Вакансии

Location: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team. Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.   The team You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business. Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.   Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for - A track record of designing, shipping and operating production-grade backend systems at scale - Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences - A coaching mindset and the ability to set engineering standards and mentor other engineers Nice to have - Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)   Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Agtonomy is looking for a Robot Operations Engineer to investigate field issues, monitor robotic fleets, automate operations, manage configurations, and support autonomous tractor site launches.

Location: New York, NY (HQ); San Francisco, CA Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT RAMP LABS Ramp Labs is Ramp's AI research group. We post-train models on finance work, build the environments and evals they learn from, and ship them into the products 70,000+ companies use to move money. We think the defensible part of an AI product is the loop: proprietary environments, evals that track what customers care about, and models trained against both. ABOUT THE ROLE Every model decision at Ramp Labs runs through a benchmark. Which model to route to. Whether a post-training run worked. Whether an agent is ready to post a corrective journal entry to a customer's ledger without a human in the loop. You'll own Ramp's benchmarking effort. You'll turn real finance work (expense policy review, invoice coding, month-end close, spreadsheet Q&A) into benchmarks and RL environments, build the graders, and tell the team what is actually improving. WHAT YOU’LL DO - Build benchmarks from real workflows: turn agent traces, customer edge cases and expert labels into versioned benchmark suites for long-horizon agents that run for hours across tools and systems, plus tool use, multi-step reasoning and financial judgment - Own the benchmarking effort: decide what we measure, run benchmark suites across models and agent versions, and report results the team makes decisions on - Design graders: rubrics, programmatic checks and llm-as-judge, calibrated against human agreement, with a clear view of where each one breaks - Close the loop with post-training: turn evals into reward functions and RL environments, and catch reward hacking and contamination before they ship - Publish external benchmarks and write-ups on how models perform at real finance work WHAT YOU NEED - Hands-on experience building LLM benchmarks or evals that people used to make real decisions - Strong Python and software engineering; your eval code is reproducible and fast - Statistical judgment: variance, confidence intervals, sample size, inter-rater agreement, and knowing when a delta is noise - Working knowledge of post-training (SFT, RL with verifiable rewards) and how evals feed into it - Comfort with SQL and large datasets; you'll work directly from production traces - Taste for what is worth measuring NICE-TO-HAVE - Industry experience on an eval, benchmarking or post-training team - Built RL environments or verifiers for agentic tasks - Published benchmark or evaluation research (NeurIPS Datasets & Benchmarks, ICML, ACL) - Built or contributed to eval frameworks (verifiers, lm-evaluation-harness, HELM or similar) - Familiarity with accounting, finance or other expert-domain work - Public work we can look at: a benchmark, an eval suite, a failure-analysis write-up BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: Remote Workplace: remote We’re hiring a Senior Systems Engineer as WRA builds its new internal IT & Cybersecurity functions. We are actively transitioning from an MSP model to a fully in-house model, and this role will operate under the guidance of our Director of Information Technology & Cybersecurity. This is also an excellent role for someone looking to refine their cybersecurity skillset.   In this role, you will act as the primary engineer for our cloud and SaaS platforms, including Microsoft 365, Azure infrastructure, Entra ID, endpoint management, and a variety of general platforms used by each of our departments. Initially, most of your time will focus on standing up new tools and assisting in the migration of select tools used by our MSP. Afterwards, your general duties will shift to engineering Azure Virtual Desktop, Microsoft 365/Entra ID, endpoint management and building automations.  You will be highly autonomous and will work closely with your Director to maintain and improve our current technology stack. Our 100-person workforce is highly distributed, and your priority is engineering our tools to enable our staff to do their best work securely, efficiently and consistently.  WRA has offices in the San Francisco Bay Area (San Rafael, Petaluma, and Emeryville) and in San Diego. This position may be performed fully remotely by candidates located in California, Colorado, Arizona, or Oregon but travel to our offices may be necessary 1 – 2 times per year on average.   