Energy Optimization Engineering Internship

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:

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.

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.

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.

We are seeking a talented and motivated Reliability Engineer to join our innovative team at Redwood Materials. In this role, you will be responsible for ensuring the reliability and performance of our cutting-edge energy storage systems. You will collaborate with cross-functional teams to develop and implement reliability engineering strategies that enhance product performance and longevity.

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.

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.

About Us at Redwood MaterialsAt Redwood Materials, we are revolutionizing the global battery supply chain by integrating recovery, reuse, and recycling. Founded in 2017, we are committed to keeping critical minerals in circulation and driving the energy transition. Our mission is to provide low-cost, large-scale energy storage solutions while producing battery materials in the U.S. for the first time, utilizing batteries we already have.Team ObjectivesOur team develops the software platform that enables optimized control and market participation of battery energy storage systems (BESS), with solutions operating on-site and in the cloud.Our work encompasses the entire technology stack: compute infrastructure, telemetry, asset modeling, alerting, feature ingestion and storage for forecasting and optimization, simulation, operational control orchestration, and seamless integration with energy markets.As a compact team, we uphold high standards for the quality and speed of our deliverables. We emphasize collaboration, trust, continuous learning, and engineering excellence while enjoying the process of building great solutions together.Your Role and ResponsibilitiesYou will actively contribute to our platform with potential focuses including:Data engineering for BESS — managing telemetry pipelines, feature ingestion, and storage for forecasting and optimizationSimulation and training infrastructure — developing platforms for orchestrating large-scale simulationsReal-time forecasting and optimization workflows — managing pipelines that drive BESS operationsEnergy market integration — overseeing data ingestion and bid managementSome of the technologies you will work with include Kubernetes, Rust, Python, NATS, PostgreSQL/TimescaleDB, SQLite, and more as our systems evolve.What We SeekStrong instincts for software design — you think systemically, reason from first principles, and grasp the real-world challenges of building available, reliable, scalable, and secure distributed systemsExperience with AI-accelerated development — you're comfortable leveraging AI to enhance software development processes

Join Intersect as a Microgrid Controls Validation Intern and immerse yourself in cutting-edge energy solutions! In this role, you will collaborate with a dynamic team to validate and optimize microgrid control systems. This internship offers a unique opportunity to gain hands-on experience in the renewable energy sector, contributing to sustainable power solutions.

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.

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.

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 our innovative team at Redwood Materials as a Field Quality Engineer specializing in energy storage solutions. In this pivotal role, you will be responsible for ensuring the highest quality standards in our energy storage products. Your expertise will help drive quality improvements and enhance customer satisfaction.As a Field Quality Engineer, you will work closely with our operations and engineering teams, conducting quality assessments, analyzing data, and providing actionable insights to ensure product excellence. This position offers an exciting opportunity to contribute to the advancement of sustainable energy technologies.

Redwood Materials recovers, reuses, and recycles battery materials to keep critical minerals in circulation and support the energy transition. Since 2017, the company has focused on developing large-scale, cost-effective energy storage solutions and manufacturing battery materials domestically, often using resources from existing batteries. Role overview This Functional Safety Engineer position focuses on advancing a sustainable circular economy for lithium-ion batteries. The role centers on ensuring that energy storage systems (ESS) meet functional safety standards and on supporting the secure deployment of new ESS technologies. What you will do Lead compliance efforts for ESS functional safety, with particular attention to standards such as UL 1998 (Software in Programmable Components), UL 991 (Tests for Safety-Related Controls Employing Solid-State Devices), and UL 5500 (Remote Software Updates). Support certification activities and help align product development with functional safety requirements. Location San Francisco, California, United States

Join Redwood Materials as an Engineering Test Technician specializing in energy storage solutions. In this pivotal role, you will be at the forefront of testing and validating cutting-edge technologies that contribute to sustainable energy practices. You will work collaboratively with engineers and technicians to ensure the reliability and performance of our innovative energy storage systems.

About Redwood MaterialsAt Redwood Materials, we are revolutionizing the battery supply chain by focusing on recovery, reuse, and recycling. Our mission is to keep essential minerals circulating and facilitate the energy transition. Since our founding in 2017, we have been at the forefront of delivering cost-effective, large-scale energy storage solutions and producing battery materials domestically—utilizing the batteries we already possess.Service Engineer, Energy StoragePosition Summary:Redwood Materials is on the lookout for a dedicated Service Engineer to become an integral part of our newly established engineering team focused on the Battery Energy Storage System (BESS) product line. In this role, you will play a crucial part in diagnosing and resolving intricate technical challenges associated with our deployed BESS. You will support the Operations and Maintenance (O&M) team by conducting routine monitoring, preventive maintenance, and first-line troubleshooting. As part of the Service Engineering team, you will act as the technical escalation resource for O&M, responsible for in-depth diagnostics, system-level failure analysis, and implementing engineering-driven corrective measures.The Service Engineer ensures the safe, reliable, and optimal performance of our assets by acting as a liaison between field operations and engineering. You will translate operational challenges into engineering solutions and provide valuable feedback from the field to enhance product and system design. This position also offers the potential for leadership growth as the team expands.The ideal candidate is self-motivated, adaptable to a dynamic startup environment, and ready to tackle both technical and leadership challenges.

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.

At Databricks, we are dedicated to empowering data teams to tackle the world's most challenging problems, from detecting security threats to advancing cancer drug development. We achieve this by offering the premier data and AI platform, allowing our customers to concentrate on their mission-critical challenges. The Mosaic AI organization assists companies in developing AI models and systems utilizing their own data, employing technologies that range from training large language models (LLMs) from the ground up to employing advanced retrieval methods for enhanced generation. We pride ourselves on pushing the boundaries of science and operationalizing our innovations. Mosaic AI believes that a company’s AI models hold intrinsic value, akin to any other core intellectual property, and that superior AI models should be accessible to all. Job Overview As a research engineer in the Scaling team, you will stay abreast of the latest advancements in deep learning and pioneer new methodologies that surpass the current state of the art. You will collaborate with a diverse team of researchers and engineers, sharing insights and expertise. Most importantly, you will be passionate about our customers, striving to ensure their success in implementing cutting-edge LLMs and AI systems by translating our scientific knowledge into practical applications. Your Impact Enhance performance through innovative optimization techniques, including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization tailored for training-specific patterns. Design, implement, and optimize high-performance GPU kernels for training workloads, including attention mechanisms, custom layers, gradient computations, and activation functions, specifically for NVIDIA architectures. Create and implement distributed training frameworks for large language models, incorporating parallelism strategies (data, tensor, pipeline, ZeRO-based) and optimized communication patterns for gradient synchronization and collective operations. Profile, debug, and optimize comprehensive training workflows to pinpoint and resolve performance bottlenecks, utilizing memory optimization techniques such as activation checkpointing, gradient sharding, and mixed precision training.