Вакансии

Location: Canada, Waterloo, ON Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. At PlayStation, we're passionate about both partnership and technology. We care about building performant products and powerful tools, solving practical problems in delightful ways. We love building the systems that millions of people use, and we're always our own first customers and critics. We strive to be at the forefront of development technologies and celebrate our diversity with engineering teams located on four continents from all walks of life. We build our teams to be places where every voice is heard, all input is valued, and our members have the creative freedom to make their ideas real. Sr Software Development Engineer in Test , ML Locations: Madison, WI and Waterloo, Ontario Canada P layStation is seeking a Sr Software Development Engineer in Test, ML to join our Madison team and lead quality efforts for machine learning-powered products and services. You will partner closely with ML engineers, software engineers, product managers, and data partners to build scalable test automation and validation approaches for systems serving PlayStation at global scale. This role is focused on building confidence in model reliability, production readiness, and behavioral consistency. Unlike traditional software backend testing, success here requires validating probabilistic systems through score distributions, cohort-level behavior, thresholds, and statistical signals, not just deterministic pass/fail assertions. Responsibilities: Drive architecture-level automation solutions and scalable quality engineering practices across multiple teams and product areas. Design, develop, and maintain automated test frameworks, test scripts for ML inference services and related ML platform components using python/Java Build and automate realistic, representative test account creations and datasets to evaluate model behavior across different scenarios Validate score distributions, ranking behavior, output quality, and other model signals for incoming ML models prior to release Perform different types of testing, including functional, integration, regression and API testing working with RESTful APIs, microservices and databases, and non-functional performance and load testing to verify inference service scalability, latency requirements and reliability under production like conditions Work closely with ML engineers and ops teams to ensure that all features and bug fixes come with automated test coverage, ensuring continuous integration and deployment Debug and analyze test failures, model anomalies and report defects Drive high standards of quality for both engineering decisions and customer-facing features with optimal test and automation strategy Develop and implement best practices for test automation that is highly scalable and maintainable Monitor test execution and optimize performance in test environments Come up with innovative solutions to organizational problems Required Qualifications: A Bachelor's degree in Computer Science or related field Minimum 5 years of experience as an SDET, with strong experience testing backend systems. Proficiency in Python/Java/Scala/go for test automation. Hands-on experience with API testing tools (e.g., Postman or similar) for distributed systems Familiarity with CI/CD pipelines and test execution in Jenkins or similar environments such as jenkins, GitHub Actions, ArgoCD, etc Hands-on experience building and maintaining automated test frameworks (e.g., pytest, JUnit, TestNG, etc.)Experience in working with databases for backend validation. Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker, etc.) Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, etc.) for validating service health Strong understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and excellent communication skills. Preferred Qualifications: Experience testing machine learning systems, such as recommendation systems, search ranking systems, or other probabilistic ML application systems. Experience creating synthetic or seeded test data to simulate realistic customer/account behaviors. Experience evaluating model outputs using statistical techniques, distribution analysis, or scenario-based validation, rather than deterministic assertions. Knowledge of data pipelines, feature stores, inference systems or model-serving infrastructure (Seldon, KServe, Ray Serve, etc.) is a plus. Experience with performance and load testing tools Experience with Databricks or similar ML platform tooling Experience architecting and optimizing CI/CD pipelines, quality gates, and release validation systems using Jenkins or similar platforms. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. The estimated Ontario base pay range for this role is listed below. $114,000 — $143,000 CAD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

