Leader, Optimization Services

Join Benchling as the Leader of Optimization Services, where you'll spearhead initiatives to enhance our services and deliver exceptional value to our clients. In this pivotal role, you will guide a talented team, leveraging data-driven insights to optimize processes and drive efficiency. Your strategic vision will be crucial in shaping our services to meet evolving market demands. If you are passionate about innovation and committed to excellence, we would love to hear from you.

About AirwallexAt Airwallex, we are redefining the landscape of financial services with our all-in-one payments and financial platform tailored for global enterprises. With our innovative blend of proprietary technology and software, we empower over 200,000 businesses, including industry leaders such as Brex, Rippling, Navan, Qantas, and SHEIN, to seamlessly manage their business accounts, payments, spend management, treasury, and embedded finance solutions on a global scale.Originally founded in Melbourne, our diverse team of over 2,000 talented professionals spans across 26 offices worldwide. With a valuation of $8 billion, supported by prestigious investors like T. Rowe Price, Visa, and Mastercard, Airwallex is at the forefront of developing the future of global payments and finance. If you are eager to take on ambitious challenges and make a significant impact, we invite you to join us.Attributes We ValueWe seek dynamic builders with entrepreneurial spirits who aspire to create real change, accelerate their learning, and take ownership of their work. You bring a wealth of expertise and critical thinking skills, driven by our mission and operating principles. You act swiftly with sound judgment, explore deeply with curiosity, and make informed decisions by balancing speed and thoroughness.You embody humility and collaboration, transforming innovative concepts into tangible products, and you are committed to seeing projects through to completion. By utilizing AI, you work smarter and resolve challenges efficiently. Here, you will tackle complex, high-impact issues alongside exceptional colleagues and advance your career as we shape the future of global banking. If this resonates with you, let's build the next big thing together.About the TeamThe Marketing team at Airwallex is dedicated to enhancing brand visibility and customer interaction through cutting-edge and strategic campaigns. We strive to effectively communicate the benefits of our financial solutions, attract new clientele, and deepen relationships with existing customers. By harnessing data-driven insights and innovative strategies, we ensure that Airwallex stands out in a competitive marketplace. Our team is passionate about narrating the Airwallex story and fostering the company’s growth and success.What You’ll DoWe are on the lookout for a data-driven, analytical, and user-focused marketer to spearhead Landing Page Optimization (LPO) and enhance conversion rates across our U.S. and EMEA acquisition funnels. This role is hands-on and centers around designing and executing experiments that optimize landing pages for maximum effectiveness and engagement.

Join Planet Labs PBC as a Mission Optimization Engineer Intern! As a part of our dynamic team, you will engage in innovative projects that leverage satellite data to optimize mission operations. This is an exciting opportunity to apply your technical skills in a real-world setting and contribute to our mission of making change visible on Earth.

Join Our Innovative Team!LucidLink is a dynamic and rapidly expanding startup dedicated to revolutionizing data accessibility. In an era where remote and hybrid work is prevalent, our cloud-based technology empowers teams to access files and collaborate seamlessly from any location, mimicking the experience of a local hard drive.Our cutting-edge solution is tailored for industries that handle large files and require real-time collaboration. We proudly serve some of the most creative companies in the world, including Paramount, Warner Brothers, Epic Games, Spotify, A+E, and Netflix. Founded in 2016 by experts in the storage industry, we now support over one billion customer files across more than 40 countries. With our headquarters in San Francisco, California, and an engineering office in Sofia, Bulgaria, we have remote team members spread across North America, Europe, and Australia.

About Redwood MaterialsRedwood Materials is at the forefront of localizing a global battery supply chain that integrates recovery, reuse, and recycling—ensuring critical minerals remain in circulation while propelling the energy transition. Founded in 2017, we are pioneering low-cost, large-scale energy storage and manufacturing battery materials in the U.S. for the first time, all sourced from batteries that are currently in circulation.Essential Duties: As an Energy Optimization Engineering Intern, you will play a crucial role in developing the predictive "intelligence layer" designed to manage energy for AI Data Centers and microgrids. Under the mentorship of senior engineers, you will assist in constructing and validating time-series forecasting models for GPU power loads and market prices, integrating these insights into Mixed-Integer Programming (MIP) prototypes. You will work alongside cloud software teams to test these "forecast-informed" algorithms in a cloud-native setting, aiding in the simulation and backtesting of energy management strategies. Your goal is to enhance the accuracy and efficiency of our Energy Management System (EMS), gaining practical experience in "value-stacking" and real-world energy optimization. This internship is for Summer 2026.Responsibilities Include:

Team Overview The infrastructure team at OpenAI manages the core systems that support AI workloads worldwide. As OpenAI expands its compute capabilities across company-owned data centers, cloud environments, and strategic partnerships, the need for careful planning and resource management grows. Reliable and cost-effective compute operations depend on this foundation. The Compute Optimization group operates at the intersection of engineering, operations, finance, and infrastructure strategy. This team develops models, decision tools, and planning systems to improve how compute resources are scheduled, deployed, and scaled as global needs shift. Role Overview OpenAI is hiring a Compute Optimization Researcher/Engineer to help maximize the use of compute capacity across the organization. This role addresses complex optimization challenges related to capacity allocation, demand forecasting, cluster planning, workload placement, and infrastructure utilization. Work includes building mathematical models, developing software systems, and collaborating with other teams to improve planning and use of compute resources. Areas of focus span GPU clusters, networking, storage, and data center infrastructure. Candidates with experience in operations research, optimization, applied mathematics, infrastructure systems, or large-scale capacity planning will be well-suited for this position. Location and Work Model This position is based in San Francisco, CA. OpenAI follows a hybrid schedule with three days per week in the office. Relocation assistance is offered.

About the RoleWe're excited to invite you to join wafer as a Spring Intern, where you will play a crucial role in shaping the future of AI infrastructure and GPU optimization. As part of our innovative team, you will work closely with full-time engineers to define our technical strategies and contribute to the development of the essential systems that drive our GPU optimization platform.Your ResponsibilitiesDesign and implement scalable infrastructure for AI model training and inference tasks.Guide the team in making technical decisions and architectural choices.Qualifications We SeekEssential Technical SkillsGPU Fundamentals: A strong grasp of GPU architectures, CUDA programming, and parallel computing methodologies.Deep Learning Frameworks: Skilled in PyTorch, TensorFlow, or JAX, especially for GPU-accelerated applications.Knowledge of LLM/AI: Solid foundation in large language models, including training, fine-tuning, prompting, and evaluation.Systems Engineering: Proficient in C++, Python, and potentially Rust/Go for developing tools around CUDA.Preferred BackgroundPublications or contributions to open-source projects related to inference GPU computing or ML/AI are advantageous.Hands-on experience in conducting large-scale experiments, benchmarking, and performance optimization.

At ClickUp, we're not just developing software; we're shaping the future of work! In an era dominated by work sprawl, we identified a more efficient way. This led us to create the first truly integrated AI workspace, consolidating tasks, documents, chat, calendar, and enterprise search, all enhanced by context-driven AI. Our mission is to empower millions of teams to escape silos, reclaim their time, and reach unprecedented levels of productivity. At ClickUp, you'll have the chance to learn, innovate, and leverage AI in transformative ways that will not only influence our product but also the broader landscape of work itself. Join a daring, pioneering team that's challenging the limits of what's possible! We are on the lookout for a technical leader in SaaS client performance who is passionate about enhancing the customer experience through top-tier performance solutions. As a Senior Performance Engineer, you will spearhead comprehensive strategies to optimize application speed, memory utilization, and reliability across our entire platform. You will be empowered to analyze, diagnose, and address performance bottlenecks wherever they arise—be it front-end, back-end, or infrastructure—ensuring ClickUp remains the fastest and most reliable productivity platform available.The ideal candidate is a hands-on authority in browser and NodeJS performance, with a thorough understanding of how code influences rendering, memory management, and overall user experience. You excel in solving intricate challenges, collaborating across teams, and establishing new benchmarks for performance excellence. If you're driven to make a significant impact for millions of users, this is your chance to lead at scale.Your Responsibilities:Conduct root cause analysis on client performance issues and perform post-mortems.Profile application code to identify inefficient algorithms, memory leaks, and other issues; propose and implement effective solutions.Establish performance monitoring, alerting, and dashboards to proactively detect and resolve client performance challenges.Examine client traffic patterns, load testing outcomes, and other metrics to set benchmarks and drive enhancements.Champion performance best practices and set performance standards across the engineering organization.Identify infrastructure upgrades (caching, CDNs, database optimization) to elevate the client experience.Collaborate with development teams to incorporate performance as a core requirement in the development of new features.

Join Hilbert, a pioneering data science-driven growth engine that empowers B2C teams with predictive insights into user behaviors, revenue streams, and sustainable growth strategies. Our innovative platform reduces decision-making cycles from months to mere minutes.Serving a range of clients from Fortune 10 companies to cherished brands such as FreshDirect, Blank Street, and Levain Bakery, our platform is the backbone of their growth strategies. We are also collaborating with leading AI firms to enhance our capabilities.We are on the lookout for a Core Data Engineer to lay the groundwork for our integration team, enabling them to operate at 10x their current speed. While others may focus on connecting systems, your mission is to ensure the integrity and flow of our data refinery. You will manage our 'shared brain', optimize ClickHouse clusters, and develop monitoring systems that proactively identify pipeline issues before they impact our customers.ROLE OVERVIEWEfficiency Expert: You thrive on minimizing query times and memory usage, always considering scalability and reliability.Dagster Enthusiast: You bring experience or a strong desire to excel in Dagster for intricate orchestration.OLAP Specialist: You possess a deep understanding of ClickHouse (or similar platforms like Druid/Pinot) and know how to structure data for optimal analytical performance.Software Development Advocate: You treat data code with the same rigor as production software. CI/CD, unit testing, and modular code are non-negotiable for you.Global Collaboration: You can coordinate with our global team, providing at least 5 hours of overlap.WHO EXCELS IN THIS ROLEYou will optimize the performance of our ClickHouse implementation.You will devise configuration schemas that facilitate controlled data ingestion pipelines.You will build and sustain shared Python libraries for data synchronization across the engineering team.You will enhance our canonical data models to balance scalability with performance.You will architect our monitoring, alerting, and observability systems to ensure high confidence in our data integrity.You will design new integration pipelines by exploring novel data sources and sync mechanisms.

Role overview This Software Engineer position at OpenAI focuses on inference and performance optimization. Based in San Francisco, the role centers on increasing the speed and efficiency of advanced AI systems. Collaboration with experienced engineers is a key part of the work, with an emphasis on refining AI performance. What you will do Work on optimizing the performance of AI inference systems Collaborate with other engineers to improve efficiency and speed Contribute to solutions that enhance AI system capabilities Location This role is based in San Francisco.

Join DigitalOcean as a Senior Engineer focused on Inference Optimizations, where you will play a pivotal role in enhancing our AI and machine learning capabilities. Collaborate with a talented team to develop cutting-edge solutions that optimize inference processes across various applications.

About the RoleWe invite you to join our innovative team at Wafer as a Technical Intern, where you will have the opportunity to shape the future of inference, GPU optimization, and AI infrastructure. As a full-time engineer, you will collaborate closely with our team to define our technical direction and develop the core systems that drive our GPU optimization platform.Your ResponsibilitiesDesign and implement scalable infrastructure for AI model training and inference.Make pivotal technical decisions and influence architectural choices.

Join Zyphra as a Research Engineer specializing in AI Performance and Kernel Optimization. In this role, you will work at the forefront of AI technologies, developing and optimizing kernel solutions that enhance the performance of our systems. You will collaborate with cross-functional teams, leveraging your expertise to drive innovation and efficiency.

Tavus – Multimodal AI Model OptimizationResearch EngineerAt Tavus, we are pioneering the human aspect of AI technology. Our objective is to make human-AI interactions as seamless and natural as in-person conversations, allowing for a human touch in areas that were once considered unscalable.We accomplish this through groundbreaking research in multimodal AI, focusing on human-to-human communication modeling (encompassing language, audio, and video) and the development of audio-visual avatar behaviors. Our innovative models drive applications ranging from text-to-video AI avatars to real-time conversational video experiences across sectors such as healthcare, recruitment, sales, and education.By empowering AI to perceive, listen, and engage with an authentic human-like presence, we are laying the groundwork for the next generation of AI workers, assistants, and companions.As a Series B company, we are supported by renowned investors, including Sequoia, Y Combinator, and Scale VC. Join us as we shape the future of human-AI interaction.The RoleWe are seeking an accomplished Research Scientist/Engineer with expertise in model optimization to be a vital part of our core AI team.The ideal candidate thrives in dynamic startup environments, is adept at setting priorities independently, and is open to making calculated decisions. We are moving swiftly and need individuals who can help navigate our path forward.Your MissionTransform state-of-the-art research models into fast, efficient, and production-ready systems through techniques such as sparsification, distillation, and quantization.Oversee the optimization lifecycle for critical models: establish metrics, conduct experiments, and evaluate trade-offs among latency, cost, and quality.Collaborate closely with researchers and engineers to convert innovative concepts into deployable solutions.RequirementsExtensive experience in deep learning with PyTorch.Practical experience in model optimization and compression, including knowledge distillation, pruning/sparsification, quantization, and mixed precision.Familiarity with efficient architectures such as low-rank adapters.Strong grasp of inference performance and GPU/accelerator fundamentals.Proficient in Python coding and adherence to best practices in research engineering.Experience with large models and datasets in cloud environments.Capability to read ML literature, reproduce results, and modify ideas accordingly.

Join DoorDash as a Machine Learning Engineer, where you'll be pivotal in designing, building, and optimizing large-scale machine learning systems within our Ads Delivery funnel. Your expertise will contribute to enhancing our Ads Marketplace, ensuring a balanced and efficient ecosystem for advertisers and consumers alike. Work with advanced AI and machine learning techniques to dynamically optimize bidding, auction design, budget pacing, forecasting, and ad experimentation. This role offers a unique opportunity to influence our innovative advertising products as we expand into new verticals such as Grocery and Retail.

About Sprinter HealthAt Sprinter Health, we are dedicated to transforming healthcare accessibility by delivering essential services directly to patients' homes. Across the U.S., nearly 30% of individuals forgo preventive and chronic care simply due to accessibility challenges. This often leads to emergency room visits, which contribute to over $300 billion in unnecessary healthcare expenses annually.Leveraging cutting-edge technology akin to that used by leading marketplace and last-mile logistics platforms, we provide care right where it’s needed, particularly for vulnerable populations. To date, we have positively impacted over 2 million patients across 22 states, conducted over 130,000 in-home visits, and achieved an impressive Net Promoter Score (NPS) of 92. Our dynamic team of clinicians, tech experts, and operations professionals has successfully raised over $125 million from esteemed investors such as a16z, General Catalyst, GV, and Accel, ensuring a solid multi-year runway for our growth.About the RoleWe are seeking a Senior Software Engineer to join our Logistics Optimization team, where you will address some of the most challenging algorithmic and operational issues in the healthcare sector. In this pivotal role, you will design and implement systems that efficiently balance clinician availability, patient demand, and routing logistics, forming the backbone of Sprinter's in-home care delivery framework. This position demands deep technical expertise and offers high-impact opportunities, focusing on the convergence of operations research, simulation, and scalable distributed systems.Office LocationAs a hybrid company based in the Bay Area, we operate from offices in San Francisco and Menlo Park. We prioritize work-life balance and are committed to providing flexibility when needed.Key Responsibilities:Design and implement algorithms that optimize clinician routing, scheduling, and dispatching on a national scale.Develop simulations that accurately model demand, capacity, and patient behaviors within real-world constraints.Create predictive models to manage cancellations, no-shows, and optimize overbooking strategies.Collaborate with product and operations teams to translate complex logistics challenges into scalable software solutions.Prototype and deploy forecasting and optimization models within a distributed environment.Engage in continuous improvement practices to enhance system performance and reliability.