Candidates in the Denver metro area are especially encouraged to apply. In this role, you will be responsible for: Cloud Infrastructure Own our Azure environment, including Azure Virtual Desktop and virtual servers, which enables our CAD, GIS and Accounting teams. This includes image management, patching, right-sizing, scaling and scheduling, backups, performance optimization, and software versioning. Deploy actionable virtual machine monitoring to measure performance (CPU, GPU, memory, disk and session latency), idle capacity and active use time, and implement alerts to monitor these metrics. Perform root-cause analysis of virtual infrastructure concerns and propose solutions. Administer our Microsoft 365 environment, including Exchange, SharePoint & OneDrive, Teams and data governance. Engage with your Director and our specialized departments to ensure their tools are appropriately sized, configured and performant. Co-manage our SaaS and cloud infrastructure backup platforms, including for Microsoft 365, Azure virtual machines and other platforms. Identity & Access Management (IAM) Administer Entra ID and SSO, including conditional access, authentication, dynamic groups, and guest access governance. Own employee identity lifecycle automations for onboarding, offboarding and role changes. Maintain SCIM provisioning across our SaaS applications. Endpoint & Mobile Device Management Manage our Windows and limited Mac fleet by administering our endpoint management platform, including device enrollment, Autopilot, compliance & configuration policies, app deployments and system patching. Manage our mobile device configuration and application policies. AI & Automations Automate IT processes using PowerShell, Microsoft Graph and other platforms to reduce or eliminate manual administrative tasks and to ensure consistent quality. Collaborate with your Director and other stakeholders to improve our implementation of Claude AI, including Connector configurations, Skills and Design. Cybersecurity Partner with your Director to build new security operations capabilities from product selection and concept trials through implementation and administration. Alongside your Director, administer our security stack, including our managed detection and response platform, email security, DNS and web filtering, and vulnerability management. Participate in our incident response process, including investigations and root-cause analyses, and apply technical containment measures as directed or delegated. Assist in strengthening our infrastructure to be compliant with industry-standard benchmarks such as CMMC and NIST SP 800-171. General IT Support Work with our IT Operations Specialist as needed and serve as a final escalation point for complex IT Support requests. Participate in an on-call rotation for critical but rare IT outages and other emergent duties. Change Management & Documentation Maintain runbooks, architecture diagrams, and system configuration documentation. Documentation must be considered a deliverable – not a “nice to have.” Follow industry-standard Change Management practices for all system changes. To be successful in this role, you will need: Experience & Location At least 6 years of direct experience supporting a hybrid or remote workforce of at least 50 employees as an engineer. Comfortable working fully remote with travel to our offices in California as described above. Able to demonstrate past history of performing duties in a high-trust role. Technical Skills Strong history of managing mission-critical Azure Virtual Desktops and application-specific servers. Deep, hands-on experience with Microsoft 365 and Entra ID, including conditional access, provisioning, identity governance and general administration. Experience managing a distributed fleet of endpoints and mobile devices using Intune, NinjaOne, WorkspaceOne or comparable tools. Proven track record of utilizing PowerShell to administer Microsoft 365 and Azure. How You Work A zero-trust security mindset demonstrated through the methods you provide IT service and engineer solutions. Excellent customer service skills and the ability to translate complex technical issues into plain language that anyone can understand. Physical Requirements Able to perform physical duties that may include lifting up to 50 lbs, climbing ladders indoors, crawling under furniture and reaching behind wall-mounted equipment. Bonus Points for experience with or having: Supporting CAD and GIS applications, such as AutoCAD, Civil 3D, ArcGIS and spatial datasets. Supporting Egnyte, Deltek VantagePoint, Elevia or markup tools like Bluebeam and Adobe Acrobat. Microsoft certifications, including (but not limited to) AZ-104, AZ-140, AZ-305, AZ-700, SC-200, SC-300, SC-401, MS-102 or MD-102. Familiarity with industry-standard frameworks, such as CMMC L1/L2, NIST SP 800-171, CCPA, SOC 2, ITSM, or ITIL. Executing platform migrations using third-party tools and/or PowerShell. Integrating IAM automations into ITSM platforms such as Jira, Freshservice, Zendesk or SolarWinds. Supporting the implementation of data retention policies. Administering UniFi Network and Protect. WRA has an established internal leveling system for our staff that maps to salary bands that have been informed by market data. Our leveling system is dependent on years of relevant industry experience, education, and the level of responsibility and autonomy at which you’re expected to operate.  We have posted a salary range that corresponds to the appropriate level for this position. In your first conversation with our recruiter, we will discuss leveling and compensation with you to make sure that our expectations are aligned.   *The salary range for this position is $130,000 – $145,000  Beyond salary, here’s how we take care of our people:  Health coverage: Medical plans through Anthem and Kaiser Permanente (options vary by state). WRA pays 100% of employee-only premiums for our base medical plans and for Guardian dental and vision. You can buy up to another plan or add a spouse, domestic partner, ordependents at your own cost.