PlayStation Global10 дн назад

Senior Staff Applied Scientist, Science Platform

Location: United States, Madison, WI Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. At PlayStation, we're passionate about both partnership and technology. We care about building performant products and powerful tools, solving practical problems in delightful ways. We love building the systems that millions of people use, and we're always our own first customers and critics. We strive to be at the forefront of development technologies and celebrate our diversity with engineering teams located on four continents from all walks of life. We build our teams to be places where every voice is heard, all input is valued, and our members have the creative freedom to make their ideas real. Sr Software Development Engineer in Test , ML Locations: Madison, WI and Waterloo, Ontario Canada P layStation is seeking a Sr Software Development Engineer in Test, ML to join our Madison team and lead quality efforts for machine learning-powered products and services. You will partner closely with ML engineers, software engineers, product managers, and data partners to build scalable test automation and validation approaches for systems serving PlayStation at global scale. This role is focused on building confidence in model reliability, production readiness, and behavioral consistency. Unlike traditional software backend testing, success here requires validating probabilistic systems through score distributions, cohort-level behavior, thresholds, and statistical signals, not just deterministic pass/fail assertions. Responsibilities: Drive architecture-level automation solutions and scalable quality engineering practices across multiple teams and product areas. Design, develop, and maintain automated test frameworks, test scripts for ML inference services and related ML platform components using python/Java Build and automate realistic, representative test account creations and datasets to evaluate model behavior across different scenarios Validate score distributions, ranking behavior, output quality, and other model signals for incoming ML models prior to release Perform different types of testing, including functional, integration, regression and API testing working with RESTful APIs, microservices and databases, and non-functional performance and load testing to verify inference service scalability, latency requirements and reliability under production like conditions Work closely with ML engineers and ops teams to ensure that all features and bug fixes come with automated test coverage, ensuring continuous integration and deployment Debug and analyze test failures, model anomalies and report defects Drive high standards of quality for both engineering decisions and customer-facing features with optimal test and automation strategy Develop and implement best practices for test automation that is highly scalable and maintainable Monitor test execution and optimize performance in test environments Come up with innovative solutions to organizational problems Required Qualifications: A Bachelor's degree in Computer Science or related field Minimum 5 years of experience as an SDET, with strong experience testing backend systems. Proficiency in Python/Java/Scala/go for test automation. Hands-on experience with API testing tools (e.g., Postman or similar) for distributed systems Familiarity with CI/CD pipelines and test execution in Jenkins or similar environments such as jenkins, GitHub Actions, ArgoCD, etc Hands-on experience building and maintaining automated test frameworks (e.g., pytest, JUnit, TestNG, etc.)Experience in working with databases for backend validation. Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker, etc.) Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, etc.) for validating service health Strong understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and excellent communication skills. Preferred Qualifications: Experience testing machine learning systems, such as recommendation systems, search ranking systems, or other probabilistic ML application systems. Experience creating synthetic or seeded test data to simulate realistic customer/account behaviors. Experience evaluating model outputs using statistical techniques, distribution analysis, or scenario-based validation, rather than deterministic assertions. Knowledge of data pipelines, feature stores, inference systems or model-serving infrastructure (Seldon, KServe, Ray Serve, etc.) is a plus. Experience with performance and load testing tools Experience with Databricks or similar ML platform tooling Experience architecting and optimizing CI/CD pipelines, quality gates, and release validation systems using Jenkins or similar platforms. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $152,000 — $190,000 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Reddit10 дн назад

