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Location: Singapore About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. About the Role: Cantina is looking for a Member of Technical Staff to join our growing Singapore research team. In this role, you will shape the data and evaluation strategies behind our video generation models. You will own the full data lifecycle—from defining data requirements and annotation standards to building high-quality datasets, evaluating model outputs, and translating findings into actionable recommendations for model improvement. You will work closely with research scientists, machine learning engineers, product teams, and external data partners to strengthen the data–model–evaluation feedback loop. What You’ll Do - Define quality standards for video generation across aesthetics, realism, composition, motion, temporal consistency, instruction following, subject consistency, editing preservation, and text rendering. - Evaluate model iterations, analyze failure patterns, and translate findings into actionable data, training, and prompting strategies. - Own end-to-end training data projects, including sourcing, construction, annotation, captioning, quality control, and delivery. - Develop labeling systems that support dataset segmentation, coverage analysis, quality filtering, training-data mixtures, and model performance attribution. - Design annotation and captioning standards for video generation, editing, and multi-reference tasks. - Create and evaluate synthetic-data workflows based on their stability, usability, quality, and training value. - Develop automated annotation and filtering workflows using vision-language models, system prompts, and quality-scoring models. - Build structured model evaluation processes covering test-set design, evaluation criteria, failure attribution, and reporting. - Establish feedback loops connecting model evaluation and negative-case analysis with data strategy and model iteration. - Train and calibrate annotation teams and external data partners, conduct quality audits, and improve delivery standards. - Partner with research, engineering, product, and creative teams to execute data initiatives and identify future model capabilities. What You’ll Bring - Hands-on experience in data strategy, dataset development, annotation, or model evaluation for generative image, video, or multimodal models. - Experience supporting model development across continued training, supervised fine-tuning, post-training, or evaluation. - Strong understanding of generative media tasks, including image and video generation, multimodal generation, and instruction-based editing. - Experience developing labeling taxonomies, annotation guidelines, captioning standards, quality thresholds, and evaluation frameworks. - Strong visual judgment and the ability to translate subjective quality expectations into measurable data and evaluation standards. - Experience managing large-scale data-production or annotation projects and collaborating with research, engineering, creative, and external partner teams. - Familiarity with automated captioning, synthetic-data generation, vision-language models, prompt design, Python, SQL, or other data and workflow automation tools is a plus. Benefits We Offer: - Competitive salary and generous company equity - Personal time off and paid holidays - Health insurance - Global travel insurance: Covers you when traveling internationally - Monthly spending stipend: $500 (~S$635) - Equipment: All equipment needed for your home office

Location: Singapore About Cantina Cantina Labs develops social AI technologies, including real-time models that enable expressive, lifelike characters. Our work connects advances in video generation and multimodal AI with new ways for people to create, communicate and interact. These capabilities underpin our flagship platform, Cantina, and the broader experiences we are building. About the Role We’re looking for a Visual Data Curation Specialist to join our growing research team in Singapore. You will identify and evaluate image and video sources that support the development of our video generation and multimodal models. This role combines visual expertise, research and analytical judgment. You’ll work closely with researchers and engineers to understand data requirements, translate them into sourcing priorities, and develop a systematic approach to assessing content quality and relevance. You’ll own sourcing and curation projects from initial discovery through review and refinement, helping the team make better decisions about the visual data used in model development. What You’ll Do - Identify and evaluate image and video sources across creator communities, specialist websites, archives and platforms such as YouTube, TikTok, Bilibili, Instagram and Vimeo. - Partner with researchers to translate model development priorities into clear sourcing briefs, selection criteria and content categories. - Assess content across aesthetics, technical quality and research relevance, considering factors such as composition, lighting, resolution, camera movement, subject motion and visual consistency. - Build and maintain a structured source catalogue with representative examples, relevant metadata, quality assessments and clear recommendations. - Identify gaps in coverage across subjects, styles, environments and types of motion, and propose targeted sourcing approaches to address them. - Review sample content with research and engineering colleagues, incorporate feedback and refine selection criteria as requirements evolve. - Document source provenance and available usage information, flagging ownership, licensing or access questions for review. - Develop repeatable curation workflows, tagging systems and quality guidelines, and identify tools that improve the efficiency and consistency of the work. What You’ll Bring - Strong visual judgment and the ability to explain how an image or video meets creative, technical, or research requirements. - A background in film, photography, animation, design, visual arts, media, or a related field, demonstrated through education, professional experience, or a portfolio. Prior experience in machine learning is not required. - Strong research skills, including the ability to investigate unfamiliar topics, assess sources, and turn findings into useful recommendations. - A systematic approach to organizing