Research Associate - Spatial Methods & Imaging

Join our innovative team at Zyphra as a Research Engineer specializing in Brain-Computer Interface (BCI) Models. In this pivotal role, you will contribute to groundbreaking research and development initiatives in the field of neuroscience and artificial intelligence. Your expertise will help shape the future of communication between humans and machines, enhancing the quality of life for countless individuals.As a Research Engineer, you will be responsible for designing, implementing, and testing advanced BCI models, collaborating closely with a diverse team of scientists and engineers. Your work will play a crucial role in advancing our understanding of neural dynamics and their applications in technology.

About AlljoinedAt Alljoined, we are pioneering solutions to eliminate communication barriers between humans and technology by non-invasively interpreting brain activity. Through advanced deep learning techniques applied to extensive EEG datasets gathered from cost-effective hardware, we decode various stimuli, including images, emotions, and even thoughts. Initially focusing on business applications, our long-term vision includes creating a consumer-facing interface to enhance productivity, entertainment, and AI applications.Our dedicated team of researchers is expanding, and we are committed to developing a high-performance and accessible interface that significantly enhances individual lives and contributes positively to societal well-being.

At Merge Labs, we are pioneering research that merges biological and artificial intelligence to enhance human capability, autonomy, and overall experience. Our mission is to create innovative brain-computer interfaces (BCIs) that seamlessly interact with the brain at high bandwidth, integrate with cutting-edge AI, and ensure safety and accessibility for all users.About Our Team:Our Bio team is at the forefront of designing, constructing, and characterizing the biotechnologies essential for next-generation BCIs. We leverage molecular engineering, synthetic biology, and neuroscience, alongside advanced physical techniques such as ultrasound, to establish minimally invasive, high-bandwidth neuron connections. The Bio team is responsible for developing and validating our core molecular technologies, assessing their performance in both in vitro and in vivo environments, and showcasing their capabilities in animal models. We create bespoke experimental setups and workflows, collaborating closely with engineers and data scientists to tackle some of the most pressing challenges in biotechnology.About the Role:As a Protein Engineer at our BCI company, you will be instrumental in designing, building, and optimizing biomolecules that translate neuronal activity into comprehensible signals. Your contributions will facilitate precise modulation between cellular and machine languages.You will engage with a range of unconventional proteins—from innovative biosensors to membrane proteins and intricate multi-component assemblies. Utilizing your biophysical expertise and high-throughput experimental methods, along with close collaboration with our computational team, you will push the limits of these molecules' functionalities. Your work will lay the molecular groundwork for advanced brain-computer interfaces.Key Responsibilities:Design and Execute Protein Engineering Strategies: From rational design and computational modeling to directed evolution and combinatorial library approaches, you will create dynamic molecular systems with desirable traits.High-Throughput Protein Variant Characterization: Rapidly test and refine hypotheses by implementing and optimizing scalable workflows from library generation to expression in various in vitro systems and conducting both standard and custom assays.Collaboration with Computational Team: Work closely to develop models that correlate sequences and structures to functional properties.

At Merge Labs, we are at the forefront of research, aiming to integrate biological and artificial intelligence to enhance human capabilities, agency, and experience. Our mission is to pioneer revolutionary brain-computer interfaces that communicate with the brain at unprecedented bandwidths, harmonizing with advanced AI technology to ensure safety and accessibility for all users.About the TeamOur team is dedicated to constructing the most sophisticated interface to the brain, engaging with neurons on an extraordinary scale and speed. Achieving this vision requires cutting-edge engineering and a collaborative spirit. We are bringing together a diverse group of talented professionals from electrical engineering, mechanical engineering, mixed-signal IC design, materials science, systems engineering, and engineering physics. Our approach is grounded in fundamental principles, enabling us to create scalable technology through rapid prototyping, testing, and iteration.About the RoleWe are looking for a Mechanical Engineer to lead the design and packaging of our brain-computer interface systems, ranging from initial R&D prototypes to mass-produced wearable technologies. In this role, you will serve as a crucial link between electrical performance and physical design constraints, ensuring our products are both high-performing and user-friendly. This position requires extensive technical knowledge in the design and execution of integrated systems featuring high-performance electronics. You will transform concepts from initial sketches to production-ready designs while managing essential vendor relationships for fabrication and tooling, setting the benchmark for mechanical engineering excellence at Merge Labs.