Location: Ghent, Belgium D-ploy is an IT and Engineering Solutions company delivering services to organizations across the EMEA region and the United States. We work closely with our clients to provide reliable, secure and practical technology solutions, supported by collaborative teams and a people-focused working environment. We are looking for an experienced Cloud Engineer to join a cloud platform environment supporting a global organization in the pharmaceutical sector. In this role, you will help build, automate and operate cloud infrastructure and shared platform services used by different business and technology teams. You will work primarily within Microsoft Azure , with a strong focus on Infrastructure as Code, Terraform, Kubernetes and DevOps automation . You will collaborate with cloud architects, application and data teams, platform specialists and external partners to deliver cloud solutions that are secure, scalable and aligned with governance and compliance requirements. Your responsibilities will include: Designing, deploying and maintaining Azure infrastructure using Terraform and Infrastructure as Code principles. Supporting a broad range of Azure services across compute, networking, storage, identity, security and monitoring. Creating reusable infrastructure components, automation frameworks and standard cloud deployment patterns. Supporting application and workload teams as they onboard services to the organization's cloud platforms. Operating and maintaining shared cloud platform capabilities and ensuring they remain stable, available and performant. Supporting and troubleshooting containerized workloads running on Azure Kubernetes Service (AKS) . Contributing to platform upgrades, lifecycle activities and ongoing technical improvements. Managing GitHub repositories and supporting branching, pull-request and source-control practices. Building and maintaining CI/CD pipelines used for infrastructure and platform deployments. Identifying opportunities to automate manual processes and improve consistency across the cloud environment. Applying cloud security standards and supporting governance requirements around monitoring, tagging, cost management and compliance. Supporting audit and compliance-related activities within a regulated environment. Working closely with architects, application teams, data teams and external partners on cloud solution design and implementation. Creating and maintaining technical documentation and operational procedures. Sharing knowledge and contributing to engineering standards and best practices across the cloud platform team. Requirements At least 3 years of professional experience in Cloud Engineering, Platform Engineering, DevOps Engineering or a similar role. Strong hands-on experience working with Microsoft Azure in enterprise environments. Solid knowledge of Terraform and Infrastructure as Code practices. Practical experience with Kubernetes , ideally Azure Kubernetes Service (AKS) . Experience designing, deploying and supporting cloud infrastructure in complex organizational environments. Good understanding of cloud-native architectures and modern platform engineering approaches. Strong knowledge of Azure networking concepts such as Virtual Networks, Private Endpoints, DNS, load balancing, Network Security Groups and firewalls . Familiarity with cloud security, identity and monitoring solutions. Experience working with GitHub, source control and CI/CD processes . Previous experience supporting Kubernetes-based platforms and containerized applications. Strong analytical and troubleshooting skills with a practical approach to problem solving. An automation-focused mindset and the ability to identify opportunities to improve operational efficiency. Strong communication and documentation skills. Ability to work effectively with multiple technical teams and stakeholders. Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology or a related field, or equivalent professional experience. Valid criminal record extract, not older than three months, required. Nice to have: Experience with AWS in addition to Azure. Previous experience in pharmaceutical, biotechnology, healthcare or another regulated industry. Experience working within a platform engineering or internal cloud services team. Exposure to different workload types, including application, integration, data or AI platforms. Relevant technical certifications such as Microsoft Azure Administrator (AZ-104), Azure Solutions Architect (AZ-305), Terraform Associate or Certified Kubernetes Administrator (CKA) . Benefits Broad range of tasks and responsibilities Friendly and international working environment Professional development opportunities Referral program (“Fishing for Friends”) Company-sponsored events Is IT in your DNA?