information and confidence using spreadsheets, databases, or digital asset management tools. - Clear communication, with the ability to translate visual observations into precise feedback for technical colleagues. - The ability to work independently, clarify open-ended requirements, prioritize tasks, and take ownership of work quality. - Curiosity about generative AI and the ability to learn new tools and workflows quickly. Prior machine learning experience is not required. Nice to Have - Hands-on experience in photography, filmmaking, video editing, animation, or other visual production. - Experience in content research, editorial curation, digital asset management, or archive research, including knowledge of visual content communities across platforms and cultures. - Familiarity with dataset curation, annotation, quality assurance, or model evaluation. - Experience with generative image or video tools, basic scripting, SQL, or workflow automation. Benefits We Offer - Competitive salary and generous company equity - Personal time off and paid holidays - Health insurance - Global travel insurance: Covers you when traveling internationally - Monthly spending stipend: $500 (~S$635) - Equipment: All equipment needed for your home office

Location: South Korea; Japan; Philippines; Vietnam; Malaysia; China Workplace: remote 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 represent the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.   OVERVIEW   We are looking for translators with experience in translating patents from English into Portuguese (Brazil)  (native-level fluency of Portuguese) with immediate availability for a patent translation project.   The ideal candidate will have strong experience in translating and proofreading patents, specifically in the field of Computer Science,  Electricity.   Project Details:   Job Title: English to Portuguese (Brazil) Patent Linguist Start Date: ASAP Location: Remote (Asia Region based) Task Type: Translation, Copy Edit Content Type: Computer Science, Electricity Expected Weighted Volume Per Week: +5,000 words CAT Tool:  XTM Employment Type: Freelance Main Duties Translate patent-related content from English into Portuguese(Brazil) , with original meaning conveyed in a manner that is readable and understandable to target audience. Perform translation and copy edit from English (en-US) to Portuguese (pt-BR) for patent. Identify and correct linguistic errors, ensuring consistency in terminology, style, and adherence to client-specific guidelines. Provide detailed feedback to translators and create comprehensive quality reports. Ensure adherence to client-specific style guides, glossaries, and project guidelines. Utilize CAT tools (XTM) to review and assess translations efficiently. Manage weekly capacity to handle +5,000 words per locale and ensure timely task completion. Requirements BS/BA in linguistics, translation, biology, or related fields. 2+ years of work experience in translation, linguistic quality assessment, copywriting, or copy-editing, specifically in patents or technical content. Deep understanding of biological terminology and ability to adapt complex scientific language for target audiences. Proven experience in reviewing or translating patents or technical documents. Proficiency in using CAT tools like XTM for project management and quality assessment. If this sounds like an opportunity you’d like to jump at, please send us your application.   Job Reference: #LI-JC1

Location: United States About the Role Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are seeking an experienced Inpatient Medical Coding Specialist with an active CCS or CIC credential to contribute to a project focused on improving the accuracy and clinical understanding of advanced AI systems. You will review and annotate inpatient medical records, assign and validate ICD-10-CM and ICD-10-PCS codes, determine principal and secondary diagnoses, and verify MS-DRG assignments. You will apply official inpatient coding guidelines, identify documentation gaps, and provide expert feedback on complex coding cases. The ideal candidate has hands-on inpatient coding experience, strong knowledge of UHDDS, POA indicators, CC/MCC classification, and current coding standards, and exceptional attention to detail. Prior AI experience is not required. SENIORITY: Experienced / Specialist LANGUAGE: Strong written and verbal English LOCATION: Remote — United States Key Responsibilities Annotate and review inpatient medical records, including admission notes, progress notes, operative reports, consultations, laboratory and imaging results, and discharge summaries. Assign accurate ICD-10-CM and ICD-10-PCS codes based on clinical documentation and applicable coding guidelines. Identify principal and secondary diagnoses and sequence codes according to official inpatient coding conventions. Assign Present on Admission (POA) indicators and validate MS-DRG assignments, including the identification of Complications or Comorbidities (CCs) and Major Complications or Comorbidities (MCCs). Apply UHDDS definitions, ICD-10-CM/PCS Official Guidelines for Coding and Reporting, and relevant AHA Coding Clinic guidance. Identify hospital-acquired conditions (HACs), patient safety indicators, and documentation inconsistencies where applicable. Collaborate with project stakeholders to clarify coding requirements, resolve documentation ambiguities, and maintain data integrity. Provide structured feedback on coding guidelines, complex cases, and recurring errors to support workflow improvements and AI model training. Ensure all coding annotations are accurate, complete, consistent, and aligned with current coding standards. Requirements Active AHIMA Certified Coding Specialist (CCS) or AAPC Certified Inpatient Coder (CIC) credential. Hands-on experience with inpatient medical coding. Strong knowledge of ICD-10-CM, ICD-10-PCS, and MS-DRG methodology. Understanding of principal diagnosis selection, secondary diagnosis reporting, code sequencing, POA indicators, CC/MCC classification, and applicable inpatient coding guidelines. Experience reviewing clinical documentation and resolving complex coding challenges. Strong written and verbal communication skills. Excellent attention to detail and the ability to apply coding rules consistently. Access to current ICD-10-CM/PCS code sets, official coding guidelines, and appropriate MS-DRG grouper tools.

