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Location: Poland Workplace: remote OVERVIEW   Are you tech-savvy? Have a passion for quality? We are looking for Data Raters to work on projects aimed at advancing AI technologies. Join us for a unique chance to kickstart your career in the AI field!   This project is an excellent starting point for entry-level candidates. We offer comprehensive learning support, making it a great opportunity to gain experience in data annotation and data rating within the AI field—an industry currently in high demand for skilled specialists, especially those with expertise in localization and linguistic proficiency.   MAIN DUTIES   - Follow project-specific guidelines to conduct research on e-commerce data. - Evaluate the usefulness of product filters and results based on the research. - Rate the e-commerce data according to the guidelines provided.   Project Details   Start Date: Immediately after completing the qualification process Duration: Ongoing Schedule: This is a freelance opportunity; the workload is based on project needs. Weekly hours may vary. Employment Type: Freelance/Independent Contract Location: Remote Language: Polish Pay Rate: $8.75/hour - Based on tasks completed   By applying, you'll become part of our Freelance community, opening doors to a range of projects tailored to your skills and availability, particularly highlighting localization and linguistic expertise.   Payment rates for future projects may vary, ensuring fair compensation that reflects your location, industry, and skill set.   Joining us means contributing to our current project and becoming part of our dynamic network.   This is a unique chance to enhance global user experiences and apply your language skills in meaningful ways. Requirements Fully Proficient in Polish Linguistic competency in English equal to the following: ILR Level 5 or CEF C2 Must be located in Poland Web-savvy and able to work in a fast-paced environment Preferably previous experience in Search Relevance tasks, experience with e-commerce searches/websites Excellent online research skills Attention to detail Performing enough research during the allocated time, working within short throughputs Reliable computer system and internet connection Ability to follow instructions in English and comply with the project conventions and rules expected by the client Must sign a Non-Disclosure Agreement to protect client confidentiality Must pass training and a required quality test before starting work When you join Welocalize, you have the opportunity to bring your career to the next level: ... receive steady volume of work and long-term partnership {where this applies}  ... professional development: work on exciting projects that will empower you keep learning and growing ... work with multicultural, international team with a great variety of documents and content types   ... 24-hour 6-day a week support from our Community team.   If this opportunity sounds appealing to you, apply below.    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

Location: New York, NY, United States About Us Fanatics is a leading global sports platform redefining how fans connect with the teams, players and moments they love. Our businesses — Fanatics Commerce, Fanatics Collectibles, Fanatics Betting & Gaming, Fanatics Events, Fanatics Advertising, Fanatics Markets and Fanatics Studios — maximize the presence and reach for hundreds of partners globally and create a one-stop experience that allows fans to buy, bet, collect, and earn, while engaging with sports in deeper, more immersive ways. This includes licensed fan gear and lifestyle products, sportsbook and iGaming, physical and digital trading cards, live events, premium sports entertainment content, credit card offerings and more. Together, they form a powerful, integrated ecosystem — connected by the Fanatics ONE loyalty program and FanCash, the currency of sport — delivering personalized experiences to over 100 million fans worldwide. Fanatics holds partnerships with over 900 sports properties, from professional leagues and players’ associations to teams, colleges and retail partners; over 7,000 athletes and celebrities; and over 2,000 retail locations, including all Lids stores. Backed by a team of more than 22,000 employees, Fanatics is committed to relentlessly enhancing the fan experience. About the Team Fanatics Core is the engineering organization building the shared capabilities, including search, AI, and customer intelligence, that every product across the Fanatics ecosystem builds on. We are seeking an Engineering Manager to lead the team that owns Search and Consumer AI. This leader will own some of the most leveraged surfaces we build: how fans find what they’re looking for, how AI shows up inside our apps, and how AI powers an excellent customer experience. You will lead a team of software engineers spanning two closely connected charters: Consumer AI: customer support AI, including LLM-powered assistants, conversational analytics, sentiment analysis, predictive troubleshooting, and the tooling that lets customer success teams act on AI-generated insights; and (2) embedded AI experiences in the fan journey, such as AI commentary, recommendations, summaries, and in-app assistance. Search: native search, including query understanding, relevance and ranking, autocomplete, and personalization; and (2) AI search, including natural-language and conversational search that lets fans ask for what they want in their own words and get answers, not just results. Success in this role requires strong partnership with Product, Data Science, Customer Operations, and product teams across the ecosystem to shape the roadmap, make smart trade-offs, and deliver outcomes fans feel. You’ll work on complex, high-scale challenges as part of a team that values innovation, collaboration, and excellence. Responsibilities Delivery & Ownership Lead the team to deliver against commitments across Search and Consumer AI, owning delivery plans end to end: scope and sequence work, remove blockers, and manage risk. Set a high bar for reliability, performance, and relevance quality, with observability in place for AI and search services. Ensure the team’s work meets Fanatics standards for data governance, security, compliance, and responsible AI. Own on-call, incident response, and operational health for the team’s systems. Strategy & Roadmap Partner with Product and engineering leadership on planning