Collaborateur Comptable Jobs

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for custom LLMs Upskilling and advisory services to spread the impact of AI As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Partner with public sector clients to scope, collect feedback and implement solutions for complex problems, including spending up to two weeks per month in client offices for feedback and delivery. Architect production-grade applications that integrate AI models with full-stack frameworks, managing everything from interactive UIs to backend APIs and systems. Deploy and manage infrastructure within cloud environments, ensuring the highest levels of system integrity, security, scalability, and long-term reliability. Contribute to core platform features designed to be reused across diverse international client use cases. Partner with design, product, and data teams to build robust applications aligned with the broader technical architecture. Ideally you’d have: Bachelor’s degree in Computer Science or a related quantitative field 5+ years of post-graduation, full-stack engineering experience with demonstrated proficiency in React (required), TypeScript, Next.js, Python, Node.js, PostgreSQL or MongoDB plus hands-on experience with Docker, Kubernetes, and Azure

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a hands-on RTL Design Engineer to own the microarchitecture and RTL implementation of the Power Management Subsystem/Interrupt Controllers/AXI Interconnect/Cache Controller . You’ll collaborate with cross-functional teams—architecture, firmware, software, DV, and PD—to define, design, and optimize power management solutions for next-generation RISC-V/ARM-based SoCs. This role is hybrid, based out of Bangalore, India. We welcome candidates at various experience levels. During the interview process, you will beevaluated and offered a level that aligns with your experience, which may differ from the one in this posting. Who You Are 5–10 years of experience in ASIC/SOC/IP design, with hands-on experience in microarchitecture and RTL development Skilled in Verilog/SystemVerilog and comfortable working across design, debug, and analysis Design and develop microarchitectures for a set of highly configurable IPs Microarchitecture and RTL coding ensuring optimal performance, power, area Work with verification teams on assertions, test plans, debug, coverage, etc. Deep understanding of power management concepts—clocking, reset, DVFS, and low-power modes Familiar with RISC-V or ARM-based SoCs and standard bus protocols (AXI, AHB, APB, CHI) Awareness of functional safety (ISO 26262) practices in hardware design What We Need Abil

Envoy Global is a proven innovator in the global immigration space. Our mission combines our industry-leading tech platform with holistic service to streamline, simplify and expedite the immigration process for employers and individuals. We have an exciting opportunity within Envoy Global’ s Automation Engineering team for a highly skilled QA Analyst to join us on a full-time, permanent basis. In this role, you will contribute to the design, development, and maintenance of C#-based automation frameworks using Playwright and Reqnroll/SpecFlow to support testing across web, API, and database layers. You will collaborate closely with developers, business analysts, and product teams to ensure the delivery of high-quality software through effective test automation and quality assurance practices. As our QA Analyst, you will be required to: Develop, execute, and maintain automated test scripts using C# and Playwright. Create and maintain BDD scenarios using Reqnroll (SpecFlow) aligned with business requirements. Contribute to the enhancement of automation frameworks and reusable test components. Develop and execute automated tests for UI, API, backend services, workflows, and data validations. Perform functional, regression, smoke, integration, API, and end-to-end testing. Validate backend workflows and perform SQL queries for data verification. Identify, document, and track defects while supporting root-cause analysis activities. Ensure adequate test coverage and adherence to established quality standards. Support the integration and execution of automation suites within CI/CD pipelines such as Jenkins, Azure DevOps, or GitHub Actions. Use Git for source code management and collaboration. Participate in automation code reviews and contribute to continuous improvement initiatives. Work closely with Developers, Product Owners, Business Analysts, and QA team members in an Agile/Scrum environment. Participate in sprint planning, backlog refinement, daily stand-u

Envoy Global is a proven innovator in the global immigration space. Our mission combines our industry-leading tech platform with holistic service to streamline, simplify and expedite the immigration process for employers and individuals. We are looking for a passionate Software Engineer to join our dynamic feature team in Hyderabad, India. This team works on complex technical challenges, employs creativity and constantly learns a variety of frameworks, tools and technologies. As our Software Engineer, you will be required to: Contribute to tech grooming backlog items providing design, architecture, and implementation details Quality is the key driver to successful delivery, ensure highly testable and quality deliverables Leverage troubleshooting and analytical skills to analyze issues Experience with debugging, performance profiling and optimization Develop code within C#, ASP. NET,.Net Core, Entity Framework, Web API, Typescript/ Angular To apply for this role, you should possess the following skills, experience and qualifications: Expertise in C#, Angular, ASP.NET Web API, .Net Core, Entity Framework Hands on experience with SQL Azure experience is a plus but not a deal breaker Knowledge and experience with Html, CSS, JavaScript 2 years to 4 years of strong programming experience with C# and ASP.NET Bachelor’s Degree or above Ready to code, collaborate, and create impact? Submit your updated resume and let’s start your journey with Envoy Global.!!