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit brings people together around their interests, questions, and experiences. Our communities generate a rich and complex ecosystem of human activity, creating scientific challenges in understanding behavior, measuring impact, and anticipating change. The Data Science Platform team builds the tools that enable a scientific understanding of Reddit. We develop Reddit’s analytics agent, and the shared scientific capabilities and methods that allow data scientists and business partners to answer increasingly sophisticated questions. We are looking for a senior technical lead who combines deep expertise in statistics, machine learning and causal inference with strong software engineering ability. You will establish the scientific direction for agentic analytics, causal inference, and forecasting, turning advances in research into reliable software used across the company. As an Applied Scientist on the Science Platform team, you will work across the full development cycle: identifying important problems, evaluating research, implementing and validating methods, and shipping capabilities that others can use confidently. You will partner closely with software engineers and data scientists to build an analytics agent that can investigate questions, select appropriate methods, execute analyses, and communicate findings with clear assumptions and uncertainty. Responsibilities: Define the scientific roadmap for Data Science Platform across agentic analytics, causal inference and forecasting, identifying opportunities where advances in methodology can improve decision-making at scale across Reddit. Research, evaluate, and implement emerging methods. Move quickly from research papers to working prototypes, validate their practical value, and develop successful approaches into maintained production capabilities. Design and build our analytics agent’s architecture and capabilities, including how the agent decomposes questions, selects scientific methods, uses data and analytical tools, checks assumptions, and produces reproducible results. Build reusable causal inference tools that help teams estimate the effects of product changes, policies, and business decisions using observational data. Develop shared forecasting capabilities for business and product metrics, including probabilistic predictions, hierarchical forecasts, and scenario analysis. Create evaluation frameworks that measure the correctness and usefulness of agent-generated analyses. Build benchmarks, simulations, and automated checks that detect methodological errors, unsupported claims, and misleading interpretations. Own the implementation of scientific methods in production software, writing robust Python code and partnering with engineers on libraries, APIs, data pipelines, observability, and system design. Work with data scientists and business partners to identify recurring analytical needs and translate them into accessible platform capabilities, documentation, and workflows. Influence technical and organizational strategy through clear scientific recommendations, mentor scientists and engineers, and share methodological advances internally and externally where appropriate. Required Qualifications: A doctorate in Statistics, Economics, Computer Science, Applied Mathematics, Operations Research, or a related discipline; alternatively, a master’s degree supported by comparable depth of expertise. At least eight years of relevant industry work following a doctorate, or ten years with a master’s degree, in applied science, data science, scientific software development, or related roles. Deep knowledge of statistical inference and econometrics, with practical experience developing causal methods for observational data and evaluating the assumptions that make their conclusions credible. Experience developing and deploying forecasting systems, including time series modeling, temporal validation, prediction intervals, and assessment of performance as underlying conditions change. Strong software engineering skills, including substantial experience writing and maintaining production Python software. Familiarity with API design, automated testing, code review, version control, and operational monitoring. A demonstrated ability to critically assess scientific literature, reproduce relevant findings, and turn promising methods into reliable software that solves practical problems. Experience developing LLM applications or analytical agents, including tool use, code execution, and systematic evaluation of their outputs. Clear communication of statistical assumptions, uncertainty, and technical tradeoffs to business audiences. Experience developing other technical contributors through mentorship, design reviews, and collaboration across organizational boundaries. The ability to make progress on ambiguous problems, prioritize consequential work, and deliver useful capabilities through rapid iteration. Preferred Qualifications: Publications, open-source contributions, or widely adopted internal tools in agentic analytics, causal inference, forecasting, or other related fields. Experience building scientific libraries or platforms used by other data scientists, including interfaces that make sophisticated methods accessible to people with different levels of statistical expertise. Experience building agents at scale that perform substantive analytical work, including retrieval of relevant data and context, selection of methods, execution of Python or SQL, and validation of findings. Benefits: 100% remote opportunity (we have four office locations for hybrid/onsite work preference in NY, SF, LA and Chicago) Comprehensive Healthcare Benefits and Income Replacement Programs 401K with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-AJ1 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $232,500 — $325,500 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

LangChain10 дн назад

Location: New York, NY Workplace: Hybrid 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 ROLE You will be LangChain's dedicated cloud alliance lead for AWS, owning the relationships and revenue motions that make these partnerships produce real pipeline. This is a senior individual contributor role sitting within the Partnerships team where you'll be close to the product, close to the field, and expected to drive results without a lot of hand-holding. You'll own co-sell execution and marketplace presence end-to-end, working with cloud partner teams, field sellers, and LangChain's GTM organization to turn partner relationships into closed deals. WHAT YOU'LL DO Co-sell and pipeline - Own and grow LangChain's co-sell motion with AWS: manage joint pipeline, coordinate deals with AWS field teams, and drive sourced and influenced revenue. - Partner with LangChain sales leadership to define priority co-sell accounts, map territories to AWS coverage, and run co-sell plays region by region. - Keep ACE hygiene high across the sales team so that opportunity sharing, acceptance, and launch become routine rather than a partnerships-team chore. Marketplace - Own LangChain's AWS Marketplace presence end to end: listings, private offers, CPPO through channel partners, and program enrollment. - Operate our marketplace GTM platform (Suger today) and extend referral and offer automation so sellers can transact through Marketplace without partnerships-team involvement. Programs and funding - Operationalize AWS funding mechanisms across the team: MDF (market development funds for co-marketing), proof-of-concept credits, ISV Accelerate benefits, and any strategic collaboration funding we secure. - Pursue AWS competency and specialization programs that strengthen our positioning with AWS sellers. - Track funding drawn down against funding available and report it monthly. Executive and partner relationships - Own LangChain's working relationships at AWS: partner development managers, ISV sales managers, Marketplace category leads, and the Bedrock and AgentCore partner teams. - Build executive sponsorship on both sides, and run a joint business plan with AWS that sets shared goals and a review cadence. - Navigate the coopetitive dynamic: partner closely with AWS on Bedrock and AgentCore while differentiating LangGraph and LangSmith where AWS has competing offerings. Field enablement and marketing - Equip LangChain sales, solutions engineering, and marketing with better-together messaging, competitive positioning, and joint sales plays for AWS accounts. - Partner with marketing on co-branded campaigns, content, and events that generate pipeline, including re:Invent, AWS Summits, and joint customer programs. - Communicate results clearly to internal stakeholders, including a monthly readout on pipeline, Marketplace, and program activity. WHAT YOU'LL BRING - 6+ years in cloud alliances, partner sales, or business development, with direct, hands-on ownership of an AWS relationship. - A track record of scaling a hyperscaler co-sell motion, not just starting one: you have taken a working AWS alliance to materially higher Marketplace share, pipeline, or partner-sourced revenue, and you can describe the mechanisms that got you there. - Deep working knowledge of AWS Marketplace transactions and programs: private offers, CPPO, ACE, ISV Accelerate, and the funding programs available to ISVs. - Experience operating a marketplace GTM platform such as Suger, Tackle, or WorkSpan, including referral and offer automation. - Experience shaping and running a joint business plan with a hyperscaler, including executive sponsorship on both sides. - Enough technical foundation to speak credibly with builders. You do not need to write code, but you need to understand how LangGraph, LangSmith, and LangChain fit into a customer's AWS stack. - Experience in a startup or high-growth environment where you set the operating rhythm for a partner motion rather than inheriting one. - Strong operational discipline: you manage pipeline in the CRM, track partner activity, and report results clearly to internal stakeholders. - Excellent communication and relationship-building skills, with comfort owning senior relationships at a large cloud organization and resolving conflict constructively across company lines. NICE TO HAVE'S - Prior experience inside AWS in partner sales, ISV, or Marketplace roles, with a working understanding of how co-sell decisions and seller compensation work internally. - Experience with commercial contracts with AWS like SCAs. - Existing relationships across the AWS ISV, field, Marketplace, and Bedrock partner teams. - Familiarity with the AI/ML ecosystem: how LLMs, agents, and developer tooling fit into enterprise stacks. - Experience with AWS partner programs specific to AI and data, such as the Generative AI Competency and related partner tracks. - Prior experience at a developer tools or infrastructure company with a product-led growth motion. Annual salary range: $200,000 - $250,000 OTE + Equity 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.