At Merge Labs, we are pioneering the intersection of biological and artificial intelligence, aiming to enhance human potential, agency, and overall experience. Our innovative research focuses on creating fundamentally new brain-computer interfaces that provide high-bandwidth interaction with the brain, seamlessly integrate with advanced AI, and prioritize safety and accessibility for all users.Team OverviewOur Bio team is at the forefront of designing, constructing, and characterizing the biotechnologies essential for next-generation brain-computer interfaces. We utilize molecular engineering, synthetic biology, and neuroscience, along with advanced physical techniques such as ultrasound, to forge less invasive, high-bandwidth connections with neuronal structures. The Bio team is responsible for developing our core molecular technologies, validating their efficacy both in vitro and in vivo, and demonstrating their advanced functionalities through animal model studies. We thrive on collaboration, working closely with engineers and data scientists, and fostering interdisciplinary creativity to tackle some of biotechnology's most pressing challenges.Role OverviewIn the position of Scientist in Cell Biology, you will be tasked with engineering neurons and various cell types to express innovative molecular biosensors and actuators, assessing their roles in enabling cellular interaction with ultrasound. Your research will encompass the study of biosensor expression, localization, degradation, and their effects on cellular function and health. You will devise protocols for cell culture, analysis, microscopy, and interactions with physical energies such as ultrasound. Your contributions will play a critical role in advancing groundbreaking molecular technologies geared towards neural interfacing and accelerating their clinical application.Key ResponsibilitiesOptimize and maintain mammalian cell preparations, including cell lines, primary and iPSC-derived neurons, brain organoids, or brain slices.Collaboratively innovate and construct novel protein and genetic constructs to facilitate biosensing and/or actuating capabilities.Develop and execute cell engineering workflows, encompassing construct delivery, selection, and differentiation processes.Characterize construct functionality and assess cellular impact using techniques such as activity recording, microscopy, stimulation, flow cytometry, immunohistochemistry, and next-gen sequencing.Engage in collaborations with cross-disciplinary teams, integrating expertise from protein engineering, biochemistry, cell biology, neuroscience, and genetics.

Company OverviewEcho Neurotechnologies is a pioneering startup in the Brain-Computer Interface (BCI) sector, dedicated to revolutionizing the lives of individuals with disabilities through advanced hardware engineering and artificial intelligence solutions. Our vision is to develop innovative technologies that empower users, restoring autonomy and enhancing their quality of life.Team CultureWe pride ourselves on cultivating an inclusive and dynamic team of skilled professionals who are passionate about their work. Our startup environment encourages ownership of impactful decisions and fosters continuous learning and collaboration, where every contribution is essential to our collective success.Job SummaryWe are on the lookout for a talented Machine Learning Research Engineer specialized in speech modeling to join our innovative team. The successful candidate will leverage ML/AI methodologies to create and refine adaptable speech models aimed at brain-computer interface applications, ultimately making a difference in the lives of patients facing severe disabilities. Candidates should possess significant expertise in speech modeling, feature engineering, time-series analysis, and the development of custom ML models.Key ResponsibilitiesDesign and evaluate diverse model architectures and strategies to enhance the accuracy and resilience of models for interpreting speech from brain activity.Investigate and implement cutting-edge speech features and representations within neural-decoding frameworks, informed by speech science and functional neurophysiology.Create pipelines for generating personalized and naturalistic speech from both text and brain activity inputs.Develop algorithms to analyze both intact and compromised speech signals, identifying biomarkers linked to various diseases and disabilities.Collaborate within a tight-knit team to build models, define R&D workflows, and translate scientific discoveries into practical applications.Contribute to best practices ensuring reliability, observability, reproducibility, and scientific rigor across the R&D landscape.Maintain well-documented, versioned code, analysis pipelines, and results for maximum interpretability and reproducibility.

At Merge Labs, we are at the forefront of research, dedicated to uniting biological and artificial intelligence to enhance human capability, autonomy, and overall experience. Our innovative approach focuses on developing revolutionary brain-computer interfaces that offer high-bandwidth interaction with the brain, seamlessly integrate advanced AI, and are designed to be safe and accessible for everyone.About the Team:Our Bio team is responsible for designing, constructing, and characterizing the biotechnologies that underpin the next generation of brain-computer interfaces. By integrating molecular engineering, synthetic biology, neuroscience, and cutting-edge physical methods such as ultrasound, we aim to establish less invasive, high-bandwidth connections with neurons. The Bio team is dedicated to developing our core molecular technologies, validating their performance both in vitro and in vivo, and showcasing their advanced capabilities in animal models. We create custom experimental setups and pipelines while collaborating closely with engineers and data scientists to tackle some of the most challenging problems in biotechnology.About the Role:We are seeking a Senior/Principal Machine Learning Biophysicist to spearhead the creation of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks. You will build the molecular modeling foundations of the company from first principles, establishing tools and workflows for simulating, analyzing, and interpreting biomolecular dynamics to elucidate function relationships. Over time, your contributions will help translate these frameworks into predictive models that expedite molecular engineering, guide experimental campaigns, and facilitate the discovery of highly functional molecules.Key Responsibilities:Develop the scientific and engineering framework for protein structure modeling and molecular dynamics, along with integrations into downstream ML frameworks.Collaborate with wet-lab scientists to establish realistic optimization objectives and encode domain-specific priors and constraints.Prototype modeling frameworks utilizing internal and public datasets; benchmark and validate performance.Make complex analyses accessible to non-domain experts through democratization of first-principles analysis.Lead the development of ML frameworks that explicitly incorporate first-principles priors.Stay abreast of the latest advancements in deep learning and molecular dynamics.

