We're looking for a Machine Learning Engineer II to join our Growth Platform engineering group. As a Machine Learning Engineer II, you will be responsible for developing and implementing ML models to improve user targeting and personalization for growth initiatives. You will design and build scalable ML pipelines for data processing, model training, and deployment. You will collaborate with cross-functional teams to identify potential ML solutions for growth opportunities. You will conduct A/B tests to evaluate the performance of ML models and optimize their impact on key growth metrics. You will analyze large datasets to extract insights and inform decision-making for user acquisition and retention strategies. You will contribute to the development of our ML infrastructure, ensuring it can support rapid experimentation and deployment. You will stay up-to-date with the latest advancements in ML and recommend new techniques to enhance our growth efforts. You will participate in code reviews and collaborate with team members as needed. You will thoughtfully leverage AI tools to speed up design, coding, debugging, and documentation, while applying your own critical thinking to validate outputs and explain how you used AI in your workflow. You will shape our AI-assisted engineering practices by sharing patterns, guardrails, and learnings with the team so we can safely increase our impact without compromising code quality, reliability, or candidate expectations.
\nTo be successful in this role, you will need to have 3+ years of experience applying ML to real-world problems, preferably in a growth or user acquisition context. You will need to have excellent communication skills and the ability to work effectively in cross-functional teams. You will need to have strong problem-solving skills and the ability to translate business requirements into technical solutions. You will need to have strong programming skills in Python and experience with PyTorch. You will need to have proficiency in data processing and analysis using tools like SQL, Spark, or Hadoop. You will need to have experience with recommendation systems, user modeling, or personalization algorithms. You will need to have familiarity with statistical analysis. You will need to have experience using AI coding assistants and agentic tools as a force-multiplier, and equally comfortable solving problems from first principles when those tools aren’t available. You will need to have a Bachelor’s/Master’s degree in a relevant field or equivalent experience.
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\nReporting to the Group Product Manager (Growth Acquisition), you'll lead high-impact initiatives from ideation through delivery. You'll partner closely with Engineering, Data Science, and Marketing to build and ship a roadmap of bold changes in service of creating a best-in-class user experience for current and future Pinners.
\nKey responsibilities include:
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\nKey Responsibilities:
\nRequirements:
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\nAs an Engineering Manager, you will set technical vision, empower a talented group of engineers, and collaborate closely with Machine Learning, Product, and Data Science to unlock better user experiences.
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\nAt Pinterest, we're on a mission to bring everyone the inspiration to create a life they love. We're looking for a technical leader and engineering manager to help lead the search backend team.
\nThe search backend team is responsible for major areas of the search engine, including indexing and document ranking, query and content understanding, personalization, ML based retrieval, shopping, videos, as well as infrastructure efficiency and scalability. The team also works on innovative applications of NLP and Vision Models, and other techniques to drive query recommendations, multimodal search, agentic search, multimodal query understanding, and query based module generation and ranking.
\nResponsibilities
\nRequirements
\nIn-Office Requirement Statement
\nWe let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
\nRelocation Statement
\nThis position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
\n#LI-REMOTE #LI-DM57
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\nYou will own the product roadmap for AI platform areas, defining what we build, why, and in what order, to accelerate customer adoption of AI and ML in production. You will drive strategy for key AI platform capabilities, shaping how enterprises operationalize AI at scale.
\nYou will partner closely with engineering teams to make deeply technical decisions about ML infrastructure, from distributed training architectures to real-time serving systems. You will represent the voice of the customer by engaging directly with enterprise ML teams, translating their pain points and workflows into platform capabilities that simplify the path to production AI.
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\nYou will join a team that ships products used by thousands of the world's most sophisticated data and AI organizations. You will drive the vision and roadmap for AI platform product areas and define how customers build, train, deploy, and monitor AI and ML systems on Databricks. You will collaborate across engineering teams to deliver an integrated and powerful path from experimentation to production.
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\nYou will analyze full-funnel customer journeys across web, marketing, and CRM touchpoints, leveraging modern analytics platforms, cloud data warehouses, and A/B testing. The ideal candidate thrives in close collaboration with marketing, webstore, product, and engineering teams.
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\nAs we expand our personalization and messaging capabilities, we are looking for a foundational member of our growing team. The Offsite Recommendations Strategist owns the activation, performance, and revenue growth of our AI-powered email recommendations offering. This is a revenue-generating, client-facing role with incentive-based compensation.
\nYou will serve as a strategic partner to retail and e-commerce clients, helping them design, launch, and scale high-performing recommendation-driven email programs across promotional, triggered, and lifecycle messaging. From first deployment through long-term expansion, you will guide customers in using intelligent recommendations to drive measurable gains in engagement, conversion, and lifetime value.
\nWhat You’ll Do
\nRequirements
\nBenefits
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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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\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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\nResearch Engineer, Notifications
\nLocation
\nSan Francisco
\nEmployment Type
\nFull time
\nDepartment
\nApplied AI
\nCompensation
\nThe base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
\nMore details about our benefits are available to candidates during the hiring process.
\nThis role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
\nAbout the Team
\nThe ChatGPT team works across research, engineering, product, and design to bring OpenAI’s technology to the world.
\nWe seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products.
\nAbout the Role
\nWe are looking for a Machine Learning Engineer to join our Notifications team, focused on building and scaling intelligent notification systems that provide real value to users even when they are not actively on the product. This role will be central to shaping how ChatGPT communicates proactively and helpfully with users—surfacing the right content, at the right time, through the right channel.
\nYou will work on designing and implementing ranking and recommendation systems that leverage both classical ML techniques and large language models (LLMs) to optimize notification relevance, timeliness, and user experience. The ideal candidate has strong ML fundamentals, experience shipping ranking or recommendation systems in production, exposure to LLMs, and sharp product intuition. You should be comfortable operating across research and product boundaries: thinking from first principles, running rigorous experiments, and building scalable systems.
\nThis role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
\nIn this role, you will:
\nYou might thrive in this role if you:
\nAbout OpenAI
\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
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\nMicrosoft are looking for a talented Senior Software Engineer at their Redmond office. This role sits at the heart of building cutting-edge solutions for document understanding on a web scale. You'll work with some of the largest datasets, lead projects end-to-end, and collaborate across teams to deliver real-world impact.
\nAbout the Role
\nThe Web Data Platform (WDP) is the data foundation of Bing and many Microsoft experiences, powering Bing Search, ads, Copilot, Grounding API to 1P and 3P scenarios, deep research, LLM training, etc. Our mission is to deliver the world's freshest, richest, and clean semantic understanding of the web document representation. Our work is central to understanding public web content and advancing the platform's capabilities in tandem with state-of-the-art modeling. As part of our team, you'll work with large-scale machine learning and large language models (LLMs) to understand and enrich web content, fueling critical Microsoft experiences and advancing the frontier of AI.
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\nMicrosoft AI are looking for a talented and experienced Machine Learning Engineer to join our Growth team and help shape the next generation of AI systems, specifically for our personal AI assistant, Copilot.
\nAbout the Role
\nAs a Machine Learning Engineer on our Growth team, you will design, develop, and implement machine learning models for high-performance recommendation systems and personalized feeds. You will leverage large language models (LLMs) to create scalable, intelligent solutions for content understanding, user engagement, and relevance ranking. You will drive data-driven experimentation using A/B testing, advanced analytics, and statistical techniques to identify growth opportunities and refine algorithms. You will develop and optimize pipelines, tools, and infrastructure to support real-time decision-making, personalization, and predictive analytics.
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