What Makes a Honda, is Who makes a Honda
\nHonda has a clear vision for the future, and it’s a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of “power” that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize “the joy and freedom of mobility” by developing new technologies and an innovative approach to achieve a “zero environmental footprint.”
\nWe are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team.
\nJob Purpose: The Service Technical IT Applications unit is seeking a highly motivated, team-oriented, and customer-focused Technical Program Manager. This leadership role encompasses responsibility for overseeing programs and portfolio comprising of numerous critical applications. This position involves providing delivery and technical leadership and guiding the delivery team to ensure alignment with unit, department, divisional, and AHM business unit objectives. The Team Manager will oversee multiple projects, including business transformation initiatives utilizing modern technology and SaaS platforms for the Service division and working with global teams.
\nKey Accountabilities:
\nLead the IT team to support the Service and Planning business unit with their business application needs.
\nFoster associate development and long-term capability by teaching, coaching and mentoring, integrated with consistent and effective individual performance Management
\nAs approved annually, including schedule, budget and quality commitments
\nDesign business and technical solutions and provide solution architecture oversight.
\nBuild NA relationships and network to achieve trust and credibility, by discovering and meeting the needs of internal and external customers
\nQualifications, Experience, and Skills:
\nWorkstyle:
\nVisa sponsorship issues:
\nRelocation assistance:
\nWhat differentiates Honda and make us an employer of choice?
\nTotal Rewards:
\nCareer Growth:
\nAdditional Offerings:
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\nAs the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
\nKey Responsibilities:
\nRequired Qualifications:
\nPreferred Qualifications:
\nUS Salary Range: $254,000-$336,000 USD
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This means hiring your first partner success managers, defining how they run their portfolios, and personally carrying a portfolio of partners yourself as your reference implementation.\\n\\nYou'll be the standard for what good looks like before you ask anyone else to do it. You will also define which partners get the team's attention. Far more firms want to be a managed partner than your team could ever serve, and choosing the right ones is one of the most consequential decisions in this role.\\n\\n## Responsibilities:\\n\\n- Build and lead the Partner Success team from scratch. Hire your first partner success managers, define how they run their portfolios, and build the operating system the team inherits.\\n\\n- Personally carry a portfolio of managed partners as your reference implementation. Be the standard for what good looks like before asking anyone else to do it.\\n\\n- Decide which partners get the team's attention. Design the criteria for entry into and graduation from the managed portfolio, and reshape it as the data comes in.\\n\\n- Design the team's engagement model. Define when proactive engagement is warranted, when reactive engagement is triggered by clear signals, and when partners are better served by routing, programmatic enablement, and the certified bench.\\n\\n- Run the joint planning and business review cadence with each managed partner. Quarterly business reviews with alliance and practice leads. Joint goal-setting on customer adoption, certified architects, references, and industry positioning.\\n\\n- Drive scalable enablement across the managed partner book. Make sure partner architects are trained on new Claude capabilities as they ship, the partner's offerings reflect what Claude can now do, and the partner's bench is positioned to apply new features in their customer work at scale.\\n\\n- Drive adoption, retention, and expansion in the joint customer book. Track the health of the customer accounts each partner is serving on Claude, surface stalls early, bring the right people in to unblock, and turn at-risk accounts around.\\n\\n- Drive industry specialization across the managed partner book. Coach each partner to commit to one or more industry lanes and hold them to building real bench depth and published reference work in those lanes.\\n\\n- Steward co-investment funding decisions. Own the calls on where Anthropic puts co-investment dollars to back specific partner-led customer engagements. The bar is outcomes, not consultant hours.\\n\\n- Interlock with Anthropic's direct sales field and with the alliances organization that owns the executive relationship with each strategic partner. Define the handoffs in writing, train both sides, and hold the line.\\n\\n- Define the team's regional coverage model as the portfolio grows and hire accordingly.\\n\\n- Instrument the managed partner portfolio. Consumption growth by partner, sourced and influenced pipeline, time-to-first-deal, adoption-retention-expansion trends, and partner health trajectory.\\n\\n## You may be a good fit if you have:\\n\\n- Six to ten years of experience working with consulting and systems integration partners at a software company, cloud platform, or partner-led business, with at least two of those years managing a team.\\n\\n- Built or scaled a partner-facing team from scratch before , hiring, onboarding, methodology creation , not just managed an existing team.\\n\\n- Deep understanding of how partner success works in a usage-based business. You have held a number tied to customer behavior (adoption, retention, expansion) rather than contract signature.