and roadmap building, using technical insight and fan impact to influence priorities. Connect day-to-day execution to team strategy and Fanatics business goals so engineers understand why their work matters. Partner with product teams across the ecosystem to embed AI experiences into their surfaces, agreeing on shared ownership, interfaces, and quality bars. Guide how LLMs and ML models are evaluated, integrated, and rolled out in production. Communication & Collaboration Coordinate across engineers, adjacent teams, and cross-functional partners to drive end-to-end delivery. Represent the team’s plans, progress, and risks in planning and review forums. Keep the team informed on goals, trade-offs, and decisions, and create space for two-way feedback. People & Ways of Working Hire, onboard, and grow a high-performing team; give candid, timely feedback and invite the same. Mentor engineers on craft, ownership, and collaboration, and support their career growth. Build team processes (planning, reviews, retros, experimentation) that help the team learn fast and ship reliably. Must be open to occasional travel to Fanatics offices and other locations for conferences, events, meetings, and team building. Qualifications We value aptitude over experience, but here are some key skills that will make you successful on this team: 1-3+ years managing a software engineering team, or significant tech-lead experience with people-leadership responsibilities, delivering complex, high-scale systems. Experience in a Java / AWS ecosystem; familiarity with AWS Bedrock or equivalent managed AI services preferred. Experience shipping consumer-facing AI/ML or NLP features to production, including integrating LLMs and building the pipelines and evaluation practices that keep them reliable. Strong understanding of search, discovery, or relevance systems, including how traditional search and LLM-based approaches complement each other. Strong technical judgment and clear, confident communication with engineers, Product partners, and leadership. Proven ability to mentor engineers and build a healthy, high-performing team culture. Preferred Background in customer support AI or embedded consumer AI experiences (assistants, conversational analytics, AI commentary, recommendations). Familiarity with Kafka, Airflow, dbt, OpenSearch, Kotlin, and Salesforce. Experience building shared platforms consumed by multiple product teams. Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE—a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process. For information about our benefits, please visit https://benefitsatfanatics.com/ #LI-VG1 Ranges will change based on country and state of residence, which are reflected in Geographical Zones defined by Fanatics Betting and Gaming. The range incorporates all of our Geographical Compensation Zones and is subject to change as the Zone associated with the actual offer is confirmed. In addition to the base and bonus, full-time employment, and more. For information about our benefits, please visit https://benefitsatfanatics.com/ Salary Range $190,000 — $237,500 USD By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy. Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here .

Location: Prague Workplace: hybrid Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows, and teams into one unified platform—where modern legal work happens with clarity and consistency. Powered by LOIS, the Legal Operating Intelligence System, Filevine connects context across every matter to transform legal operations from reactive to proactive. LOIS reads, understands, and reasons across your data to surface insight, automate complexity, and give professionals the clarity and confidence to see more, know more, and do more. Fueled by a team of exceptional collaborators and innovators, Filevine’s rapid growth has earned AI awards and recognition from Deloitte and Inc. as one of the most innovative and fastest-growing technology companies in the country. The Depo Intelligence team powers the AI behind Filevine's deposition product line. We deliver automated post-deposition transcript analysis, timelines, summaries, and witness impressions. Our latest product, Depo Copilot, assists attorneys during deposition preparation and delivers real-time insights during live proceedings. Additionally, our intelligent insights extend support to the Filevine Meetings and Notetaking apps. As the Tech Lead for Depo Intelligence, you will drive the technical direction of our AI systems. This is a hands-on machine learning role requiring strong software engineering skills. You will spend your time designing and building LLM pipelines and evaluations, as well as leading the team's architectural and design choices. You will collaborate closely with the team's Engineering Manager, who handles people management and delivery, allowing you to focus squarely on technical leadership. Key Responsibilities Own the technical vision and system architecture for machine learning workflows driving Depo Copilot, Depo Summaries, and the Meetings and Notetaking app. Architect and build LLM pipelines capable of reasoning over extensive case files and real-time transcripts, ensuring all outputs are fully grounded in source material. Determine optimal model strategies - evaluating when custom fine-tuning or trained models are required over prompt engineering - and lead implementation. Establish evaluation frameworks alongside our legal experts and annotators, creating custom datasets, rubrics, offline metrics, and release checks to proactively prevent regressions. Optimize pipeline efficiency, latency, and operational costs for live streaming analysis using strategic model selection, fallbacks, and precomputation. Transition prototypes into production-grade systems with typed contracts, test coverage, tracing, and observability, serving as technical lead for incident response during live proceedings. Author design documents, guide architectural decisions, and partner with Product, product engineering, speech recognition, and document retrieval teams to translate roadmap goals into actionable technical plans. Mentor machine learning engineers through detailed code reviews, pair programming, and design feedback while clearly communicating technical outcomes and tradeoffs to business stakeholders. Who are you? Minimum of 5 years of experience building production ML or software systems, including at least 3 years in machine learning roles with end-to-end project