Location: Valletta, Malta We currently have a vacancy for a System & Network Engineer fluent in English, to offer his/her services as an expert who will be based in Malta. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team on site and off site. Your tasks Design, implement, operate, and troubleshoot enterprise network and network security infrastructure across LAN/WAN environments; Implement and support routing, switching, firewalling, VPN, and network segmentation solutions; Configure and support Application Delivery Controller (ADC), load balancing, and Web Application Firewall (WAF) solutions; Participate in infrastructure projects, network upgrades, migrations, and deployment of new technologies; Maintain network documentation and support operational, security, and change management processes. Requirements Bachelor Degree in IT combined with 6 years of relevant working experience in mission-critical, high-availability and security sensitive environments; Hands-on experience in deploying and hardening on-premises infrastructure (HCI, VMware, RHEL/Windows Server, Docker/Kubernetes); Experience with enterprise networking (VLAN segmentation, firewalls, load balancers), hybrid cloud platforms (Microsoft Azure / Azure Key Vault / VNets); Experience wirh operational security (Veeam backup/DR, SIEM logging); Experience in supporting PKI / network-attached HSM integrations; Excellent command of the English language; Good command of Maltese. Benefits If you are seeking a career in an exciting and dynamic company, where you will offer your services as part of a team of a major European Institution, operating in an international, multilingual and multicultural environment where you can expect real chances to make a difference, please send us your detailed CV in English, quoting reference (SE/11/2026). We offer a competitive remuneration (either on contract basis or remuneration with full benefits package), based on qualifications and experience. All applications will be treated as confidential. EUROPEAN DYNAMICS (ED) () is a leading Software, Information and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). The company employs over 600 engineers, IT experts and consultants (around 3% PhD, 36% MSc and 53% BSc or equivalent). We design and develop software applications using state-of-the-art technology. The group generates annual revenues in the range of EURO 40 million, with an EBITDA in the range of 20%. The value of our contract portfolio exceeds EURO 250 million. EUROPEAN DYNAMICS is a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published in . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorise ED to process your personal data for the purposes of the company's recruitment opportunities, in line to the Policy. Furthermore, when providing your data, it is up to you to explicitly consent that your data can be assessed for future job openings, for as long as you do not withdraw such consent. If you do not consent, we will not be able to consider the data you provide to us for future job openings.

Location: Prague, Czechia D-ploy is an IT and Engineering Solutions company with operations throughout the EMEA region including Switzerland, Germany, Czech Republic, Austria, UK, as well as the USA. We pride ourselves on delivering innovative and superior services and solutions to numerous industry-leading clients. By building relationships and trusted partnerships within the IT community, we optimize our customer‘s IT productivity and contribute to the organization’s success and value. We are interested in talking to engaging, flexible, and solution-oriented individuals who are looking to become a part of a dynamically growing and international organization. We are focused on creating value where IT counts, join us! We are looking for an experienced full-stack software and AI engineer to build internal cybersecurity platforms and developer tools. The role combines AI-assisted development, agent harness engineering, application security, Python development, MCP server design, and AWS cloud architecture. You will use coding agents to move rapidly from requirements to working software while remaining accountable for architecture, security, quality, and production outcomes. Fast-paced delivery is expected without compromising reliability or engineering quality. Tasks and Responsibilities Deliver secure, reliable software at a consistently fast pace using Claude Code. Develop Python services, web applications, integrations, and developer tools. Design MCP servers and agent workflows. Build and tune custom AI harnesses for security scanning, including hardcoded secrets, SAST, and SCA. Review AI-generated code and validate agent outputs. Design and operate secure AWS architecture and deployment workflows. Requirements Strong production experience with AI coding agents and harness engineering. Experience designing MCP servers, tools, and agent workflows. A security engineering or application security background is strongly preferred. Professional Python development and automated testing experience. Strong cloud engineering and architecture experience, predominantly on AWS. Strong technical judgment, ownership, and communication skills. Experience building developer-facing CLI tools is an advantage. Fluent English (oral and written) Candidates must declare Criminal record extract not older than three months Benefits Broad range of activities, tasks, and projects Flexible working conditions Minimum 5 weeks of vacation Paid sick days Meal vouchers Vouchers (B-day voucher, wedding, and new born surprise) Contributions to wellness programs (multisport card) Fishing for Friends program – our referral program Refreshments in the D-ploy office Further development and professional advancement Friendly and international working environment Company-sponsored events Competitive salary and various benefits Is IT in your DNA?