Location: Serbia; Spain Social Discovery Group (SDG) is a group of social discovery companies. SDG solves the problems of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG’s products redefine the way people interact and connect with one another. Our portfolio includes social entertainment platforms designed to connect people online across different cultures and regions of the world. We bring together a team of like-minded people and IT professionals who specialize in creating and developing globally impactful social discovery products. Our international team of digital nomads works remotely from all over the world. We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025). We are looking for Machine Learning Engineer. Your main tasks will be: Set the ML direction: choose which strategic bets to make and tie each one to clear business needs. Drive LLM post-training and model adaptation end to end, from dataset construction to fine-tuning and preference optimization. Design and build agent harnesses and tool-using LLM systems. Shape multi-agent development workflows that make the team faster and more effective. Build evaluation frameworks and LLM-as-a-judge systems that reliably predict real-world performance. Improve dialogue quality across memory, emotional intelligence, persona consistency, safety and anti-loop behavior. Ship production systems that directly shape user experience, retention and monetization. We expect from you: Python expert level: clean code, typing, async, multiprocessing, profiling, debugging, notebooks + production code.Trainsformers. Training and fine-tuning LLMs. SFT, LoRA/QLoRA, PEFT. Preference optimization: DPO / ORPO / SimPO / CPO / GRPO or willingness to quickly go deep. Building datasets for LLM training: cleaning, filtering, deduplication, preference pairs, synthetic data, hard negative mining. LLM evaluation: offline evals, pairwise evals, LLM judges, human annotation. Agent harness design: tool calling, function calling, structured outputs, retries, routing, state management, memory/context, guardrails. Production LLM integration: APIs, streaming, batching, fallbacks, cost/latency trade-offs. Observability for agents: traces, tool-call logs, transcript analysis, failure clustering. Strong understanding of transformer architecture and modern LLM behavior. Accuracy with dtype/device/batching: fp32/fp16/bf16, quantization, CUDA memory, avoiding dtype mismatch bugs. Git, Docker, Linux, basic MLOps. Fluent Russian, ready to work in CET (±2) hours. Nice to have: experience beyond text (computer vision, image generation, multimodal), long-running conversations and character consistency, vLLM / TGI / SGLang, DeepSpeed / FSDP / Accelerate, quantization, safety classifiers. What do we offer: REMOTE OPPORTUNITY to work full-time; The initial pay level or pay range for this role will be shared with candidates during the recruitment process and before the commencement of employment; Vacation 28 calendar days per year; 7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave; Bonuses up to $5000 for recommending successful applicants for positions in the company; 50% payment for professional training, international conferences, and meetings; Corporate discount for English lessons; ​ Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); ​ Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years; Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now!

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done. ABOUT THE ROLE We’re looking for an Engineering Manager to lead the team building LangSmith, our observability and evaluation platform for LLM applications. You’ll define the technical direction, grow and mentor a world-class engineering team, and partner with product and design to deliver features that help developers build and deploy trustworthy AI systems with confidence. WHAT YOU'LL DO - Build, mentor, and grow a high-performing team of engineers, fostering collaboration, ownership, and accountability - Strengthen LangChain’s engineering culture through mentorship, high-quality code, and technical excellence - Shape long-term technical direction and ensure scalability and reliability of LangSmith AI Observability Platform - Partner with product and design teams to define scope, sequence, and success criteria for key initiatives - Maintain a high bar for technical excellence while making sure the team moves with urgency and focus - Lead by example in writing clean, maintainable, and well-tested code in Go/Python and Typescript - Engage directly with customers to understand their needs and translate them into actionable product improvements WHAT YOU'LL BRING - Experience managing or tech-leading teams delivering complex full-stack products - Strong technical background in Go/Python and React/Typescript - Solid understanding of databases (Postgres, Redis and ClickHouse) - Proven ability to design high throughput data-intensive systems - Bias towards shipping quickly and learning from customers - Strong communication skills—able to collaborate with internal stakeholders and engage directly with customers - Bonus: Experience building AI/LLM-powered applications, developer tools, or observability platforms - Annual salary range: $200,000- $250,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: United Kingdom; India; Germany; United States About Huzzle Labs Huzzle Labs partners with frontier AI labs to evaluate and improve frontier models through deep human expertise. Contributors directly assess advanced AI systems in their specialist fields, receive competitive compensation, and help define the standards used to measure model performance. About the Role Huzzle Labs is seeking experienced accountants to write realistic accounting tasks that test how well frontier AI systems handle accounting work. You will create prompts that are difficult enough for a