LangChain10 дн назад

Software Engineer, Infrastructure Engineering

Location: Chicago, IL Workplace: Hybrid 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 ROLE You will be LangChain's dedicated cloud alliance lead for AWS, owning the relationships and revenue motions that make these partnerships produce real pipeline. This is a senior individual contributor role sitting within the Partnerships team where you'll be close to the product, close to the field, and expected to drive results without a lot of hand-holding. You'll own co-sell execution and marketplace presence end-to-end, working with cloud partner teams, field sellers, and LangChain's GTM organization to turn partner relationships into closed deals. WHAT YOU'LL DO Co-sell and pipeline - Own and grow LangChain's co-sell motion with AWS: manage joint pipeline, coordinate deals with AWS field teams, and drive sourced and influenced revenue. - Partner with LangChain sales leadership to define priority co-sell accounts, map territories to AWS coverage, and run co-sell plays region by region. - Keep ACE hygiene high across the sales team so that opportunity sharing, acceptance, and launch become routine rather than a partnerships-team chore. Marketplace - Own LangChain's AWS Marketplace presence end to end: listings, private offers, CPPO through channel partners, and program enrollment. - Operate our marketplace GTM platform (Suger today) and extend referral and offer automation so sellers can transact through Marketplace without partnerships-team involvement. Programs and funding - Operationalize AWS funding mechanisms across the team: MDF (market development funds for co-marketing), proof-of-concept credits, ISV Accelerate benefits, and any strategic collaboration funding we secure. - Pursue AWS competency and specialization programs that strengthen our positioning with AWS sellers. - Track funding drawn down against funding available and report it monthly. Executive and partner relationships - Own LangChain's working relationships at AWS: partner development managers, ISV sales managers, Marketplace category leads, and the Bedrock and AgentCore partner teams. - Build executive sponsorship on both sides, and run a joint business plan with AWS that sets shared goals and a review cadence. - Navigate the coopetitive dynamic: partner closely with AWS on Bedrock and AgentCore while differentiating LangGraph and LangSmith where AWS has competing offerings. Field enablement and marketing - Equip LangChain sales, solutions engineering, and marketing with better-together messaging, competitive positioning, and joint sales plays for AWS accounts. - Partner with marketing on co-branded campaigns, content, and events that generate pipeline, including re:Invent, AWS Summits, and joint customer programs. - Communicate results clearly to internal stakeholders, including a monthly readout on pipeline, Marketplace, and program activity. WHAT YOU'LL BRING - 6+ years in cloud alliances, partner sales, or business development, with direct, hands-on ownership of an AWS relationship. - A track record of scaling a hyperscaler co-sell motion, not just starting one: you have taken a working AWS alliance to materially higher Marketplace share, pipeline, or partner-sourced revenue, and you can describe the mechanisms that got you there. - Deep working knowledge of AWS Marketplace transactions and programs: private offers, CPPO, ACE, ISV Accelerate, and the funding programs available to ISVs. - Experience operating a marketplace GTM platform such as Suger, Tackle, or WorkSpan, including referral and offer automation. - Experience shaping and running a joint business plan with a hyperscaler, including executive sponsorship on both sides. - Enough technical foundation to speak credibly with builders. You do not need to write code, but you need to understand how LangGraph, LangSmith, and LangChain fit into a customer's AWS stack. - Experience in a startup or high-growth environment where you set the operating rhythm for a partner motion rather than inheriting one. - Strong operational discipline: you manage pipeline in the CRM, track partner activity, and report results clearly to internal stakeholders. - Excellent communication and relationship-building skills, with comfort owning senior relationships at a large cloud organization and resolving conflict constructively across company lines. NICE TO HAVE'S - Prior experience inside AWS in partner sales, ISV, or Marketplace roles, with a working understanding of how co-sell decisions and seller compensation work internally. - Experience with commercial contracts with AWS like SCAs. - Existing relationships across the AWS ISV, field, Marketplace, and Bedrock partner teams. - Familiarity with the AI/ML ecosystem: how LLMs, agents, and developer tooling fit into enterprise stacks. - Experience with AWS partner programs specific to AI and data, such as the Generative AI Competency and related partner tracks. - Prior experience at a developer tools or infrastructure company with a product-led growth motion. Annual salary range: $200,000 - $250,000 OTE + Equity 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.