\\n\\n- Strong commercial instincts on partner selection and co-investment funding. You can tell which partners are worth investing in and which look impressive on paper but will not ship customer outcomes.\\n\\n- Experience running scalable partner or practitioner enablement, or the hunger to learn it. You understand the difference between a training program that gets attendance and one that changes what practitioners do in customer engagements the next week.\\n\\n- Enough technical fluency to be credible in an architecture review. You do not need to write code, but you can follow the conversation and ask the second question when a partner architect walks through how they are using Claude on a real customer problem.\\n\\n- Comfortable sharing the partner relationship with a separate alliances team that owns the executive conversation. You can work closely with them, weekly, without ego friction.\\n\\n- Use Claude or another large language model in your own daily work , not as a chat tool, but as part of how you prepare for partner reviews, draft account plans, analyze pipeline, and coach your team. We will ask you to walk us through a recent deliverable.\\n\\n## Strong candidates may also have:\\n\\n- Direct experience with global systems integrators such as Accenture, Deloitte, Capgemini, Infosys, TCS, or Wipro, and an understanding of how their delivery practices are built.\\n\\n- Working at a company in transition from product-led to partner-led motion.\\n\\n- Stewarding co-investment funding at scale and forming opinions about what works and what does not.\\n\\n- Building a vertical industry motion in which partners specialized by industry and the program rewarded it.\\n\\n- Designing an engagement model for a small team covering a large ecosystem , the proactive-reactive-automated split that lets a handful of people serve thousands of relationships.\\n\\nThe annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $300,000-$355,000 USD
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\nAbout the Team
\nWe build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.
\nMicrosoft Superintelligence Team
\nMicrosoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nThis role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!
\nResponsibilities
\nLead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.
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\nWe pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.
\nThis role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.
\nIn addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.
\nMicrosoft Superintelligence Team\nMicrosoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
\nThis role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.
\nResponsibilities\nLead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.
\nDrive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.
\nCo-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.
\nDevelop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.
\nPartner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.
\nInfluence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.
\nLead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.
\nMentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.
\nQualifications\nBachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
\nAdditional or Preferred Qualifications\nMaster’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
\nStrong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.
\nProven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. Publications, patents, or open-source contributions in systems, architecture, or ML systems are a plus.
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\nWorking closely with Applied AI Architects, Account Executives, and Anthropic's Product and Engineering teams, you'll guide startups through deep technical engagements. You'll leverage your AI engineering expertise to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable startups to succeed with Claude.
\nYou will serve as a deep technical advisor to high-potential startups, working alongside them to build innovative use cases that push the boundaries of AI. You will work hands-on with startup engineering teams: pair programming, architecture reviews, and code contributions that accelerate their development.
\nYou will develop prototypes and technical documentation—including evaluation suites, AI engineering techniques, and architecture diagrams—that enable startups to build and scale with Claude. You will collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements.
\nYou will identify patterns across engagements and contribute insights back to Product, Engineering, and the broader Applied AI team. You will create technical content for startup audiences including documentation, tutorials, and sample code. You will foster community engagement through hackathons, webinars, technical office hours, and startup-focused events.
\nYou will travel to customer sites for workshops, implementation support, and relationship building. You will be a builder credibility that earns trust with technical founders and engineering teams—you've shipped products and can speak from experience.
\nYou will have strong technical communication skills with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans. You will have experience facilitating technical workshops, hackathons, or developer-focused events. You will have passion for making powerful technology safe and beneficial.
\nThe annual compensation range for this role is £225,000 - £240,000GBP.
\nXML job scraping automation by YubHub
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