Join Merge Labs, a pioneering research facility dedicated to merging biological and artificial intelligence to enhance human capabilities, agency, and experience. We aim to achieve this by crafting innovative brain-computer interfaces that communicate with the brain at high bandwidth, seamlessly integrate with cutting-edge AI, and prioritize safety and accessibility for all users.About the Team:At Merge Labs, we are on a mission to revolutionize brain-computer interfaces by leveraging advancements in synthetic biology, neuroscience, AI, and non-invasive imaging technologies. Our cross-functional data science team is situated at the convergence of computational modeling, neuroscience, and biomolecular engineering. This collaborative unit works closely with wet-lab scientists, automation specialists, and data engineers to develop machine learning frameworks that facilitate rapid molecule discovery and device enhancement.About the Role:We are seeking a talented Senior / Principal ML Scientist to architect and scale Bayesian optimization and reinforcement learning frameworks that guide molecular engineering initiatives through iterative design-build-test-learn (DBTL) cycles. You will start with a fresh approach to construct the company's closed-loop optimization infrastructure, establishing the data and modeling foundations that link experiments with these ML frameworks. Over time, you will transition prototypes into operational pipelines, significantly enhancing experimental throughput and discovery success across various biomolecular and neuroengineering sectors.Key Responsibilities:Develop the scientific and engineering framework for active learning and closed-loop optimization, encompassing data ingestion, ML modeling, and library design.Collaborate with wet-lab scientists to establish feasible optimization objectives while incorporating domain-specific priors and constraints.Create prototypes for representation learning and acquisition strategies utilizing both internal and public datasets; benchmark and validate the performance of models.Integrate machine learning models with experimental data streams, making them accessible to non-domain experts for broader utilization.Extend machine learning frameworks to accommodate multi-objective or constrained optimization challenges.Stay abreast of the latest advancements in Bayesian optimization, active learning, and reinforcement learning, and prototype innovative algorithms to enhance the company's capabilities.

Join Our TeamAt Air Apps, we are driven by the ambition to innovate and accelerate. Founded in Lisbon in 2017, we are on a mission to develop the world's first AI-powered Personal & Entrepreneurial Resource Planner (PRP). With a self-funded journey, we've achieved over 100 million downloads globally. Our dual presence in Lisbon and San Francisco fuels our commitment to pushing the boundaries of AI-driven solutions that enhance people's lives.As part of our team, you will play a pivotal role in creating transformative products that empower individuals worldwide. We're looking for passionate and driven individuals to help us redefine resource management.Your RoleWe are seeking a talented App Store Optimization (ASO) Specialist to join our San Francisco office. In this critical role, you will spearhead strategies aimed at enhancing visibility, discoverability, and conversion rates within the Apple App Store. Utilizing keyword research, creative testing, and data analytics, you will drive user acquisition and retention through organic channels.This position is ideal for an individual passionate about mobile growth, detail-oriented, and eager to optimize multiple applications that serve millions globally.Key ResponsibilitiesConduct comprehensive keyword research and optimize app metadata (titles, descriptions, tags) to maximize store visibility.Create and test engaging creative assets (icons, screenshots, app previews, CPPs) to enhance conversion rates.Analyze app store performance metrics and deliver actionable insights for improvement.Monitor competitors and industry trends to identify new growth opportunities.Collaborate effectively with User Acquisition, Product, and Creative teams to ensure alignment of ASO strategies with broader marketing goals.Remain updated on platform changes, industry best practices, and emerging ASO tools.QualificationsMinimum of 3 years experience in ASO or mobile growth marketing.Deep understanding of app store ecosystems, particularly Apple App Store and Google Play.Proficient in ASO and analytic tools such as App Annie, Sensor Tower, and Data.ai.Strong analytical skills with a proven ability to derive insights from data.Excellent communication and collaboration skills.

Join Waymo as a Staff Software Engineer specializing in Simulation Capacity Optimization. In this pivotal role, you will leverage your expertise in software engineering and simulation technology to enhance our autonomous vehicle systems. Your contributions will be vital in optimizing the performance and efficiency of our simulations, ensuring that our vehicles are equipped to navigate the complexities of real-world environments.

Whizz is at the forefront of revolutionizing delivery services with our innovative and cost-effective electric bicycle solutions. Our mission is to redefine transportation affordability while ensuring customer satisfaction. We prioritize our clients by addressing concerns promptly and enhancing user experience through streamlined registration and usage processes. Our objective is to cultivate an environment where riders can earn a sustainable income, maintain safety, and foster community connections.As the leading e-bike subscription provider in the U.S., Whizz is committed to making a significant impact in the delivery landscape.Key Responsibilities:Sales: Identify and engage potential clients, effectively present our e-bike solutions, and consistently achieve sales targets on a weekly and monthly basis.Onboarding & Training: Provide in-field training, mentor team members, and facilitate ongoing professional development.Management & Coaching: Supervise daily operations, develop schedules, and enhance sales processes for maximum efficiency.Reporting: Monitor sales performance, analyze trends, and compile regular reports for management review.