Location: São Paulo, Brazil; Buenos Aires, Argentina; Bogotá, Colombia; Lima, Peru New opportunities in Latin America! 🟢 Dev.Pro is a US-based software development company helping tech companies build their products and grow their business. We’re remote-first, and we work with independent contractors in over 55 countries, so you’d be collaborating in a multicultural environment on some really interesting projects. We invite a skilled AI Engineer to join our team in building GPU-accelerated video analytics for real-time safety monitoring across large fleets and industrial environments. In this role, you’ll help design and optimize pipelines that detect and track actionable safety events in high-volume video streams. You’ll work on real-world systems that make an impact, collaborating with engineering and product teams to deliver reliable, high-performance solutions. 🟩 What's in it for you: Collaborate with top engineers on an innovative, technically challenging computer vision project Build impactful systems that enhance safety across large fleets and industrial operations Gain hands-on experience with GPU-accelerated video analytics, temporal tracking, and real-time safety monitoring ✅ Is that you? 7+ years of software engineering experience with strong backend skills 3+ years of experience shipping computer vision solutions to production Strong Python proficiency Experience with OpenCV, PyTorch, async I/O frameworks, and API integrations Hands-on experience with YOLO/Ultralytics or similar object detection frameworks Experience detecting, labeling, and tracking objects in video Solid knowledge of frame sampling, confidence thresholds, temporal filtering, and multi-camera aggregation Experience with GPU inference optimization (batching, stride, TensorRT, CUDA, quantization, throughput tuning) Ability to communicate and collaborate effectively with engineering and product teams Upper-Intermediate+ English level Desirable: Experience with Azure Event Hub, Blob Storage, Application Insights, or similar Familiarity with Docker, cloud deployments, and production monitoring systems Experience in temporal/sequence analysis for event detection Experience with video analytics in safety, compliance, or industrial/transportation environments 🧩 Key responsibilities and your contribution In this role, you’ll develop and maintain robust backend solutions that process video data and deliver actionable insights using pre-trained computer vision models. Develop and optimize GPU-accelerated video inference pipelines for real-time processing Implement, evaluate, and improve object detection models (YOLO or similar) Build temporal smoothing and tracking logic for safety event detection Optimize model performance using TensorRT, ONNX, CUDA, and GPU profiling tools Build and maintain integrations with event-driven APIs, Azure Event Hub, Blob Storage, and internal services Add metrics, logging, telemetry, and fail-safe mechanisms for resilient inference jobs Contribute to dataset curation, labeling, and model evaluation; fine-tuning/training as needed Support containerized deployments (Docker) and assist with monitoring and scaling production workload Our next steps: ✅ Submit a CV in English — ✅ Intro call with a Recruiter — ✅ Interview — ✅ Signing the Contract Interested? Find out more: 📋 How to Join Us 💻 LinkedIn Page 📈 Our website 💻 IG Page By submitting application, I've read and agree to the Dev.Pro Private Policy and Consent on Processing of Personal Data . I agree to have my Personal Data being stored and processed by Dev.Pro.

Location: Jakarta, Indonesia; Kuala Lumpur, Malaysia Eram Talent, an ISO 9001:2015-certified division of Eram Group, delivers human resources, industrial projects, and maintenance services across a broad range of sectors, including oil and gas, petrochemicals, power, infrastructure, water, mining, healthcare, and IT. Within the oil and energy space, the company supports complex industrial operations with practical engineering expertise and a strong focus on quality, safety, and project delivery. This role offers the opportunity to contribute to technically demanding energy projects where strong process engineering judgment can make a measurable impact. As a Process Design Engineer, you will support the development and improvement of plant systems, working across engineering disciplines to help shape efficient, safe, and reliable process solutions for industrial facilities. If selected, the work location would be onsite at Saudi Arabia . Responsibilities Develop process designs, simulations, and engineering studies for energy projects. Deliver FEED and detailed engineering packages for plant modifications. Lead HAZOP reviews and ensure compliance with safety requirements. Identify debottlenecking opportunities across brownfield and greenfield facilities. Coordinate multidisciplinary teams throughout project planning and execution. Requirements Required Qualifications Bachelor’s degree in Chemical Engineering, Process Engineering, or a related field. 7+ years of experience in process engineering or plant operations, including hands-on work in process design and process simulation. Experience leading or participating in HAZOP reviews and delivering FEED and detailed engineering packages. Track record of identifying or executing debottlenecking initiatives across brownfield and greenfield projects. Proficiency with data analysis and process simulation software such as Aspen Plus and HYSYS. Strong knowledge of gasification processes, power production, and related technologies, along with safety and environmental regulations such as OSHA and EPA standards. Experience with process optimization methodologies, including Six Sigma and lean manufacturing. Experience managing projects across planning, budgeting, and execution. Experience leading multidisciplinary teams, preparing engineering reports, and coordinating effectively with cross-functional stakeholders. Preferred Qualifications Master’s degree in Engineering or Management. Experience in industries such as petrochemical, refining, gas processing, chemical manufacturing, gasification facilities, fertilizer plants, power generation plants, or large industrial utility operations. Holding a Six Sigma, Lean Manufacturing, or PMP certification.