Reddit10 дн назад

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Infrastructure Engineering team enables Reddit to deliver Reliability, Performance, and Efficiency, with a single opinionated technology stack. We empower Reddit developers by delivering a reliable, scalable, and automated foundation - unifying compute, seamless deployments, robust storage, and high-performance messaging to maximize developer velocity and system resilience. This centralized role hires across several high-impact teams, including: Messaging: Delivers a reliable, performant, and efficient platform to support asynchronous communication across all products and services at Reddit. Site Defense: Builds platforms that detect and mitigate bots, scraping, and abusive traffic while preserving a reliable experience for legitimate users across Reddit. Infrastructure Security: Builds platforms for service identity, secrets management, and secure access that make Reddit’s infrastructure secure by default. What You’ll Do Cross-Functional Product Architecture: Partner closely with Product Management, Product Design, Data Science, and Client Engineers (iOS/Android/Web) to translate business and user needs into reliable, low-latency technical solutions. End-to-End Delivery: Own the full software lifecycle for major product initiatives from technical design docs and API contracts to development, testing, rollout, and observability. Metrics & Experimentation-Led Engineering: Design, build, and evaluate A/B experiments. Work with tools like BigQuery, HEX, or Firebase to analyze user behavior, conversion funnels, and retention loops to make data-backed engineering decisions. API & System Performance: Build and maintain scalable APIs (GraphQL, REST, gRPC) and distributed backend services optimized for client consumption and consumer UI performance. Technical Rigor & Modern Tooling: Establish engineering best practices, improve developer workflows, mentor teammates, and use modern, AI-integrated tools to ship high-quality products efficiently. In your day-to-day, you will: Steer: Work with the team to select, scope, and drive high leverage projects that align with Reddit’s goals. Build: Execute on a strategy and create a more performant, more scalable, higher quality architecture around authentication, authorization and identity. Amplify: Mentor, coach, and collaborate with other technical contributors Collaborate: Work together with a variety of cross functional teams across Reddit Engineering. Evolve: Learn and improve your own technical and non-technical abilities Who you might be: 3+ years of experience building internet-scale software, preferably with a focus on distributed systems infrastructure or infrastructure security. Software development experience in one or more general purpose programming languages; Golang, Python, C++, Java Experience with essential cloud infrastructure (Kubernetes, CI/CD, AWS, GCP) Hands-on experience implementing features, optimizations, and bug fixes to distributed messaging systems. Excellent communication skills to collaborate with stakeholders in engineering, data science, machine learning, and product. Degree in Computer Science or equivalent technical field. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $164,000 — $229,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