ownership. Proven track record of technical leadership, including conducting design reviews, setting architectural direction, and mentoring engineers. Strong background in NLP and production LLM systems, encompassing retrieval and grounding, long-context reasoning, structured outputs, evaluation, and mitigation of common failure modes. Experience designing evaluation frameworks for generative AI systems, including developing datasets and rubrics in collaboration with domain experts and annotators. Solid software engineering foundations, including API design, data modeling, distributed and asynchronous workflows, testing, and fault tolerance. Advanced proficiency in Python, alongside hands-on experience with PyTorch or other deep learning frameworks. Experience with real-time/streaming systems or legal domain NLP is a plus. Strong written and verbal communication skills in English, a collaborative team spirit, and an autonomous problem-solving mindset. Ability to meet periodically at our Prague or Bratislava office to support in-person collaboration. Our current stack primarily utilizes Python (DSPy, Pydantic, Temporal), PostgreSQL, Kubernetes, AWS, Google Cloud, and multi-provider LLMs; strong core engineering skills are prioritized over familiarity with specific tools or frameworks. Compensation starts at 190,000 CZK per month, with the final offer determined by the candidate’s seniority and experience. This opportunity is for independent contractors and is not intended to establish an employment relationship. Contractors are responsible for their own taxes and compliance with applicable laws in their jurisdiction. This role is open exclusively to candidates currently residing in, or willing to relocate to, Czechia or Slovakia with the legal right to work in these countries. Unfortunately, we are unable to consider applications from candidates based outside of these locations due to operational and regulatory requirements Privacy Policy Notice Filevine will handle your personal information according to what’s outlined in our Privacy Policy.

Location: Chicago, IL or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As a Senior AI Engineer you will own LLM-powered systems and agentic workflows for our customers. These systems automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with a measured accuracy you can defend as models change and usage grows. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system architecture, code quality, security, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the eval bar it ships against. Salary range is: $180,000 - 225,000 This position is bonus eligible. Key Responsibilities: Own the delivery of LLM-powered systems in Python and TypeScript, from an ambiguous customer problem, scoped with product managers and data scientists, through production operation. Set the evals and guardrails strategy for your area: what gates a release, what production signals the team watches, and how a change is simulated against historical claims before it ships. Raise the bar for how the team works with agentic coding tools: sharpen the specifications, instruction files, hooks, and permission policies they run under, and hold generated code to the same review standard before it merges. Design the NLP pipelines that turn unstructured claim data into structured data customers can act on, choosing where semantic search, classical NLP, or an LLM fits. Build and operate durable, event-driven, multi-tenant systems in which agents run as steps inside deterministic workflows, designing their failure modes, replay semantics, and cost profile before they show up under load. Own tracing and audit for your area: every model call and agent step recorded, so any recommendation can be reconstructed and cited back to its sources by on-call and auditors alike. Set the privacy and security baseline every system in your area starts from: tenant isolation, least-privilege access for agents and their tools, redaction, retention, and what data may reach a model provider. Author the design documents for complex systems to get feedback and buy-in, review other engineers' designs and code with the same care, and mentor the engineers in your area. Take part in a shared on-call rotation for the systems you own. Requirements: 6+ years of professional software engineering experience, including an LLM-powered system you architected, shipped to external customers, and carried through at least one model or prompt migration. Python and TypeScript at the level of setting a team's conventions: the async model, typing strictness, and test strategy for a shared codebase, plus a performance problem you profiled and fixed. An evals and guardrails strategy you set for a product area others built in: where human approval was required, and how production corrections re-entered the evals. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work, plus changes you turned back, and why. Pipelines you designed that blend LLMs, semantic search, and classical NLP, including a retrieval design you can defend and a case where a classical technique beat an LLM on cost, latency, or reliability. Durable, event-driven systems you designed with deterministic orchestration around non-deterministic model steps: compensating actions, idempotency, backpressure, and event-sourced replay. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Systems architected and operated on Azure or AWS, with CI/CD and infrastructure as code, and hands-on time with a durable workflow engine such as Temporal or the Durable Task Scheduler. Technical design documents you have authored for systems that span more than one team, used to get feedback and buy-in before building, and that those teams then built to. Clear writing and discussion for technical and non-technical audiences: drawing out a customer's real problem and explaining the trade-offs back to them. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences. Experience with agent frameworks, LangGraph, PydanticAI, and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing. Experience designing A/B tests for AI features. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months, every model change in your area is gated by evals you designed, regressions are caught before a customer sees them, and you can show the accuracy number held or moved. You are trusted with the high-stakes, ambiguous problems, and you turn them into a roadmap, a shipped system, and a number you can put in front of a customer. You are energized by what agentic coding tools make possible. Your team ships more than its headcount suggests, and your specifications and reviews are why the output survives production. You have a passion for systems that last: the ones you design have their failure modes understood in advance, and when one fails anyway, the trace says exactly where. Privacy and security reviews of systems in your area find nothing that was not already designed in. Standards you set for evals, reviews, and design documents outlive the project they started on. Engineers you mentor ship LLM-powered features with evals and guardrails in place without your direct involvement. You enjoy getting a product manager, a data scientist, and a customer's team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Location: Chicago, IL or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As an AI Engineer you will build and ship LLM-powered features and agentic workflows for our customers. These features automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with measured accuracy, not a convincing demo. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system design, security, and hard debugging. You own features end to end. Salary range is: $170,000 - 195,000 This position is bonus eligible. Key Responsibilities: Ship LLM-powered features and agentic workflows in Python and TypeScript, from a problem scoped with product managers and data scientists through production traffic, and help set the metrics you will be measured against. Write the evals, guardrails, and feedback loops that make your features trustworthy, and hold them to explicit token and latency budgets. Use agentic coding tools every day, and own the review of what they produce: catch the correctness, security, and design problems in generated code before you open the pull request. Maintain and extend the NLP pipelines that turn unstructured claim data into structured data customers can act on, blending semantic search, classical NLP, and LLMs. Build and operate durable, event-driven services in which agents run as steps inside deterministic workflows, with checkpointed model outputs so a retry does not re-invoke a completed LLM step. Trace every model call and agent step so a recommendation can be reconstructed and audited, with citations back to the source documents, and wire that tracing into your alerts. Model and query claims data across relational, document, and graph stores. Design privacy and security in from the start: tenant isolation, least-privilege access for agents and their tools, and a clear rule for what data may reach a model provider. Write a technical design document before any significant change, and use it to get feedback and buy-in from the team before you build. Take part in a shared on-call rotation for the services you build. Requirements: 3+ years of professional software engineering experience, including at least one LLM-powered feature you shipped and then operated in production. Python and TypeScript: typed, tested, async code in both, and real depth in one. Evals you have designed for LLM output, plus guardrails you have shipped. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work. Pipelines that blend LLMs with semantic search and classical NLP: structured output, tool calling, embedding-based retrieval, and a case where a classical technique beat an LLM. Services built on message- or event-driven architectures, including long-running workflows with retries, idempotent handlers, and event-sourced state, plus an LLM or agent step you ran inside one. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Backend services built and operated on Azure or AWS, and exposure to a durable workflow engine such as Temporal or the Durable Task Scheduler. Technical design documents you have written to get feedback and buy-in from a team before building, and that the team then built to. Clear writing and discussion for technical and non-technical audiences, and code review you can give as well as take. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end. Chat, streaming, and citation-heavy AI experiences especially. Experience with CI/CD pipelines and infrastructure as code such as Terraform or Bicep. Experience with agent frameworks, LangGraph and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing. Experience designing A/B tests for AI features, or what-if simulations that replay historical claims through a proposed change before it ships. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months you ship an LLM-powered feature, its evals run in CI, and you can name the metric it moved. When a model migration or prompt change causes a regression, the evals you wrote catch it before a customer does. You take ownership from concept to production with light direction, asking the right questions early. You care that things hold up: the services you build survive retries, partial failures, and model migrations without incidents a customer can see. When something goes wrong in production, the trace tells you which step and which model call, and you can show an auditor the same thing. Privacy and security reviews of your features find nothing that was not already designed in. You enjoy the craft, and it shows: engineers pick up your patterns without being told to. You enjoy the back-and-forth that gets a feature scoped, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Ищем Tech Lead для руководства командой NLP-инженеров и backend-разработчиков, которая развивает платформу парсинга документов в банке. Специалист будет отвечать за техническое развитие продукта, архитектуру LLM/NLP-решений, управление бэклогом и качество реализации.

Founders Factory is looking for a Co Founder and CTO to build and scale an AI-powered field-service product and its engineering organization.

Figure’s Property Analytics team is seeking a Senior Applied Scientist to join us in our effort to reinvent real estate lending. You will be working alongside engineering, product, and business leaders to tackle complex research and machine learning problems related to automated valuation models (AVMs), asset valuation, and process optimization.

Задачи: анализ транскрибированных звонков и оценка качества транскрибации, применение LLM для подготовки рекомендаций сотрудникам, написание системных промптов, анализ качества и настройка ETL, использование open-source ASR-модуля при низком качестве транскрибации, разработка AI-агентов для первой линии поддержки.