Location: US, Boston, MA Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE As our Engineering Lab Manager, you'll be the backbone of our hardware lab — keeping it organized, stocked, and running smoothly so our engineers can focus on building. This is a hands-on, highly visible role in a small, fast-moving office of around 30 engineers working on cutting-edge humanoid robotics. This is a great opportunity for someone with a hands-on technical background who wants to grow inside a robotics company at an early and exciting stage.   WHAT YOU’LL DO - Own lab organization — maintain a clean, safe, and well-organized lab environment. Keep workbenches, storage, and shared spaces in order so the team can work efficiently. - Engineering inventory management — track and restock components, consumables, tools, and lab equipment. Own the procurement process for day-to-day lab needs, working with vendors and internal stakeholders to keep things moving. Kit parts for engineering builds and repairs. - Support hardware and equipment — assist engineers with equipment setup, basic maintenance, and calibration of lab tools including oscilloscopes, power supplies, soldering stations, and test fixtures. Flag equipment issues and coordinate repairs or replacements. - Facilitate general lab operations — coordinate deliveries, manage lab access, support onboarding of new team members to lab tools and processes, and help enforce lab safety policies. - Support the team day-to-day — pitch in where needed across a small, busy engineering team. This might mean helping set up a demo, organizing a shipment, or sourcing a hard-to-find component quickly. WHAT WE’RE LOOKING FOR - Hands-on experience in an electronics, engineering, or hardware lab environment — through work or school. - Demonstrated experience managing physical inventory: receiving, tracking, reorder thresholds, vendor coordination in a lab, warehouse, makerspace, or production environment. - Familiarity with component and inventory management tools or systems - Comfort handling and organizing electronic components, PCBAs, cables, and lab equipment - Expertise with ESD handling protocols for sensitive electronic components and assemblies. - Strong attention to detail and a natural tendency to keep shared spaces organized and functional - Strong communication skills and comfort working closely with technical teams - Ability to manage multiple tasks and priorities in a fast-moving environment - This role requires the ability to lift and carry equipment and materials weighing up to 40 lbs as part of regular lab duties NICE TO HAVE - Experience with basic soldering, rework, or electronics assembly - Exposure to robotics, electromechanical systems, or a hardware startup environment - Comfort using tools like Notion, Jira, or similar for tracking and documentation. - Experience with PLM tools, such as TeamCenter or Arena. For this role in Massachusetts, the expected base salary range is $65-85K USD per year; your placement in that range depends on how your experience maps to our internal leveling.