PlayStation Global10 дн назад

Software QA Engineer 2

PlayStation Global10 дн назад

Sr. Director, Strategic Development

Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Director, Strategic Development Position Overview Sony Interactive Entertainment is entering an important new chapter in its evolution looking to expand business and identify future growth opportunities. This is a senior leadership position for an individual who combines exceptional strategic judgment with the ability to activate change across complex, highly accomplished organizations. The successful candidate will help SIE move beyond strategy as an annual planning exercise toward a continuous discipline of strategic choices, organizational alignment, experimentation, and measurable business outcomes. Working directly within the Business Strategy team alongside senior leaders across PlayStation, this individual will build the frameworks, decision mechanisms, and leadership practices that enable executives to own the outcomes of the company's strategic evolution. The central purpose of this role is not simply to develop strategy. It is to help the organization become better at continuously making, activating, and adapting strategic decisions. Key Responsibilities Activate PlayStation's Strategic Transformation Translate PlayStation's long-range strategic direction into clear, actionable enterprise priorities that connect the company's existing strengths with future growth opportunities. Help operationalize the strategic shifts defining PlayStation's evolution, including developing new value propositions, driving business model adaptation to new customers and opportunities and moving from periodic planning to continuous strategic adaptation. Establish practical frameworks that clarify what SIE must preserve, evolve, and newly develop over the next three to five years. Partner with functional executives to translate enterprise strategy into meaningful choices, commitments, and measurable outcomes within their organizations. Identify structural, cultural, and operational barriers to transformation and help leadership teams address them. Activate the strategy by embedding it within cross functional leaders to own it and adapt it as assumptions change. Establish Continuous Strategic Planning and Adaptation Build a strategy capability that operates throughout the year, responding to market shifts, emerging technologies, competitive developments, and organizational learning. Design and implement a continuous strategy operating rhythm, connecting three-to-five-year ambitions with annual priorities, quarterly strategic reviews, and ongoing opportunity assessment. Develop scenario-planning, strategic sensing, and portfolio-evaluation frameworks that allow leadership to anticipate change rather than simply respond to it. Connect insights from product, commercial, finance, technology, studios, and external partners into an evolving view of PlayStation's future. Create the right level of materials for decision-oriented executive forums and then orchestrate those important meetings to find emerging opportunities, challenge assumptions, and recommend adjustments to strategic priorities. Build mechanisms for leaders to revisit investment assumptions and reallocate attention and resources as evidence changes. Influence and Mobilize Cross-Functional Executive Leadership Serve as a trusted strategic partner to senior leaders, bringing together different perspectives and enabling collective decisions on issues that transcend individual business units. Build trusted relationships with VP- and SVP-level leaders across PlayStation and Sony Group. Facilitate high-stakes strategic conversations involving competing priorities, resource constraints, and differing perspectives on the future. Use rigorous analysis (both internal and external), commercial judgment, and compelling narratives to influence decisions without relying on formal authority. Help executive teams move from conceptual agreement to explicit decisions, accountable ownership, and coordinated action. Challenge established assumptions constructively while demonstrating respect for the achievements and operational realities of existing businesses. Identify and resolve strategic misalignment before it becomes an impediment to execution. Develop the Core / Explore Strategic Framework Support the development of two distinct but interconnected operating models that allow PlayStation to maximize current business performance while investing in future opportunities. Establish differentiated frameworks for evaluating core-business optimization and higher-uncertainty exploration initiatives. Help define how future opportunities are identified, validated, incubated, prioritized, and transitioned into scaled operating businesses. Partner with Finance and operating leaders to develop portfolio-level investment frameworks that balance near-term returns with longer-term strategic value. Create transparent decision criteria for advancing, redirecting, or discontinuing strategic initiatives. Ensure exploration activities are commercially grounded without subjecting early-stage opportunities to inappropriate mature-business performance expectations. Support leadership in determining where shared capabilities, resources, and partnerships can accelerate both operating systems. Strengthen Enterprise Strategy Execution and Organizational Capability Create repeatable approaches that allow SIE leaders to turn strategic direction into coordinated organizational progress. Develop executive-level strategy activation frameworks, including strategic outcome maps, decision rights, leadership commitments, and progress measures. Partner with team members to create processes for translating strategic choices into functional priorities without creating unnecessary reporting or bureaucracy. Facilitate leadership working sessions that resolve trade-offs and create durable ownership of agreed outcomes. Build strategy toolkits and practical methodologies that functional teams can adopt independently. Capture and institutionalize lessons from strategic initiatives, including successes, unsuccessful experiments, and changing market assumptions. Introduce AI-enabled research, synthesis, scenario modeling, and knowledge-management capabilities that increase the speed and quality of strategic work. Required Experience and Qualifications The ideal candidate will bring 15+ years of progressive experience in enterprise strategy, business transformation, corporate development, strategic operations, or product leadership, including substantial experience influencing senior executives within complex global organizations. A proven record of leading enterprise-wide strategic transformation, with tangible examples of changes adopted by business leaders and sustained beyond the initial initiative. Deep experience influencing cross-functional leadership teams, particularly in situations involving ambiguous authority, competing priorities, and significant organizational complexity. Demonstrated success designing and implementing strategic planning, portfolio management, or governance frameworks that improved actual business decisions. Experience in technology platforms, gaming, digital entertainment, consumer ecosystems, or similarly dynamic industries. Strong commercial and financial judgment, including the ability to evaluate investment trade-offs, growth opportunities, and long-range enterprise value. Exceptional executive communication, facilitation, and strategic storytelling capabilities. Experience navigating global organizations and multicultural leadership environments. Demonstrated ability to use emerging AI and analytical capabilities to improve strategic effectiveness. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $275,000 — $412,400 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Harvey10 дн назад