Location: Москва Мы - Управление развития искусственного интеллекта блока "Развитие клиентского опыта B2C". В нашей зоне ответственности ML-решения, результаты работы которых ежедневно влияют на поведение десятков миллионов клиентов. Развитие клиентского опыта – динамический и активно развивающийся процесс. Совместно с бизнесом мы проводим десятки различных экспериментов ежемесячно, и лучшие из них оформляем в полноценные ML продукты. Финансовые эффекты от наших продуктов > 1 млрд. руб. в год. И сейчас мы находимся в поиске сильного технического специалиста по профилю Classic ML Data Scientist. Обязанности * строить ML модели на основе различных данных: табличные, графовые, NLP, GEO, последовательности событий (кликстрим, транзакции и т.д.) * писать production код и выводить его в ПРОМ * улучшать процесс построения моделей, разрабатывать собственные прикладные модули командного фреймворка разработки для повышения производительности DS и улучшения качества кода в промышленной среде * выдвигать data-driven гипотезы/предложения для запуска новых механик, а также поиск инсайтов в данных. Требования * глубокое знание классического ML * понимание основных Deep Learning подходов * продвинутое знание SQL * отличное знание Python * понимание и опыт АB-тестирования. будет плюсом: * понимание специфики разработки ML-технологий, начиная с формулировки бизнес-проблемы, заканчивая выведением на регулярную основу в прод * опыт решения задач ранжирования или Real Time Bidding * опыт работы с Pyspark, Greenplum. Условия * комфортный современный офис рядом с м. Кутузовская  * офисный формат работы * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха более 400 образовательных программ СберУниверситета для профессионального и карьерного развития  * программа адаптации и помощь руководителя на старте  * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа  * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких  * вознаграждение за рекомендацию друзей в команду Сбера.

Location: United States Workplace: remote About Lyra Health Lyra Health is a leading provider of evidence-based mental health care, serving more than 20 million people globally in partnership with employers and more than 100 million through health plan and partner relationships. The company has delivered more than 15 million sessions of mental health care, published more than 35 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness, and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions. About the Role:  The Director of People Analytics and Workforce Intelligence will lead our global workforce intelligence strategy, transforming complex talent and organizational data into actionable business outcomes. Reporting to the Sr. Director, People Solutions, you will bridge HR, Artificial Intelligence, and enterprise analytics.  We are seeking a visionary leader to architect scalable solutions that empower executive leadership and managers to make data-driven decisions. You will build proactive tools to create insights that shift the paradigm from reactive reporting to predictive talent interventions. This role can be based in our Madison, WI office, or fully remote/virtual. Remote candidates must be physically located within the United States. Responsibilities Define and execute the global roadmap for People Analytics, aligning workforce insights directly with core business strategy and growth goals. Lead the design, development, and deployment of custom AI-driven analytics tools, internal dashboards, and predictive decision-support applications for leaders and managers. Shift the organizational paradigm from reactive, descriptive reporting to proactive, predictive talent interventions (e.g., flight-risk modeling, workforce planning, skill gap forecasting, performance drivers). Utilize Generative AI frameworks across HR data ecosystems to automate insights generation, summarize employee sentiment, and streamline talent operations. Partner with IT, Enterprise Data, and Security teams to ensure rigorous data governance, privacy compliance (GDPR/CCPA), and ethical AI frameworks for employee data. Champion data democratization across the company by training and empowering People Business Partners and business managers to self-serve actionable insights. Serve as the principal data advisor to the People Leadership Team, translating complex analytical findings into compelling executive narratives. Design framework models that measure the ROI of People programs, culture initiatives, compensation strategies, retention plans, and talent acquisition pipeline efficiency. Benchmark internal metrics against industry standards and macroeconomic trends to anticipate organizational talent shifts. Qualifications 10+ years of progressive experience in Analytics, Business Intelligence, or Workforce Data Science Demonstrated experience building or deploying AI/ML models (e.g., predictive modeling, NLP for sentiment analysis, LLM integrations) that translate raw data into user-friendly organizational tools. Advanced proficiency in SQL, Python/R, and enterprise HR systems (Workday, SuccessFactors, etc.), along with demonstrated experience implementing a data warehouse that connects to a BI visualization platform (e.g., Tableau, PowerBI, Looker). Exceptional narrative and storytelling ability—capable of distilling complex statistical models into clear, high-impact strategies for executive stakeholders. Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Industrial/Organizational Psychology, Business Analytics, or a related quantitative field. "We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.   By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra.  We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR.  Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives.  If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form.  This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice." As a full-time Director, People Analytics and Workforce Intelligence , you will be employed by Lyra Health, Inc. The anticipated annual base salary range for this full-time position is $189,000 to $231,000. The base range is determined by role and level, and placement within the range will depend on a number of job-related factors, including but not limited to your skills, qualifications, experience and location. This role may also be eligible for discretionary bonuses.  Annual salary is only one part of an employee’s total compensation package at Lyra. We also offer generous benefits that include:  Comprehensive healthcare coverage (including medical, dental, vision, FSA/HSA, life and disability insurances) Lyra for Lyrians; coaching and therapy services Equity in the company through discretionary restricted stock units Competitive time off with pay policies including vacation, sick days, and company holidays Paid parental leave  401K with up to 3% matching Monthly tech allowance We like to spread joy throughout the year with well-being perks and activities, surprise swag, regular community celebration…and more!   We can’t wait to meet you.