frontier model to fail, then write a scoring rubric for each task so reviewers can assess the output consistently. A rubric is a list of objective, checkable criteria that a reviewer marks pass or fail. Your judgement helps define the standards used to measure model performance. This is an expert judgement role focused on realistic task design, careful review of model output and precise, consistent documentation. Training is provided. Prior AI training or data-annotation experience is required. Responsibilities Write realistic accounting tasks: Create requests of the kind a client, controller or business owner would send, covering month-end close, bank and credit card reconciliations, AR/AP ageing, accruals and adjusting entries, sales tax, job costing and the clean-up of incomplete or inconsistent books. Build from real material: Review a deal room containing hundreds of files, select the relevant documents and use them to develop prompts and rubrics for tasks a frontier model struggles to complete correctly. Require usable deliverables: Each request should call for a working output, usually a spreadsheet, a journal entry schedule or a short memo. Test against a frontier model: Run each request and review the output with the care you would apply when signing off accounting work. Where the model succeeds, increase the difficulty until a genuine gap appears. Write scoring rubrics: Define objective criteria that another reviewer can apply without repeating your work, for example, “the reconciled ending balance equals $X” and “the $X deposit is recorded as a customer deposit liability, not revenue.” Apply guidelines consistently: Follow the task and rubric guidelines, flag ambiguous cases and help refine the criteria. Requirements At least 5 years in accounting, bookkeeping or finance operations. Prior AI training or data-annotation experience is required. Hands-on knowledge of month-end close, reconciliations, AR/AP, accruals and adjusting entries, sales tax and job costing. Excellent written English and precision with numbers. Careful and detail-oriented: accurate figures and objective, checkable criteria. Available 20 to 40 hours per week for an initial one-week trial, with potential extension. Example Assignment For a client deal room covering a small business with incomplete and inconsistent books, you would: Review the files and select the relevant documents, such as bank statements, ledgers, invoices and ageing reports. Write a prompt as the business owner or controller would, asking for a reconciliation and the adjusting entries needed to close the month. Run the prompt against a frontier AI model and check the spreadsheet or journal entry schedule line by line. If the model completes the task correctly, increase the difficulty, for example, by adding a customer deposit, a timing difference or a sales tax complication, until it fails. Write the rubric, such as “the reconciled ending balance equals $X” and “the $X deposit is recorded as a customer deposit liability, not revenue,” so another reviewer can grade any answer without repeating the work. Confidentiality An NDA must be signed before the engagement begins. Benefits Compensation: $60 - $90 USD / hour

Location: Paris ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE This is a chance to build the frontier LLM evals that shape the next generations of flagship models. Could a model design a computer chip, or find the backdoor an attacker left in a network? Public benchmarks can't tell us, as they're generally not a good measure of real work. As an Evaluation Engineer, you'll own evals from start to finish. You'll run workshops with customers, industry experts and our customer-facing teams to understand their most important industry use cases (e.g., an engineer updating a part in CAD software), and help decide which are worth building first. You'll also look beyond today's use cases and design moonshot evals for work no model can do yet, so Mistral gets there first. Then you'll turn each one into a benchmark, often one where an agent has to do the work inside real software. You'll source the data, decide how to score it, and run it on every new Mistral model and on competitor models. When our models fall short, you'll work with the post-training teams to close the gap. When they catch up, you'll make the eval harder. You'll write up and present your results so senior leaders can act on them. They also give our go-to-market teams evidence of where Mistral leads. You'll learn new fields quickly. One month you might be learning how chip designers check their work, and the next how a bank investigates a flagged payment. The team is new and fast-paced, and you'll have a lot of autonomy. You'll spend a lot of time speaking with people across Mistral to work out what matters most, then decide what to build. WHAT YOU WILL DO - Run discovery with customers, industry experts and teams across Mistral, then help decide which use cases are worth building first. - Design new benchmarks for industry use cases and frontier capabilities, including how they're scored. - Build evals where agents work inside real software (e.g., CAD and simulation tools), and run them on our models with checks that the results stay reliable over time. - Stress-test existing evals to find flaws and bugs before we rely on them. - Source data with expert vendors. Where customer data can't leave the customer, build realistic proxy or synthetic data instead. - Write up and present what you find so leaders across Mistral can act on it. - Help other teams build their own evals, with tools and guides they can reuse. WHAT WE'RE LOOKING FOR EXPERIENCE - 2+ years of industry experience (e.g., in software, AI, or consulting), or a PhD. - A software engineering or research background, with experience writing code that others can build on. - Experience working directly with