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Harvey10 дн назад

Location: London Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Harvey10 дн назад

Location: Remote Workplace: Remote WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Harvey10 дн назад

Solution Architect-North Central

Location: New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

ClickHouse10 дн назад

Solution Architect-Texas

Location: Dallas; Austin; Houston Workplace: Remote THE ROLE As an Enterprise Solutions Architect at ClickHouse, you'll own the technical side of the sales cycle for enterprise accounts in Texas. This role serves our Enterprise segment in Texas, and the ideal candidate would be based in Austin or Dallas. You'll engage with data platform engineers, architects, SRE, and the VP who owns the standard - and your job is to design something that satisfies all of them and then prove it at production scale. Getting an enterprise team there usually means moving them off something else, so most of your work is making that migration credible: the architecture, benchmarks run against their own data, and a plan their engineers believe they can execute. This is a role for engineers who want the hard version of the problem: real scale, real constraints, and an incumbent to displace. Prior pre-sales experience helps but isn't required - technical depth is non-negotiable. WHAT YOU WILL BE DOING - Own the technical evaluation for enterprise accounts - from discovery through POC or competitive bake-off, architecture sign-off, security review, and first production workload. - Engage across a wider set of stakeholders than a single team: data platform engineers, architects, SRE, security, and the executive who owns the standard. Design solutions that hold up with all of them in the room. - Design for production scale - sizing, sharding and replication strategy, ingestion topology, tiered storage, cost modeling, and what happens when something fails at 3am. - Win competitive displacements against Elasticsearch, Splunk, Snowflake, BigQuery, Druid, Pinot, and homegrown systems, using benchmarks the customer's own team can reproduce. - Own the migration plan - sequencing, dual-run, validation, and cutover - so the customer's team can see exactly how they get to production. - Clear the security and procurement path: questionnaires, compliance artifacts, network and identity architecture, and BYOC or private deployment requirements. - Partner closely with Enterprise AEs to progress and close opportunities - you own the technical win, they own the commercial close. Build the TCO case against the incumbent/competition together. - Advocate for customer needs internally with Product and Engineering - you're the voice of the technical buyer inside ClickHouse. - Contribute reference architectures, benchmark harnesses, migration guides, and objection handling material that help the team scale what's working. WHAT YOU BRING - Deep technical foundation in data infrastructure - built through experience as a data engineer, platform engineer, software engineer, DBA, or solutions architect. - Production experience with analytical databases (ClickHouse, Snowflake, BigQuery, Redshift, Druid, Pinot, Vertica) and with operating them, not just querying them. - Distributed systems judgment: partitioning, replication, consistency trade-offs, query execution, and a felt sense for where things break under load. - Fluency across the modern data stack - Kafka and CDC pipelines, orchestration, object storage, BI tools, and at least one major cloud (AWS, GCP, Azure) at architecture level. - Experience running a technical evaluation against a named competitor and winning it, including designing the migration off the incumbent and the parts of it that are genuinely hard. - Customer-facing experience with real stakes - pre-sales, consulting, technical account management, or a staff-level engineering role that put you in front of customers. - Strong written and verbal communication. You can whiteboard with a staff engineer in the morning and present to a VP of Engineering in the afternoon. - Comfort with longer cycles and more stakeholders. Enterprise evaluations don't close in three weeks, and you know how to keep one moving without letting it stall. - Willingness to say ClickHouse isn't the right tool for a given workload when that's true. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