Location: Chicago, New York City, London DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. Our Unified Platform (UP) organization builds and offers managed data services, shared infrastructure, and metadata management systems that underpin our common query layer and power batch and streaming pipelines that power teams across DRW. As a Staff Engineer focused on the Data Platform , you will bring experience scaling data platforms to shape and uphold DRW’s long-term data platform vision, translating data strategy into engineering products and managed services used by Traders, Quantitative Researchers, and Back-Office personnel. You will work across tooling, producer, and consumer teams to connect business priorities with technical direction and hands-on delivery. This is an individual contributor role combining strategic thinking, architectural leadership, software development, and mentorship, with responsibility for technical initiatives that span teams. Key Responsibilities Contribute to and uphold the overall vision for DRW’s Data Platform, guiding its architecture and evolution to advance the firm’s data strategy. Work with engineering leads , product managers , and stakeholders to understand business priorities and translate data strategy into engineering products, platform capabilities, and contribute to the sequenced technical roadmap. Design , guide, and build managed platform services for data storage, distributed query execution, batch and streaming processing, and workload orchestration, owning their lifecycle from provisioning and upgrades through production support , refining the managed offers from direct user feedback. Lead delivery across team boundaries, turning ambiguous requirements into practical designs and measurable outcomes while balancing immediate business needs with long-term platform goals. Drive architecture reviews and technology decisions, documenting trade-offs and building consensus around patterns that uphold the platform vision across the data ecosystem. Own the strategy for large-scale data governance and b uild platform capabilities for metadata management, discovery, lineage, schema evolution, and data qua lity. Partner with security and data stakeholders on access controls and usage tra cking. Troubleshoot distributed systems, contribute to production support and incident response, and drive lasting improvements through root-cause analysis, automation, and operational documentation. Mentor engineers across teams through design reviews, code reviews, and hands-on collaboration, strengthening engineering practices and helping others take ownership of complex systems. Required Qualifications Extensive experience designing, building, and operating large-scale, data-intensive distributed systems , including technical leadership of initiatives spanning multiple teams. Experience coordinating with engineering leadership to accelerate team- and organization-wide delivery within existing processes and practices. A track record of translating data or business strategy into engineering products and technical roadmaps, with the judgment to align near-term delivery with a long-term platform vision. A track record of building and offering managed platform services to other teams, owning provisioning, upgrades, reliability, and ongoing support throughout the service lifecycle , working directly with users to incorporate their requirements and feedback into product and roadmap decisions. Experience scaling metadata management systems, such as data catalogs or lineage tracking systems , that span multiple storage and compute technologies . Expertise in Java and/ or Python, with a proven ability to deliver high-quality, maintainable production software, and strong familiarity with SQL and Linux environments. Deep understanding of distributed systems trade-offs, including consistency, fault tolerance, concurrency, partitioning, and recovery from partial failures. Production e xperience building both batch and stream processing systems at scale , demonstrating practical knowledge of state management, replay, backpressure, and delivery guarantees. Experience deploying data processing and query technologies such as Flink, Spark, and ClickHouse , and the ability to guide platform us ers on the performance and operational trade-offs among them. Experience with multiple storage technologies, including object storage, relational or NoSQL databases, and event streaming systems such as Kafka . In-depth k nowl ed ge of the internals of open table formats such as Iceberg or Delta Lake. Extensive e xperience with data modeling, schema governance and evolution, and formats and serialization systems such as Arrow, Parquet, Protobuf , or Avro. Familiarity with building and operating cloud-native data infrastructure, including Kubernetes, workflow orchestration, automated deployment, and production monitoring. Excellent written and verbal communication skills, with the ability to communicate a technical vision, explain trade-offs, align stakeholders, and lead through influence across a globally distributed organization. Strong technical judgment and problem-solving skills, with the ability to prioritize competing needs, deliver incrementally in a fast-paced trading environment, and develop other engineers. Desirable Qualifications Experience scaling managed data services across teams with different workloads, service expectations, and operational constraints. Hands-on knowledge of data governance in regulated environments. Familiarity with financial datasets and the needs of trading, quantitative research, or back-office users. The annual base salary range for this position is $200,000 to $275,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . [#LI-Insert Recruiter Initials Here1]