customers, industry experts, or other teams (e.g., through consulting, solutions engineering, or research collaborations). - Experience building something with LLMs. - Comfort working with large datasets, including building and cleaning them. TECHNICAL - Strong Python skills. - Comfortable working in a large, shared codebase and getting your code through reviews by other teams. - A strong understanding of LLM training, inference, and evaluation. COMMUNICATION - You enjoy speaking with people and are good at it. - You write clearly. A short doc or deck from you is enough for a busy leader to make a decision. - Confident presenting to both technical and non-technical audiences. - Fluent in English. HOW YOU WORK - High energy, and you don't need a roadmap. You move independently and handle uncertainty with confidence. - Proactive and high-agency. You spot what needs doing and get it done. - You make good decisions about what to build first and can explain why. - Low-ego, collaborative, and eager to learn. - Curious, with a track record of learning things outside your work or studies. You can get to grips with a new field in a few weeks. NICE TO HAVE - Experience building AI evaluations, especially for industry applications. - Published research on evals or contributions to open-source evaluation frameworks. - Experience building datasets, generating synthetic data, developing labelling guidelines, or working with annotation vendors. - A background in an industry outside software (e.g., engineering, finance, or science). WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

проектировать, запускать и поддерживать процессы сбора, обработки, разметки и валидации данных; формулировать требования к датасетам совместно с командами Computer Vision, NLP и AI;

Location: Gurgaon, India Workplace: remote 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    About the Team  Welo Data's Trust & Safety function protects the integrity of a global, distributed workforce that powers AI data and annotation work. We run a multi-layered fraud detection stack combining identity verification checks, in-house behavioral signals, and platform activity data, and are actively building out a Trust & Safety Committee spanning four core workstreams: identity verification, location verification, account integrity, and multi-accounting detection. This is a hands-on investigative role, not a policy-only seat — you'll be working live cases from day one.  About the Role  We're looking for a Trust & Safety Specialist, based in India, to join our investigations team, working active fraud cases and supporting the broader fraud strategy program. You'll come in with real T&S, fraud/risk, or identity-verification experience from another platform, marketplace, gaming company, fintech, IDV vendor, or crowdsourced-workforce environment, and be ready to run investigations, process removals, and spot fraud patterns from week one. What You Will Do Run investigations end-to-end: triage flagged accounts, review evidence (identity signals, behavioral flags, platform activity data), reach a disposition, and process removals in line with policy and SLA. Own IDV review: verify identity and location signals for flagged or high-risk accounts, distinguishing genuine edge cases from fraud. Conduct manual audits and reviews: prioritizing cases by risk and signal strength rather than intake order. Detect multi-accounting and account integrity abuse: recognize patterns across linked accounts, device/location overlap, and behavioral signals. Apply a hypothesis-driven investigation method: form a hypothesis, test it against the evidence, and reach a disposition that can be replicated and audited. Contribute to detection improvement: escalate emerging fraud vectors, false-positive/false-negative patterns, and rule gaps to the fraud strategy team. Handle sensitive data responsibly: apply GDPR-aligned data handling and deletion practices in every case. Collaborate cross-functionally: partner with Research Labs, Quality Strategy Architecture (QSA), and Forward Deployment Engineering on tooling gaps and process fixes surfaced by your casework What You Bring (Must Have-s) 4+ years in a T&S, fraud/risk, or identity-verification investigations role — from a platform/marketplace T&S team, a fintech/payments risk team, an identity-verification vendor, or a crowdsourced/gig-workforce trust function. Direct experience with identity/fraud signals — device fingerprinting, IP/geolocation checks, document verification, or behavioral fraud scoring. Multi-accounting / account integrity pattern recognition — you've dealt with linked-account abuse, farming, or account sharing before, not just single-account review. Case documentation discipline — you write clean, evidence-backed case notes that would survive an audit or an appeal. Comfort with ambiguity and volume — you can prioritize a queue by risk, not just clear it by count. Working knowledge of data privacy obligations (GDPR or equivalent) as they apply to case handling and data retention/deletion. Nice to Have Experience specifically in AI/ML data annotation, RLHF, or research operations workforce platforms. Exposure to rule-based fraud detection engines and an opinion on rule sprawl vs. signal quality. Familiarity with clustering/anomaly-detection approaches to fraud (even at a conceptual level). Case management system experience (any ticketing or knowledge-base tooling). Recommended Education Bachelor's degree in Criminology, Law, Criminal Justice, Cybersecurity, Information Security, Data/Computer Science, or a related field. Equivalent practical experience in T&S, fraud investigations, or identity verification will be considered in place of a degree. Relevant certifications are a plus: CFE (Certified Fraud Examiner), CAMS (Certified Anti-Money Laundering Specialist), or IDV/identity risk vendor certifications.

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.

Location: United States; Canada Workplace: OnSite WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities - Build and maintain data pipelines for SFT, preference, and RL post-training data. - Own dataset quality, versioning, and reproducibility. - Turn research data recipes into production-grade, reusable components. - Scale model inference for data generation and model-based grading. - Design data formats and schemas that keep post-training datasets consistent and efficient to train on. - Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications - Strong software engineering skills. - Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. - Track record of running distributed data processing and model inference at scale. - Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour. - Excellent communication skills. This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Remote Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy. - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE Productions is the “done for you” managed services wing of ElevenLabs, built for creators and media businesses. We bring together our AI audio tools and human experts in linguistics, mixing and post-production to deliver human-edited dubs, audiobooks and more in 15+ languages, directly on the ElevenLabs platform. Our customers include global media broadcasters, publishers, gaming companies and major film studios. We’re hiring engineers to build the systems behind it: the platforms that let human expertise and AI work together at the quality our clients expect, and the labelling tools our research teams use to improve our models. You’ll own a scope in one of these areas: - Human data platform: the labelling and evaluation platform research uses to continuously improve our models. You’ll ship new task editors, improve reliability, catch misuse and build the metrics behind higher-quality data pipelines. - Core productions engine: the backend machine nobody sees but everybody relies on. You’ll build and maintain the services that run our production workflows, with room to lead projects. - Editor platform: the professional editing tools our production teams work in. You’ll build in Rust, combining UI systems with a deep understanding of the underlying system. We’re building professional tools and core infrastructure, not consumer features. The work is mostly building, with little hand-holding. You’ll carve out your own scope and own the outcome. Requirements - Strong backend engineering experience, ideally in functional programming languages like Rust, with a full-stack focus on designing UI systems. You’ve shipped and run production systems end to end. - Experience making systems reliable and scalable, such as internal platforms, workflow or task engines, or data pipelines. You take pride in the infrastructure nobody sees but everybody relies on. - Comfortable switching between building a new tool or editor and hardening the platform underneath it, and keen to lead projects when the opportunity arises. - Opinionated and able to defend your ideas, but know when to just grind. You’re happy doing the unglamorous work, and you’re hungry. Bonus: - Experience building editor or UI-heavy professional tools, with a systems-level understanding of what sits underneath. - Experience with data labelling or annotation platforms, or managing crowdsourced workforces. Location This role is remote-first, so it can be executed from anywhere in Europe and the US East Coast, with the ability to operate in GMT-5 to GMT+1 timezones required. If you prefer, you can work from our offices in London, New York, Dublin, Amsterdam, and Warsaw. #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Location: California; Sunnyvale, CA; San Francisco, CA; Seattle, WA; Redmond, Washington; Burlingame, CA; New York City Metropolitan Area; Los Angeles, CA; Washington, D.C.; Boston, MA Workplace: onsite Overview Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems. This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs. While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale. We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.  Project Details Job Title: Data Labeling Analyst (Speech & Voice AI)  Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent)  Hours: Full-time, 40 hours per week Employment Type: W2 Full-Time Employee Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship) Hourly Pay Rate: $28/hour Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Los Angeles, Washington DC, Boston. Please only apply if you meet this location requirement. What You’ll Do Execute high-volume data labeling and annotation tasks across speech and voice datasets Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale Work with audio and language data, including transcription, categorization, and tagging Maintain strong throughput while meeting quality expectations Escalate unclear or ambiguous cases appropriately Adapt to evolving guidelines and workflows as systems and requirements change Support baseline data production needs for AI training pipelines Contribute to team calibrations and quality alignment sessions What We’re Looking For Native-level fluency in Spanish (Mexico) Strong written communication skills and language fundamentals 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field. Ability to follow detailed instructions and apply guidelines consistently High attention to detail and ability to maintain accuracy in repetitive tasks Comfort working in structured, process-driven environments Ability to manage time effectively and maintain steady output Willingness to ask questions and escalate when needed Basic familiarity with AI, speech technology, or language data is a plus Benefits Paid Vacation: 6 days Paid Company Holidays: 2 days (Memorial Day and Labor Day) Paid Sick Leave: accrued per applicable state law and company policy Medical, Dental, and Vision Insurance (eligibility applies) Health Savings Account (HSA) 401(k) Retirement Plan Employee Assistance Program Additional voluntary benefits (life, accident, critical illness, etc.) Onsite Perks (where applicable): Free breakfast, lunch, and dinner Stocked micro-kitchens with snacks and beverages Commuter benefits, including shuttles and bike-to-work options Unique campus features depending on location 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. Why This Role This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users. It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.

Location: California; Sunnyvale, CA; San Francisco, CA; Seattle, WA; Redmond, Washington; Burlingame, CA; New York City Metropolitan Area; Los Angeles, CA; Washington, D.C.; Boston, MA Workplace: onsite Overview Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems. This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs. While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale. We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.  Project Details Job Title: Data Labeling Analyst (Speech & Voice AI)  Hiring in: Onsite (Bay Area, NYC, or client-dependent)  Hours: Full-time, 40 hours per week Employment Type: W2 Full-Time Employee Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship) Hourly Pay Rate: $28/hour Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Bellevue, Redmond, Seattle, San Francisco, Sunnyvale, Burlingame, Los Angeles, Washington DC, Boston. Please only apply if you meet this location requirement. What You’ll Do Execute high-volume data labeling and annotation tasks across speech and voice datasets Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale Work with audio and language data, including transcription, categorization, and tagging Maintain strong throughput while meeting quality expectations Escalate unclear or ambiguous cases appropriately Adapt to evolving guidelines and workflows as systems and requirements change Support baseline data production needs for AI training pipelines Contribute to team calibrations and quality alignment sessions What We’re Looking For Native-level fluency in Spanish (Spain) Strong written communication skills and language fundamentals 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field. Ability to follow detailed instructions and apply guidelines consistently High attention to detail and ability to maintain accuracy in repetitive tasks Comfort working in structured, process-driven environments Ability to manage time effectively and maintain steady output Willingness to ask questions and escalate when needed Basic familiarity with AI, speech technology, or language data is a plus Benefits Paid Vacation: 6 days Paid Company Holidays: 2 days (Memorial Day and Labor Day) Paid Sick Leave: accrued per applicable state law and company policy Medical, Dental, and Vision Insurance (eligibility applies) Health Savings Account (HSA) 401(k) Retirement Plan Employee Assistance Program Additional voluntary benefits (life, accident, critical illness, etc.) Onsite Perks (where applicable): Free breakfast, lunch, and dinner Stocked micro-kitchens with snacks and beverages Commuter benefits, including shuttles and bike-to-work options Unique campus features depending on location 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. Why This Role This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users. It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.

Location: California; Sunnyvale, CA; San Francisco, CA; Seattle, WA; Redmond, Washington; Burlingame, CA; New York City Metropolitan Area; Los Angeles, CA; Washington, D.C.; Boston, MA Workplace: onsite Overview Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems. This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs. While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale. We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.  Project Details Job Title: Data Labeling Analyst (Speech & Voice AI)  Hiring in: Onsite (Bay Area, NYC, or client-dependent)  Hours: Full-time, 40 hours per week Employment Type: W2 Full-Time Employee Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship) Hourly Pay Rate: $28/hour Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC,  Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Los Angeles, Washington DC, Boston. Please only apply if you meet this location requirement. What You’ll Do Execute high-volume data labeling and annotation tasks across speech and voice datasets Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale Work with audio and language data, including transcription, categorization, and tagging Maintain strong throughput while meeting quality expectations Escalate unclear or ambiguous cases appropriately Adapt to evolving guidelines and workflows as systems and requirements change Support baseline data production needs for AI training pipelines Contribute to team calibrations and quality alignment sessions What We’re Looking For Native-level fluency in English (UK) Strong written communication skills and language fundamentals 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent academic qualification in a related field. Ability to follow detailed instructions and apply guidelines consistently High attention to detail and ability to maintain accuracy in repetitive tasks Comfort working in structured, process-driven environments Ability to manage time effectively and maintain steady output Willingness to ask questions and escalate when needed Basic familiarity with AI, speech technology, or language data is a plus Benefits Paid Vacation: 6 days Paid Company Holidays: 2 days (Memorial Day and Labor Day) Paid Sick Leave: accrued per applicable state law and company policy Medical, Dental, and Vision Insurance (eligibility applies) Health Savings Account (HSA) 401(k) Retirement Plan Employee Assistance Program Additional voluntary benefits (life, accident, critical illness, etc.) Onsite Perks (where applicable): Free breakfast, lunch, and dinner Stocked micro-kitchens with snacks and beverages Commuter benefits, including shuttles and bike-to-work options Unique campus features depending on location 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. Why This Role This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users. It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.

Location: Mexico Workplace: remote 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    About the Team  Welo Data's Trust & Safety function protects the integrity of a global, distributed workforce that powers AI data and annotation work. We run a multi-layered fraud detection stack combining identity verification checks, in-house behavioral signals, and platform activity data, and are actively building out a Trust & Safety Committee spanning four core workstreams: identity verification, location verification, account integrity, and multi-accounting detection. This is a hands-on investigative role, not a policy-only seat — you'll be working live cases from day one.  About the Role  We're looking for a Trust & Safety Specialist, based in Mexico, to join our investigations team, working active fraud cases and supporting the broader fraud strategy program. You'll come in with real T&S, fraud/risk, or identity-verification experience from another platform, marketplace, gaming company, fintech, IDV vendor, or crowdsourced-workforce environment, and be ready to run investigations, process removals, and spot fraud patterns from week one. What You Will Do Run investigations end-to-end: triage flagged accounts, review evidence (identity signals, behavioral flags, platform activity data), reach a disposition, and process removals in line with policy and SLA. Own IDV review: verify identity and location signals for flagged or high-risk accounts, distinguishing genuine edge cases from fraud. Conduct manual audits and reviews: prioritizing cases by risk and signal strength rather than intake order. Detect multi-accounting and account integrity abuse: recognize patterns across linked accounts, device/location overlap, and behavioral signals. Apply a hypothesis-driven investigation method: form a hypothesis, test it against the evidence, and reach a disposition that can be replicated and audited. Contribute to detection improvement: escalate emerging fraud vectors, false-positive/false-negative patterns, and rule gaps to the fraud strategy team. Handle sensitive data responsibly: apply GDPR-aligned data handling and deletion practices in every case. Collaborate cross-functionally: partner with Research Labs, Quality Strategy Architecture (QSA), and Forward Deployment Engineering on tooling gaps and process fixes surfaced by your casework What You Bring (Must Have-s) 5+ years in a T&S, fraud/risk, or identity-verification investigations role — from a platform/marketplace T&S team, a fintech/payments risk team, an identity-verification vendor, or a crowdsourced/gig-workforce trust function. Direct experience with identity/fraud signals — device fingerprinting, IP/geolocation checks, document verification, or behavioral fraud scoring. Multi-accounting / account integrity pattern recognition — you've dealt with linked-account abuse, farming, or account sharing before, not just single-account review. Case documentation discipline — you write clean, evidence-backed case notes that would survive an audit or an appeal. Comfort with ambiguity and volume — you can prioritize a queue by risk, not just clear it by count. Working knowledge of data privacy obligations (GDPR or equivalent) as they apply to case handling and data retention/deletion. Nice to Have Experience specifically in AI/ML data annotation, RLHF, or research operations workforce platforms. Exposure to rule-based fraud detection engines and an opinion on rule sprawl vs. signal quality. Familiarity with clustering/anomaly-detection approaches to fraud (even at a conceptual level). Case management system experience (any ticketing or knowledge-base tooling). Recommended Education Bachelor's degree in Criminology, Law, Criminal Justice, Cybersecurity, Information Security, Data/Computer Science, or a related field. Equivalent practical experience in T&S, fraud investigations, or identity verification will be considered in place of a degree. Relevant certifications are a plus: CFE (Certified Fraud Examiner), CAMS (Certified Anti-Money Laundering Specialist), or IDV/identity risk vendor certifications.

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done.   ABOUT THE ROLE We are looking for a Senior Backend Engineer to join us. In this role you will be building the backend systems that power LangChain’s observability and evals platform. You will work on the core services that allow developers to monitor and evaluate their AI applications at scale. While the focus is on backend feature development, familiarity with fullstack or frontend engineering, performance tuning, and debugging production issues would be extremely valuable.   WHAT YOU'LL DO - Design, develop, and maintain backend services and APIs to support LangSmith’s tracing, monitoring, and evaluation workflows. - Collaborate on architectural decisions to ensure systems are performant and maintainable. - Optimize storage and query performance for high-volume observability and evaluation data. - Ensure system reliability through strong testing, monitoring, and alerting practices. - Troubleshoot and resolve production issues, performing root-cause analysis and implementing long-term fixes. - Create and maintain technical documentation, including system design and API references. - Work closely with full-stack engineers, product managers, and product designers on rolling out new features.   WHAT YOU'LL BRING - 5+ years of professional experience in backend engineering working on highly complex products - Proficiency in one or more backend languages/frameworks, ideally Python or Go - Strong understanding of API design and building reliable data services. - Experience with high-throughput or mission-critical systems. - Demonstrated ability to optimize backend services for performance and reliability. - Experience with database systems (Postgres, Redis, Clickhouse), and cloud platforms (AWS, GCP, Azure) - Strong communication skills, with the ability to collaborate cross-functionally - Customer centricity and ownership mentality   Compensation Annual salary range: $180,000- $240,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.