Проект по созданию аналитической платформы на базе ИИ — единая экосистема для работы с данными.

Задачи: — участие в формулировке ИИ-гипотез, подготовке данных и обучении моделей, включая LLM-решения и классический ML — экспериментирование с LLM, prompt-инжиниринг, RAG и агентные подходы — разработка прототипов ИИ-сервисов — оценка качества моделей по метрикам, проведение офлайн- и онлайн-экспериментов — ведение технической документации и артефактов экспериментов Требования: — опыт работы в DS/ML не менее 3 лет в реальных продуктах — уверенные знания Python и библиотек NumPy, pandas, scikit-learn, PyTorch и других — опыт решения NLP-задач не-LLM методами — опыт или готовность быстро освоить LLM (развёртывание, настройка, prompt-инжиниринг, RAG/агенты) — понимание работы генеративных моделей и методов их дообучения — навыки подготовки и анализа данных, построения и интерпретации метрик — знание принципов создания ML-сервисов в on-prem (REST API, Docker) — понимание ML-жизненного цикла — английский язык для чтения статей и документации

Location: Алматы Задачи Разрабатывать ML модели для широкого круга задач; Участвовать в разработке сервиса на основе ML на всех этапах: от сбора данных до выкатки в продакшн и дальнейшего мониторинга/сопровождения сервиса; При необходимости оптимизировать модели под HighLoad системы; Тесное взаимодействие со своей продуктовой командой; Работать с нейронными сетями и обучать PyTorch модели для production; Интегрировать языковые модели (LLM/SLM) в существующие сервисы компании. Требования Понимание теории вероятности, математической статистики, линейной алгебры; Знание “классического ML” на хорошем уровне (регрессия, методы кластеризации, деревья решений и их ансамбли); Знание основ Deep Learning в сфере CV и NLP (работа с разнородными данными: изображения, текст, табулярные данные); Владение Python (опыт использования Pytorch) и связанным с ним стэком для ML (pandas, sklearn, numpy); Знание Git и Docker. Будет плюсом Опыт разработки ML решений в одной из следующих областей: NLP, CV, Recommendation Systems; Опыт работы с DVC, MLFlow; Опыт работы с airflow, bigquery; Понимание kubernetes.

Location: Москва Мы помогаем государству проводить disrupt госуправления через внедрение AI/GenAI и ускорять национальное развитие AI/GenAI, организуем одно из крупнейших в мире профильных мероприятий – AIJourney, объединяем бизнес, государство и международное научное сообщество, чтобы обеспечить GenAI-трансформацию страны. Обязанности • cтроить и развивать систему оценки качества LLM, RAG и агентов: тестовые наборы, метрики, автоматические прогоны, отчёты • проводить регрессионное тестирование в CI при смене моделей, промптов и настроек, контролировать качество перед релизами и показами • оценивать агентов по траекториям: успешность задач, ошибки вызова инструментов, лишние шаги • калибровать автоматическую оценку (LLM-as-a-judge) против экспертной разметки • строить пайплайны обработки документов: PDF, сканы, OCR, таблицы, восстановление структуры • готовить датасеты для дообучения, включая синтетические данные и траектории вызова инструментов. Требования • от 3 лет в Data Science, Data Engineering или ML, из них не менее года с LLM-проектами • опыт построения с нуля системы оценки качества LLM или RAG • знание метрик поиска (recall@k, MRR, nDCG) и метрик ответов (faithfulness, полнота, корректность) • опыт оценки агентных систем или многошаговых сценариев • прикладная статистика: доверительные интервалы, значимость различий, размер выборки • опыт обработки реальных документов в продакшене, включая OCR • Python на уровне production-кода, уверенный SQL • оркестрация пайплайнов (Airflow, Prefect, Dagster или аналоги), версионирование данных и трекинг экспериментов (DVC, MLflow или аналоги). **Будет плюсом:** • работа с юридическими, нормативными или канцелярскими текстами на русском языке • классический NLP: NER, классификация, извлечение сущностей • опыт с русскоязычными бенчмарками • работа с персональными данными по 152-ФЗ • Elasticsearch, OpenSearch, векторные базы данных. Условия * гибридный формат работы (м Кутузовская) * ежегодный пересмотр зарплаты, годовой бонус * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа.

Location: Москва, удалённая работа, RU; Россия О команде Юнит Support Automation разрабатывает и развивает внутренние сервисы и инструменты, которые помогают автоматизировать работу с пользовательскими обращениями в поддержку. Команда отвечает за метрики эффективности систем автоматизации и удовлетворённости пользователей в автоматизированной части потока. Юнит состоит из кросс-функциональных команд, которые работают с разными этапами обработки обращений: первичной классификацией, RAG-системами, LLM-агентами и оценкой автоматизированных сценариев. Какие задачи вас ждут: — строить и улучшать RAG-систему поддержки: retrieval- и generation-части; — настраивать и поддерживать безопасность процесса: создавать гардрейлы, обеспечивать надёжность работы и снижать риск галлюцинаций; — разрабатывать мультиагентные системы, которые помогают пользователям решать вопросы по определённой теме обращения, оптимизировать промпты и инференс моделей; — анализировать эффективность решений на исторических данных и в продакшене с учётом офлайн-метрик качества решения ML-задач и бизнес-метрик; — экспериментировать с SOTA-методами машинного обучения, когда их применение оправдано задачей; — разрабатывать и внедрять модели для определения тематики обращений пользователей: более 500 интентов, которые постоянно расширяются новыми и объединяются друг с другом; — поддерживать и улучшать существующие модели и эвристики для разных классификаций обращений: от простых правил и эвристик до ML-систем с онлайн-инференсом LLM-моделей; — проектировать и внедрять сквозные ML-решения, а также готовить дизайн и запускать A/B-тесты совместно с аналитиками; — отслеживать деградации и изменения метрик в продакшене. Мы ждём, что вы: — не менее 2 лет работали в Data Science в NLP-домене; — строили RAG-системы и оценивали их качество в продакшене; — понимаете принципы построения AI-агентных систем; — имеете опыт работы с NLP-задачами в продакшене; — внедряли ML-модели в продакшен; — пишете поддерживаемый, тестируемый и масштабируемый код на Python; — владеете стеком PyTorch, pandas, NumPy, Docker; — работали с агентными библиотеками: ADK, LangGraph, PydanticAI или аналогами; — работали с self-hosted LLM 8B+ в продакшен-задачах; — понимаете ML-алгоритмы: классические подходы и основные архитектуры нейронных сетей; — используете агентную разработку в рабочих задачах или пет-проектах; — знаете, как при необходимости организовать разметку, в том числе с помощью LLM. Будет здорово, если вы: — работали с разными модальностями данных и понимаете, какие методы ML/DL применимы в конкретных бизнес-задачах; — получили высшее образование в области прикладной математики, статистики, ML или в смежных областях; — уверенно владеете SQL и умеете извлекать необходимые данные для анализа и обучения моделей; — умеете оценивать качество моделей при запуске нового проекта и отслеживать его изменение во времени; — при запуске модели учитываете не только ML-метрики, но и влияние решения на бизнес-метрики, за которые отвечает команда; — имеете опыт автоматизации поддержки или похожих бизнес-процессов. Работа у нас — это: — возможность влиять на пользовательский опыт и развивать ML-продукты Авито; — исследовательские и инженерные задачи в продуктах Support Automation; — культура взаимопомощи и обмена опытом в DS-сообществе; — прозрачный карьерный трек и инструменты для роста: семинары, менторство, митапы; — мощное оборудование, AI-инструменты и всё, что нужно для продуктивной работы; — расширенная забота о здоровье: ДМС, страхование жизни, онкострахование; — сервис психологической поддержки, а также финансовые, юридические и ЗОЖ-консультации для вас и ваших близких; — корпоративный спорт: групповые тренировки, велбиинг-приложение; — спецпредложения от партнёров и скидки на сервисы Авито: бронирование жилья, услуги продвижения, ипотечное страхование; — компенсация питания.

