Engineering Effectiveness Manager Jobs

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. About the role As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines. Join us in our mission to develop advanced AI systems pushing the frontiers of science and benefiting humanity. Responsibilities: Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI. Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows Collaborate to translate experimental requirements into production-ready infrastructure Develop large scale data pipelines to handle advanced language model training requirements Optimize large scale training and inference pipelines for stable and efficient reinforcement learning You may be a good fit if you: Have 6+

As an Enterprise Sales Engineer, you'll partner with Sales to help customers understand the value of Datadog and how it solves their most important technical and business challenges. You'll lead technical evaluations, deliver compelling demos, and guide customers through the journey from discovery to successful adoption. You'll act as a trusted advisor, bridging business goals with technical solutions, and play a key role in winning new business and expanding existing accounts. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the sales process in partnership with Account Executives by leading and shaping the technical strategy across opportunities from PG to Closed Won Lead customer discovery to uncover technical challenges, business goals, and success criteria, then translate those needs into tailored Datadog solutions Deliver engaging product demos, technical presentations, and workshops that connect platform capabilities to customer outcomes Project manage technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify and cultivate technical champions within customer accounts, empowering them to advocate for Datadog adoption and drive consensus internally Participat e actively in structured product and engineering field feedback sessions, serving as the technical voice of the customer to help shape product direction Maintain operational excellence by ensuring activity, deal progress, and customer interactions are accurately documented and up to date in related systems Collaborate cross-functionally with Product, Support, and GTM teams to address customer needs and resolve technical bloc

As an Enterprise Sales Engineer, you'll partner with Sales to help customers understand the value of Datadog and how it solves their most important technical and business challenges. You'll lead technical evaluations, deliver compelling demos, and guide customers through the journey from discovery to successful adoption. You'll act as a trusted advisor, bridging business goals with technical solutions, and play a key role in winning new business and expanding existing accounts. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the sales process in partnership with Account Executives by leading and shaping the technical strategy across opportunities from PG to Closed Won Lead customer discovery to uncover technical challenges, business goals, and success criteria, then translate those needs into tailored Datadog solutions Deliver engaging product demos, technical presentations, and workshops that connect platform capabilities to customer outcomes Project manage technical evaluations (POVs) end-to-end: scoping use cases and requirements, defining success criteria, building a project plan with clear timelines, and holding all participants accountable to the process Identify and cultivate technical champions within customer accounts, empowering them to advocate for Datadog adoption and drive consensus internally Participat e actively in structured product and engineering field feedback sessions, serving as the technical voice of the customer to help shape product direction Maintain operational excellence by ensuring activity, deal progress, and customer interactions are accurately documented and up to date in related systems Collaborate cross-functionally with Product, Support, and GTM teams to address customer needs and resolve technical bloc

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows. About the role As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged. Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity. Responsibilities: Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery Scaling research ideas from prototype to production Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use Implement distributed training systems and performance optimizations to support large-scale model development You may be a good fit if you: Have 8+ years of ML research experience Are

InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond. At InMobi Advertising , you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Position Summary: We look for talented Applied Scientists who can roll up their sleeves and have direct impact on our company metrics. The performance of our models and experiments a

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy ), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team. Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. Our current topics of focus include... Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Alignment Stress-testing : Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Automated Alignment Research: Building and aligning a system that can speed up & improve alignment research. Alignment Assessments : Understanding and documenting the highest-stakes and most concerning emerging properties of models through pre-deployment alignment and

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 10 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators an

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: Implement and optimize post-training techniques at scale on frontier models Conduct research to develop and optimize post-training recipes that directly improve production model quality Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation Develop tools to measure and improve model performance across various dimensions Collaborate with research teams to translate emerging techniques into production-ready implementations Debug complex issues in training pipelines and model behavior Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities Adapt quickly to changing priorities Maintain clarity when debugging complex, time-sensitive issues Have strong softwa

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas: Developing systems that enable models to use computers effectively Advancing code generation through reinforcement learning Pioneering fundamental RL research for large language models Building scalable RL infrastructure and training methodologies Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy ), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team. Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas: AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Alignment Stress-testing : Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London and travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python. Representative

About Us: YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments. Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence. We operate globally with offices in the US (NYC, Austin, Miami, Mountain View) APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery. What It’s Like to Work at YipitData: YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals. From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers. Why Top Talent Chooses YipitData: Ownership That Matters : You’ll lead high-impact projects with real business outcomes Rapid Growth : We compress years of learning into months Merit Over Titles : Trust and responsibility are earned through execution, not tenure Velocity with Purpose: We move fast, support each other, and aim high—always with purpose and intention Who Thrives Here? We hire sprinters, not coasters—people who: Choose growth over comfort Lead through challenges Are energized by high expectations It’s not for everyone, and that’s intentional. If your ambition is matched by your