Summary: Join Interface as a Founding Engineer! We seek versatile engineers (ML, data, full-stack) who are driven, innovative, and eager to make a difference. If you're ready to challenge the status quo and build impactful solutions, we want you on our team! Your Profile:Make swift, informed decisions with a focus on outcomesProactively address issues before they escalateFluent in our technology stack (TypeScript, Python, Docker, LLMs, YOLO, Tesseract, PostgreSQL, AWS, React Native, etc.)Have a proven track record of building functional productsThrive in fast-paced environmentsYour Responsibilities:Engage with users/customers to understand their experiences, challenges, and requirementsDesign robust systems utilized by thousands at billion-dollar enterprisesDevelop autonomous data pipelines for auditing large volumes of documentsEnsure scalable infrastructure managementDeliver quickly – our mantra is progress over perfection.Important Insights:Collaborate directly with the founding team and customersUser needs take precedence over flashy featuresThe team works six days a week in our San Francisco officeEnjoy working in SF: vibrant atmosphere, pleasant weather, and access to the best tech ecosystem in the world Additional Information:We welcome applications from around the globe.We offer competitive compensation, substantial equity, and the chance to influence our early team dynamics.$3,000 referral bonus for successful hires.About Interface: We are pioneers in autonomous safety solutions for the industrial sector, focusing on error detection and correction in industrial documentation. Our AI-powered platform aims to automate compliance tasks across various domains. You will leverage cutting-edge technologies at the crossroads of LLMs, computer vision, and data frameworks to redefine industry standards.

Anthropic is looking for a Research Engineer focused on model evaluations. This position involves research and development to assess and strengthen the performance of AI models. Teams are based in San Francisco and New York City, and the role supports remote work with required travel. Key responsibilities Design and implement evaluations for Anthropic's AI models Collaborate with team members to enhance model performance Contribute to research that pushes the boundaries of AI systems Location Remote-friendly (travel required) San Francisco, CA New York City, NY

Zyphra is an innovative artificial intelligence company located in the heart of San Francisco, California.The Opportunity:Join our dynamic team as a Research Engineer - Audio & Speech Models, where you will play a pivotal role in advancing Zyphra’s Audio Team. You will be instrumental in developing cutting-edge open-source text-to-speech and audio models. Your contributions will span the full spectrum of the model training process, from data collection and processing to the design of innovative architectures and training approaches.Your Responsibilities:Conduct large-scale audio training operationsOptimize the performance of our training infrastructureCollect, process, and evaluate audio datasetsImplement architectural and methodological improvements through rigorous testingWhat We Seek:A strong research mindset with the ability to navigate projects from ideation to implementation and documentation.Proficiency in rapid prototyping and implementation, allowing for swift experimentation.Effective collaboration skills in a fast-paced research environment.A quick learner who is eager to embrace and implement new concepts.Excellent communication abilities, enabling you to contribute to both research and engineering tasks at scale.Preferred Qualifications:Expertise in training audio models, such as text-to-speech, ASR, speech-to-speech, or emotion recognition.Experience with training audio autoencoders.Solid understanding of signal processing, particularly in audio.Familiarity with diffusion models, consistency models, or GANs.Experience with large-scale (multi-node) GPU training environments.Strong understanding of experimental methodologies for conducting rigorous tests and ablations.Interest in large-scale, parallel data processing pipelines.Competence in PyTorch and Python programming.Experience contributing to large, established codebases with rapid adaptation.

Company OverviewEcho Neurotechnologies is an innovative startup in the Brain-Computer Interface (BCI) sector, pioneering advancements through superior hardware engineering and artificial intelligence solutions. Our mission is to develop state-of-the-art technologies that empower individuals with disabilities, enhancing their independence and overall quality of life.Team CultureBecome a part of a dynamic team of passionate and knowledgeable professionals. Our early-stage environment allows you to influence critical decisions that lead to significant and long-term impacts. We value ongoing learning and development, promoting cross-functional collaboration where your input is essential to our success.Job SummaryWe are looking for an adept Applied AI Scientist specializing in language and contextual modeling to enhance our team. The successful candidate will utilize machine learning and AI principles to design, develop, optimize, personalize, and miniaturize advanced language and context models for brain-computer interface applications, aiming to make a tangible difference in the lives of patients with physical disabilities.Key ResponsibilitiesLanguage modeling: Utilize your deep understanding of language models (LMs) to develop tailored solutions for brain-computer interface applications, including fine-tuning and customization of large language models (LLMs).Context modeling: Create and implement machine learning pipelines that facilitate real-time inference across multiple input streams, deploying both proprietary and industry-standard models to analyze audio, video, and application states.General ML practices & adherence to company standards: Focus on model dissection for enhanced interpretability, enabling the extraction of rich latent representations from extensive models for broader application.

About NudgeAt Nudge, we are dedicated to pioneering advanced technology that interfaces with the human brain to enhance lives. Our initial focus is on creating a revolutionary non-invasive, ultrasound-based device designed to stimulate and image the brain with exceptional clarity and depth. This integrated initiative encompasses the development of state-of-the-art hardware, software, and robust research capabilities aimed at delivering transformative products that can positively impact millions — and ultimately billions — of individuals.To achieve our ambitious goals, we are committed to building elite teams across all functions. We seek individuals who excel in their fields, believe in the value of tackling challenging problems, and are relentless in their execution. Our environment fosters the highest standards of rigor and integrity.About the RoleCollaborate with research and engineering teams to conduct high-quality data collection for various studies and R&D experiments.Implement experimental protocols: administer cognitive tasks and gather imaging/physiological data across clinical and non-clinical populations.Oversee participant workflows from start to finish: recruitment, screening, scheduling, and informed consent management.Acquire knowledge in operating neuromodulation and imaging systems, adhere to SOPs, and maintain precise equipment logs.Contribute to documentation processes, perform data quality checks, and assist in analysis to advance neurotechnology development.About YouA minimum of 2 years of relevant research, clinical, or laboratory experience (academic or industry).Bachelor’s degree in a scientific, mathematical, or engineering discipline (including neuroscience, cognitive science, psychology, or computer science), or equivalent experience.Proven track record of significant contributions in previous roles.Excellent interpersonal and communication skills.Experience with data collection and analysis.Demonstrates high integrity in all professional interactions.

Join Interface as a Forward Deployed Engineer! We are on the lookout for innovative generalist engineers (machine learning, data, full-stack) who are not afraid to push boundaries and have a strong drive to succeed. If you thrive in a fast-paced environment and believe in building quickly to achieve results, we want you on our team!Who You Are:You make quick, strategic decisions that can be reversed easily.You proactively identify and resolve issues before they are brought to your attention.You are proficient with our technology stack, including TSX, Python, Docker, LLMs, YOLO, Tesseract, PostgreSQL, AWS, and React Native.You have a track record of building impactful products that are actively used.You excel in dynamic and chaotic environments.Your Responsibilities:Engage with users and customers to understand their experiences, challenges, and needs.Design and architect systems that are utilized daily by large-scale enterprises.Develop autonomous data pipelines that efficiently audit vast amounts of documents.Manage scalable infrastructure to support our growing needs.Deliver solutions rapidly, as we believe that perfectionism can impede progress.Real Talk:Collaborate closely with the founding team and our customers.Prioritize user needs over flashy features and trends.Expect to work six days a week at our office.Be ready for an intense working environment in San Francisco, known for its excellent weather and vibrant tech ecosystem.Additional Information:Remote applications are welcomed from candidates around the globe.We offer competitive salaries, substantial equity, and the opportunity to influence early-stage decisions.Receive a $3,000 bonus for successful referrals!About Interface: We are the leaders in autonomous safety solutions for the industrial sector. We are developing an advanced AI-powered auditing platform that identifies and rectifies errors in various industrial documents, including regulatory filings and CAD files. Join us at the forefront of innovation where LLMs, computer vision, and data pipelines converge to redefine compliance and safety standards.