Location: United States Workplace: Remote Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We’re looking for a Senior Infrastructure/SRE Engineer to improve the reliability and stability of the customer-facing production infrastructure behind Webflow’s Convert pillar. Convert owns a suite of products that give marketing and growth teams the tools to experiment, personalize, and drive real revenue from their web presence, including Webflow Analyze, Optimize, AEO, and Campaigns. As tens of thousands of projects launch on Webflow each month, you’ll help keep the platform secure, scalable, and dependable for the people who rely on it. Much of what Convert delivers depends on data: high-volume event ingestion, real-time and analytical data stores, and pipelines that turn visitor behavior into reporting, experiments, and personalization. You’ll own the reliability, performance, and cost of this data infrastructure, including streaming and batch pipelines and analytical databases. You’ll set SLOs, build observability, plan capacity, and make sure data stays fresh, accurate, and available as volume grows. The next chapter is ambitious. We’re serving some of the world’s largest enterprises and rethinking what an AI-native conversion platform can be. You’ll work across a large, revenue-generating system, partner with the engineers who build on it, and help decide how it needs to evolve.   About the role: - Location: Remote-first (USA and Argentina) - Permanent - Exempt - United States (all figures cited below are in USD and pertain to workers in the United States) - Zone A: $187,500 - 225,000 - Zone B: $176,700 - 212,000 - Zone C: $165,000 - 198,000 - Application Information: - Application deadline: applications accepted on an ongoing basis until position is closed and filled - This posting is for a new position. As a Senior Infrastructure/SRE Engineer on the Convert pillar, you'll: - Own and evolve the cloud infrastructure behind the Convert products, including compute, serverless, networking, and cloud operations on AWS. - Build and maintain our infrastructure-as-code foundation in Pulumi, and evolve the patterns and shared components other teams build on. - Improve scalability and reliability of distributed, event-driven systems, including our Druid, MongoDB, and Airflow workloads, with a focus on low latency. - Make observability the foundation of how we operate. Improve the dashboards, alerts, and SLOs for the systems you own so we catch issues before customers notice, and on-call pages are actionable instead of noisy. - Lead projects from design through launch that move team and engineering org goals. - Write and review maintainable, tested, performant code and automation, and raise the quality bar for the team. - Build AI-powered automation, from policy-as-code and drift detection to LLM-assisted runbook generation, and use AI tools in your daily work. - Help the team build reliable systems. ABOUT YOU Requirements: - BA/BS degree or equivalent experience - Business-level fluency to read, write and speak in English You’ll thrive as a Senior Infrastructure/SRE Engineer if you: - Have 5+ years owning and operating cloud infrastructure in a customer-facing environment with little tolerance for downtime. You come from infrastructure, SRE, or cloud engineering with a love of automation and code, or from software engineering with a deep interest in cloud infrastructure and distributed systems. - Have deep hands-on experience with AWS and a clear view of what good cloud operations look like. - Have used infrastructure as code (Pulumi or Terraform) and prefer changes made through code, not consoles. - Have operated high-throughput, data-intensive distributed systems in production, such as Druid, MongoDB, or Airflow, and understand scalability, fault tolerance, consistency trade-offs, and performance tuning. - Are fluent in Python or TypeScript/Node.js for automation and tooling, and can read and work in Java services. - Treat observability as the basis of operations: you design SLOs, dashboards, and alerts so that issues surface before customers notice and pages are actionable. - Handle incidents well, including on-call and blameless postmortems, and fix the root causes behind them instead of just closing tickets. - Want to improve developer productivity, with CI/CD, tooling, and paved paths that let product engineers ship without owning infrastructure. It would be a bonus if you had even one of the following: - Experience with Apache Spark, Airflow, or TensorFlow. - Familiarity with Kafka or other event streaming platforms. - Experience building AI-assisted infrastructure tooling, including cost optimization loops, anomaly detection, or policy-as-code with LLM assistance. - Experience contributing to multi-region architecture including data residency, regional failover, or latency-based routing. OUR CORE BEHAVIORS - Build lasting customer trust. We build trust by taking action that puts customer trust first. - Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act. - Reinvent ourselves. We don't just improve what exists, we imagine what's possible. - Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.   BENEFITS - Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company. - Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums. - Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions. - Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired. - Wellness for the whole you. Access to mental health resources, therapy and coaching. - Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally. - Stipends to support our distributed team. Localized support for cell, Wi-Fi, and WFH expenses to help you settle into your best remote life. - Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.   Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.   BE YOU, WITH US At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.   STAY CONNECTED Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.   PLEASE NOTE: We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered. To join Webflow, you'll need a valid right to work authorization depending on the country of employment. If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes. Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.

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 systems that power how we adapt and improve leading open-weight models for legal work. 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 the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. 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

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 systems that power how we adapt and improve leading open-weight models for legal work. 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 the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. 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

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 systems that power how we adapt and improve leading open-weight models for legal work. 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 the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. 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

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 systems that power how we adapt and improve leading open-weight models for legal work. 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 the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. 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

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

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