About Us: YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments. Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence. We operate globally with offices in the US (NYC, Austin, Miami, Mountain View) APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery. What It’s Like to Work at YipitData: YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals. From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers. Why Top Talent Chooses YipitData: Ownership That Matters : You’ll lead high-impact projects with real business outcomes Rapid Growth : We compress years of learning into months Merit Over Titles : Trust and responsibility are earned through execution, not tenure Velocity with Purpose : We move fast, support each other, and aim high—always with purpose and intention Who Thrives Here? We hire sprinters, not coasters—people who: Choose growth over comfort Lead through challenges Are energized by high expectations It’s not for everyone, and that’s intentional. If your ambition is matched by your work ethic—and you'

エンタープライズ企業向けのセールス・エンジニアとして、プレゼンテーション、製品デモンストレーション、および技術評価（POV）において技術的な専門知識を提供します。セールスエンジニアは、お客様やパートナーとの商談におけるソリューションのfeasibilityを判断し、商談を成功に導く役割を担うとともに、お客様、競合他社、パートナーからの意見に基づいて製品チームに機能の優先順位を提案する役割も果たします。 Datadogでは、人間関係やコラボレーション、そして創造性といったオフィスカルチャーを大切にしています。 業務内容： セールスチーム、テクニカルアカウントマネージャー、CSM、その他幅広いアカウントチームと協力し、Datadogの全体的な価値提案、ビジョン、戦略をお客様に説明する トライアルフェーズ中に顧客を技術的に支援する。Datadogの価値を伝え、特定された問題や懸念事項について顧客と協力して成功に導く 高度な業界知識、技術的スキル、およびお客様との信頼関係構築を通じて複雑な案件を技術的にクローズする 潜在的なお客様に対して製品および技術ブリーフィング／プレゼンテーションを提供する 製品のフィードバックや競合状況に関して、お客様およびDatadogのビジネス／技術チームと積極的に連携し、コミュニケーションを取る 募集要項： セールス・エンジニアリング（プリセールス）または関連する役割で3年以上の経験を持つ方 AWS、Azure、またはGCPのご経験がある方 DockerやKubernetesなどのコンテナ技術に関するご経験がある方 お客様にとってビジネス上重要な課題を特定し解決することに情熱を持ち、お客様と共に評価計画を構築し実行できる方 自発的に行動し、技術に精通したプロフェッショナルで、企業のビジネス要件を容易に理解し、Cレベルの役員、技術のエキスパート、そしてその間にいるすべての人に対して、Datadogの価値と技術的な詳細を説明できる方 文書及び口頭での優れたコミュニケーションスキルを持つ方。この役割には、当社の提供するビジネス上の価値と技術的な利点の両方を理解し、明確に伝える能力 次のいずれかのプログラミング／スクリプト言語での経験を持つ方：Java、Python、Ruby、Go、Node.JS、PHP、.NETなど Datadogは、さまざまな立場の人々を大切にしています。誰もが初日から上記の資格をすべて満たすわけではないことは理解しています。それでも構いません。テクノロジーに情熱を持ち、スキルを伸ばしたいと思っている方は、ぜひご応募ください。 福利厚生と成長機会： 最高のオンボーディング 継続的な専門能力開発、製品トレーニング、キャリアパスの提供 新入社員への株式付与（RSU / 譲渡制限付株式ユニット）および従業員株式購入制度（ESPP） 社内ネットワーク構築のためのメンターおよびバディ・プログラム インクルーシブな企業文化、コミュニティ・ギルドへの参加機会 幅広く手厚い医療関連の福利厚生制度 企業型確定拠出年金（401K） 上記の内容は、就業する国やDatadogでの雇用内容によって異なる場合があります。 #LI-Hybrid About Datadog: Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram , LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datad

Scale AI is seeking a highly skilled and motivated AI Data Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows. You will: Be open to >50% onsite work in a secured space. Collaborate with cross-functional teams to define and execute the vision for data pipelines and agents. Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back. Deploy and maintain Scale software at customer sites. Develop customer requested features and work closely with them to ensure that they win customer love. Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions. Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions. This role will require at minimum an active Secret clearance and willingness to obtain a TS/SCI security clearance. Ideally you have: Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles. Prior experience developing with Python Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Unders

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) 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 position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval