become product for everyone. - Make it reusable: turn the one-off that unblocked one customer into the workflow, plugin, or integration the next ten customers start from. - Run the evaluation: own evaluation plans end to end, guide managed trials, build tailored demos on the customer's own footage and brand, and carry the technical side of deal cycles with AEs. - Scope deployments that land: 4–12 week engagements with customer-defined success criteria, a hands-on builder and an executive sponsor on their side from day one, and enough discipline to keep them on scope when the asks start piling up. - Get customers to production fast: take new technical and non-technical customers from signed contract to first production call in days rather than quarters, grow API-only accounts into Platform + API, and fix the onboarding so the support tickets stop coming. - Present to anyone: walk an analyst through a pipeline in the morning and a studio head through a production plan in the afternoon. - Bring the field back to the product: embed with Product, Engineering, and Creative to turn what you saw at the customer into roadmap. Every repeat ask is a product requirement, not a patch. - Measure what the customer measures: time to production, usage before and after a project, what they shipped because you were there. We track our own numbers in Salesforce and the warehouse; you'll own yours. WHAT WE VALUE - People who aren't satisfied with surface-level answers and will go into the data, the code, and the room to find the real one - Low ego: the customer's outcome matters more than who gets the credit - Comfort with open-ended problems in unstructured environments, and the instinct to create structure instead of waiting for it - Builders who would rather prototype than debate, and who keep iterating with the customer until it actually works - Adaptive and introspective: willing to learn, guide, lead, and follow WHAT WE NEED - You build things that run in production. Python or TypeScript, APIs, integrations, and data pipelines. Whether you write the code yourself or with coding agents, you can read it, debug it when it breaks, and explain line by line why it's built that way, including to a customer's engineering team. You've shipped something a customer actually ran: a workflow, an integration, a plugin, or an internal tool. - You've deployed AI or ML systems and integrations inside complex organizations and can point to the outcome, not just the delivery - You can hold a room of executives and a room of engineers, and translate between the two. Some of those rooms are at the customer, so expect some travel. - Nice to have: data tooling (SQL, BigQuery, Retool), or experience in media, entertainment, or advertising production 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
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Location: San Francisco, CA; Seattle, WA; New York, NY 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. ABOUT THE ROLE *Open to hiring remote across the US — we also have offices in NYC, San Francisco, and Seattle Strategic Finance is a high-visibility, high-impact role embedded in the decision-making core of the company. You will serve as a crucial partner to our executive, R&D, and GTM teams, owning the financial modeling and analysis that drives our core product and research strategy, optimizes our GTM engine, and informs critical operational decisions. This is a role for someone who has done this inside a fast-growing company before. You bring that operating judgment alongside analytical rigor, strong communication, and the curiosity to thrive at the frontier of generative AI. You’ll work closely with our CFO and Head of Strategic Finance, and partner directly with the executive team and cross-functional leads. WHAT YOU’LL DO - Partner deeply with Product, Research, and Engineering leadership to evaluate the financial ROI and viability of new product lines, features, and R&D investments. - Drive pricing and packaging strategies that maximize market penetration and revenue expansion. - Collaborate with Sales and Marketing leaders to analyze and optimize unit economics (LTV/CAC, payback periods), sales efficiency, pipeline health, and customer retention. - Act as the analytical engine for the executive team by leading cross-functional initiatives to improve operational efficiency, optimize resource allocation, and scale business processes. - Translate operational plans into financial models, identify risks and opportunities, and hold teams accountable to KPIs. - Own the KPI infrastructure that connects product and revenue metrics to financial outcomes, ensuring accuracy, timeliness, and a consistent narrative across all reporting. WHAT YOU’LL NEED - 7+ years of experience, including foundational analyst experience in investment banking or financial services, and high-impact operating experience in Strategic Finance, BizOps, or Corporate Finance at a high-growth technology company. - Experience building and leveraging AI tools for yourself and for cross-functional use. - A track record of operating through rapid scale: building and evolving financial models, planning processes, and reporting as a company’s complexity grows. - Strong fundamentals in financial modeling with a rigorous and quantitative approach to measuring operational success. - Exceptional communication skills with the ability to distill complex financial concepts into simple, digestible narratives for non-financial stakeholders. - You have a high bar for operational excellence and a keen sense of how to translate complex, ambiguous business questions to a clear plan of action. - A genuine interest in AI and its implications for industry and society 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
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