Location: Москва Мы - команда, создающая **комплексную систему противодействия мошенничеству** и обеспечивающая online/offline безопасность миллионов клиентов банка 24/7/365, предоставляя инструменты **собственной разработки** для: * Построения графа связей (позволяет проанализировать не только объекты и их свойства, но также их связи с другими объектами различных уровней и характеристик и применяется для получения дополнительных знаний об объекте за счет извлечения знаний о его окружении, выявления наиболее значимой информации, центров влияния, групп связанных объектов, цепочек) * Геопространственой аналитики: анализа локаций, построения маршрутов и тепловых карт * Выявления и анализа попыток мошенничества и иных отклонений * Портфеля технологичных сервисов накопления и обработки больших объемов данных со сложной структурой Мы находимся на передовой технологических инноваций, соединяя возможности ИИ, современные технологии и потребности общества. Наше направление AI-трансформации — это стратегическая инициатива по интеграции LLM-агентов и мультиагентных систем в собственную аналитическую платформу: * AI-решения для глубокого анализа данных * Набор AI Tools, дающих агентам доступ к инструментам и сервисам платформы * Собственная no-code/low-code платформа для оркестрации AI-агентов и автоматизации рабочих процессов * Интеграция с внутренними LLM-шлюзами и средами исполнения агентов * RAG-системы для работы с корпоративными базами знаний и методологиями Наш передовой технологический стек: * Storage - Hadoop, Cassandra, ClickHouse, Elasticsearch, FastGraph, PostgreSQL * Big Data Engineering- Scala, Spark, Flink * Backend - GO (GIN), Scala (ZIO), Kubernetes (OpenShift, DropApp) * Fronted - React, Redux (Redux ToolKit, RTK Query), Typescript, jest. Библиотеки: react-force-graph, leaflet * AI - Python (LangChain, LangGraph, Harness), GO (mcp-go), Typescript (no code platform), ai-coding (gigacode cli, claude, codex), RAG\\GraphRag (PostgreSQL, Elasticsearch, Qdrant) * QA - Java, TestNG, Selenium, Maven, Allure * DevOps - Docker, Helm, Jenkins Обязанности * Проектирование и анализ архитектуры технического решения совместно с командой разработки * Разработка и согласование концепции, проектной документации и технической документации, описание API, ведение документации в Confluence * Развитие направления мультиагентных решений обеспечивая полный цикл реализации * Проведение исследовательских работ и тестирование новых подходов и техник AI * Анализ источников данных, разработка моделей данных, логики алгоритмов и интеграций * Документирование и обеспечение соблюдения правил сбора, хранения и использования данных * Участие в полном цикле разработки и внедрения Требования * Умение быстро погружаться в исследуемую область и оперативно переключаться на новое направление * Навыки интеграции решений на основе ML/AI в реальные производственные системы * Опыт проектирования логической и физической моделей данных. Языки SQL: понимание работы ETL-инструментов, умение писать SQL-запросы различной сложности * Знание форматов JSON/XML и навыки проектирование REST API * Способность обрабатывать и структурировать большой объем сложной информации, доступно и наглядно ее презентовать * Сбор, анализ и документирование бизнес-требований, описание use case, генерация идей, проработка технических решений, интеграционных взаимодействий * Коммуникативные навыки, достаточные для выстраивания конструктивного взаимодействия со смежными подразделениями и внутри команды Будет плюсом * Понимание ключевых алгоритмов и подходов в AI/GenAI (LLM, vector search, NLP, context engineering и др.) * Понимание архитектуры AI/GenAI решений, LLM, RAG, BI и DataOps * Наличие опыта разработки собственных библиотек и инструментов для AI * Опыт успешного внедрения AI-решений, знание инструментов AI на рынке * Опыт программирования на любом языке и способность анализировать код * Владение инструментами Big Data (Hadoop, AirFlow, Spark, Kafka) * Понимание принципов работы NoSQL баз данных (Cassandra, ClickHouse, ElasticSearch, Qdrant, Neo4j) Условия * Комфортный современный офис (ст.м.Кутузовская) * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Remote, Worldwide 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 are representative of the knowledge, skill, and/or ability required.     MAIN RESPONSIBILITIES - Performing Translations / Review and quality assurance (QA) of Punjabi translation Tasks. - Performing copy-editing and linguistic checks to ensure accuracy, consistency, and style adherence. - Providing feedback to translators and freelancers to improve overall quality. - Managing and maintaining language assets (glossaries, style guides, work instructions), ensuring they are accurate, consistent, and up to date. - Managing and responding to linguistic queries from translators, project managers, etc. - Ensuring smooth collaboration within the translation team by clarifying terminology, style, and linguistic issues. - Supporting the onboarding, development, and training of new linguists and freelancers when required. - Participating in the development of new and improved review and quality processes. - Meeting or exceeding quality and productivity KPIs as defined for the role. - Achieving the goals set by the Squad Lead / Language Lead.   REQUIEREMENTS Education Level - University degree in Translation, Applied Languages, Linguistics, or an equivalent combination of education and experience.   Experience - 3+ years of experience in translation, review, or localization. - Native fluency in Punjabi Language. - Fluency in English (written and spoken). - Solid understanding of the localization process and review workflows. - Proficiency in standard software (Windows, MS Office). - Hands-on experience with CAT tools (e.g., XTM, SDL Studio, PolyGlot, MateCat, ATMS, fbCAT etc.) and query/issue management tools (e.g., JIRA). - Ability to quickly learn and adapt to new localization tools.   Skills - Strong attention to detail with excellent review and editing skills. - Ability to give clear, concise, and constructive feedback to linguists. - Strong communication skills (written and verbal). - Excellent knowledge of terminology management in one or more subject areas. - Ability to work effectively under tight deadlines. - Strong problem-solving skills and ability to handle varied linguistic issues. - Ability and willingness to train and mentor others when required. - Positive approach to client and stakeholder communication. - Ability to work successfully in a virtual, global team.