ClickHouse10 дн назад

Location: Chicago; Minneapolis Workplace: Remote THE ROLE As an Enterprise Solutions Architect at ClickHouse, you'll own the technical side of the sales cycle for enterprise accounts in the North Central United States. This role serves our Enterprise segment across the North Central region, and the ideal candidate would be based in Minneapolis or Chicago. You'll engage with data platform engineers, architects, SRE, and the VP who owns the standard - and your job is to design something that satisfies all of them and then prove it at production scale. Getting an enterprise team there usually means moving them off something else, so most of your work is making that migration credible: the architecture, benchmarks run against their own data, and a plan their engineers believe they can execute. This is a role for engineers who want the hard version of the problem: real scale, real constraints, and an incumbent to displace. Prior pre-sales experience helps but isn't required - technical depth is non-negotiable. WHAT YOU WILL BE DOING - Own the technical evaluation for enterprise accounts - from discovery through POC or competitive bake-off, architecture sign-off, security review, and first production workload. - Engage across a wider set of stakeholders than a single team: data platform engineers, architects, SRE, security, and the executive who owns the standard. Design solutions that hold up with all of them in the room. - Design for production scale - sizing, sharding and replication strategy, ingestion topology, tiered storage, cost modeling, and what happens when something fails at 3am. - Win competitive displacements against Elasticsearch, Splunk, Snowflake, BigQuery, Druid, Pinot, and homegrown systems, using benchmarks the customer's own team can reproduce. - Own the migration plan - sequencing, dual-run, validation, and cutover - so the customer's team can see exactly how they get to production. - Clear the security and procurement path: questionnaires, compliance artifacts, network and identity architecture, and BYOC or private deployment requirements. - Partner closely with Enterprise AEs to progress and close opportunities - you own the technical win, they own the commercial close. Build the TCO case against the incumbent/competition together. - Advocate for customer needs internally with Product and Engineering - you're the voice of the technical buyer inside ClickHouse. - Contribute reference architectures, benchmark harnesses, migration guides, and objection handling material that help the team scale what's working. WHAT YOU BRING - Deep technical foundation in data infrastructure - built through experience as a data engineer, platform engineer, software engineer, DBA, or solutions architect. - Production experience with analytical databases (ClickHouse, Snowflake, BigQuery, Redshift, Druid, Pinot, Vertica) and with operating them, not just querying them. - Distributed systems judgment: partitioning, replication, consistency trade-offs, query execution, and a felt sense for where things break under load. - Fluency across the modern data stack - Kafka and CDC pipelines, orchestration, object storage, BI tools, and at least one major cloud (AWS, GCP, Azure) at architecture level. - Experience running a technical evaluation against a named competitor and winning it, including designing the migration off the incumbent and the parts of it that are genuinely hard. - Customer-facing experience with real stakes - pre-sales, consulting, technical account management, or a staff-level engineering role that put you in front of customers. - Strong written and verbal communication. You can whiteboard with a staff engineer in the morning and present to a VP of Engineering in the afternoon. - Comfort with longer cycles and more stakeholders. Enterprise evaluations don't close in three weeks, and you know how to keep one moving without letting it stall. - Willingness to say ClickHouse isn't the right tool for a given workload when that's true. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

JAYA TALENT10 дн назад

Lead Inference Engineer (AI)

RELOCATION TO UAE | JAYA TALENT Abu Dhabi 🇦🇪 can be remote for 3 months, with relocation after Office-based, few times per week Senior / Tech Lead level Build and scale high-performance AI inference with a sharp, fast-moving team!

ГибридseniorLEAD INFERENCE ENGINEER (AI) | RELOCATION TO UAE | JAYA TALENT #relocation #uae #fulltime #itjob https://teletype.in/@remoteit/wvFM4E18No4; RELOCATION TO UAE | JAYA TALENT Abu Dhabi 🇦🇪 can be remote for 3 months, with relocation after Office-based, few times per week Senior / Tech Lead level Build and scale high-performance AI inference with a sharp, fast-moving team!

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