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. The New York Times is looking for a talented, experienced and versatile correspondent to join the tech pod on the Business desk to cover OpenAI and Anthropic as the artificial intelligence race heats up. At the core of the beat are two companies that are writing people’s futures with their fast-advancing technology and becoming the new power brokers in Silicon Valley, dealmaking, geopolitics, national security, economics and Wall Street. We are looking for an energetic, determined and collegial journalist who thrives when competing on the most compelling and important storylines. Proven success in building and cultivating sources and experience reporting on companies are prerequisites. You will work closely with other tech reporters in the United States and around the world. This is a high metabolism job, with breaking news, second-day stories, analysis, explainers, profiles, accountability stories and enterprise. You will collaborate across multiple desks and teams including finance, Audio, Video and Graphics. You will write articles, short Live updates, contribute to newsletters and videos and participate in collaborative reporting projects. This is an in-office position, based in San Francisco and includes regular attendance in the office four days each week. There may be some flexibility to work remotely per your departmental guidance. Responsibilities : You will generate original reporting on news, events and trends on Anthropic a

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. The New York Times is looking for a talented, experienced and versatile correspondent to join the tech pod on the Business desk to cover Anthropic as the artificial intelligence race heats up. Anthropic has grown quickly and changed coding, security and other areas with its technology, becoming a new power broker as it heads toward a public offering, and tangling in geopolitics, national security, economics and religion. We are looking for an energetic, determined and collegial journalist who thrives when competing on the most compelling and important storylines. Proven success in building and cultivating sources and experience reporting on companies are prerequisites. You will work closely with other tech reporters in the United States and around the world. This is a high metabolism job, with breaking news, second-day stories, analysis, explainers, profiles, accountability stories and enterprise. You will collaborate across multiple desks and teams including finance, Audio, Video and Graphics. You will write articles, short Live updates, contribute to newsletters and videos and participate in collaborative reporting projects. This is an in-office position, based in San Francisco and includes regular attendance in the office four days each week. There may be some flexibility to work remotely per your departmental guidance. This role is represented by the NewsGuild of NY. Responsibilities: You will generate original reporting on

About the role: We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems. What you'll be doing: As a Senior Backend Engineer in the AI Engineering team, you will: Build and maintain reliable, scalable backend services to support AI agent execution and orchestration. Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse. Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama. Build and maintain integrations with clinical systems (FHIR, EMR). Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse. Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes. Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems. Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities. What we're looking for: 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin). Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines. Proven experience in building and scaling backend APIs, microservices, and background jobs. Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema des

About the Role: We are looking for a Senior DevOps Engineer to join our DevOps team at K Health. You will own and evolve the infrastructure underpinning a healthcare AI platform serving patients and enterprise health system partners. This is a high-ownership role: you will architect and operate cloud environments across K Health and its enterprise partners, lead complex infrastructure migrations, drive disaster recovery programs, and help build the next generation of AI-powered operations tooling. You will also mentor junior engineers and collaborate closely with product and engineering teams across the company. This is a hybrid role based in New York City (4 days/week in office) and includes participation in a daytime on-call rotation. What you will do: Own the design, implementation, and evolution of our GKE-based Kubernetes infrastructure across K Health and enterprise partner environments. Build and maintain our Terraform modular infrastructure library, including reusable modules with automated testing, across GCP, Cloudflare, and AWS. Architect, build, and maintain GitLab CI/CD shared pipeline templates used by all engineering teams (build, test, security scanning, deployment). Own and maintain self-hosted infrastructure software running in-cluster, including GitLab, ArgoCD, Langfuse, DependencyTrack, NGINX Ingress, and others. Implement and support security and compliance controls across infrastructure and the software supply chain - secrets management, pipeline secret detection, container scanning, SOC2 and HIPAA. Drive disaster recovery readiness: design failover scenarios, author runbooks, and lead periodic DR tests. Lead development of AI-powered operations tooling and agentic infrastructure. Monitor, troubleshoot, and improve production system reliability; respond to incidents during on-call shifts. Mentor junior DevOps engineers and establish team-wide engineering standards. What we are looking for: 5+ years of experience in DevOps, platform engineering,

Opportunity Overview: As a member of the Solutions Configuration Management team you will be contributing to the analysis, documentation, implementation and maintenance of the configurations needed to enable Cohere Health solutions to meet the needs of our customers. You’ll work closely with members of the Product, Engineering, Implementation, and Testing teams to scope, document, implement and deliver configuration items (CIs) needed to meet the requirements as part of the implementation and maintenance of our solutions. What you’ll do: Own the execution of configuration deliverables for assigned projects, including client implementations and launches Analyze requirements and translate them into scalable configuration solutions Create and maintain clear documentation, including configuration specifications and standard operating procedures Collaborate with Product, Engineering, Implementation, and Testing teams to ensure configurations meet client and system requirements Validate and troubleshoot configurations in partnership with QA and testing teams Manage configuration items (CIs) throughout their lifecycle, ensuring timely and accurate delivery Required Qualifications: Must-haves 2+ years of professional experience in a Configuration role Hands-on experience working with structured data formats (JSON, XML) Familiarity with APIs Experience troubleshooting configuration issues in production or pre-production environments Experience working with ticketing systems (Jira, ServiceNow, etc.) Strong written and verbal communication skills in English, with the ability to clearly document technical configurations and decisions Experience with project management Experience with data exchange/transformation and/or integration/interoperability analysis and implementation Proven experience in Excel, including advanced functions and data analysis Knowledge of version control systems Knowledge of configuration management tools Self-starter, able to work independently, able to