Merge Labs is at the forefront of research, aiming to connect biological systems with artificial intelligence, thereby enhancing human capacity, autonomy, and overall experience. Our objective involves pioneering innovative strategies for brain-computer interfaces that operate at high bandwidth, seamlessly integrate advanced AI technologies, and ensure safety and accessibility for all users.About the Team:Our Bioengineering team is dedicated to the design, development, and assessment of biotechnologies that will serve as the cornerstone for next-generation brain-computer interfaces. We bring together expertise in molecular engineering, synthetic biology, neuroscience, and cutting-edge physical techniques such as ultrasound to create less invasive, high-bandwidth connections with neural circuits. The team validates our core molecular technologies through rigorous in vitro and in vivo testing and showcases their capabilities in animal models. We develop customized experimental setups and pipelines, collaborating closely with engineers and data scientists. Our interdisciplinary approach fosters innovative solutions to some of the most complex challenges in biotechnology. As part of this initiative, we are developing methods for precise light delivery and detection within the intact brain, which will advance our brain-computer interface research, utilizing sophisticated optical systems that integrate optics, mechanics, electronics, and control software.About the Role:In the position of Optical Systems Engineer, you will be responsible for designing, constructing, and validating optical systems and associated software to facilitate high-performance neuroscience experiments in rodents. You will leverage optical and mechanical design tools to develop and characterize multifunctional imaging systems, integrating them with other modalities, including ultrasound. This role involves close collaboration with neuroscientists, mechanical and electrical engineers, and data scientists to deliver robust hardware and software platforms that support sophisticated biological research.In this role, you will:Design optical systems utilizing ray-tracing and CAD tools such as Zemax and SolidWorks/Inventor.Construct and align optical systems, including illumination and camera-based detection modules.Develop online data processing pipelines that facilitate closed-loop brain interfaces.Prototype and evaluate closed-loop optical brain interfaces.Collaborate with mechanical and electrical engineers to merge optics with sensors, actuators, and control electronics.Establish and carry out optical calibration processes to ensure system accuracy.

Join Perplexity as a Research Engineering Manager, where you will spearhead a team of exceptional AI researchers and engineers dedicated to crafting the advanced models that power our innovative products. Our talented team has pioneered some of the most sophisticated models in agentic research, query understanding, and other critical domains that demand precision and depth. As we broaden our user base and expand our product offerings, our proprietary models are increasingly essential for delivering a premium experience to the world's most discerning users.You will explore our extensive datasets of conversational and agentic queries, applying state-of-the-art training methodologies to enhance AI model performance. Through proactive technical and organizational leadership, you will empower your team to create cutting-edge models for the applications that are most significant to our business and our users.

About Sygaldry TechnologiesSygaldry Technologies is at the forefront of innovation, developing quantum-accelerated AI servers designed to significantly enhance the speed of AI training and inference. By merging quantum computing with AI, we are navigating the challenges of increasing compute costs and energy constraints, paving the way towards superintelligence. Our AI servers leverage a diverse range of qubit types in a fault-tolerant architecture, achieving the necessary balance of cost, scalability, and speed for advanced AI applications. We are committed to pioneering new frontiers in physics, engineering, and AI, tackling the most complex challenges with a culture grounded in optimism and rigor. We seek individuals passionate about defining the convergence of quantum and AI and making a meaningful global impact.About the RoleGenerative AI is revolutionizing computational possibilities but reveals the limitations of classical hardware. While diffusion models yield remarkable outcomes, their iterative sampling and high-dimensional score estimation often lead to computational inefficiencies.We are convinced that quantum computing holds the key to overcoming these challenges. As an ML Research Scientist, you will operate at the intersection of generative modeling and quantum acceleration, formulating theoretical foundations and practical applications that merge these domains. Your focus will be on identifying areas where quantum methods can deliver substantial advantages in generative workflows, providing not just incremental enhancements but transformative improvements grounded in mathematical principles.Your ResponsibilitiesGenerative Model Architecture & EfficiencyInnovate state-of-the-art diffusion and score-based generative models.Investigate computational bottlenecks in sampling, denoising, and likelihood estimation.Design and evaluate novel solver techniques for diffusion ODEs/SDEs.Quantum-Classical IntegrationDiscover mathematical structures in generative models that are suitable for quantum acceleration.Prototype hybrid workflows that utilize quantum subroutines to enhance classical processes.Conduct rigorous benchmarks comparing theoretical advantages against practical benefits in realistic scenarios.Research to ProductionTransform research findings into scalable implementations.Collaborate with quantum hardware teams to guide architectural specifications.Facilitate the integration of research insights into production environments.

Zyphra is a cutting-edge artificial intelligence firm headquartered in the vibrant city of San Francisco, California.Position Overview:As a Research Scientist specializing in Model Architectures, you will play a pivotal role in Zyphra’s AI Architecture Research Team. Your responsibilities will include the design and thorough evaluation of innovative model architectures and training methodologies aimed at enhancing essential modeling capabilities (e.g., loss per flop or loss per parameter) and tackling core limitations inherent in current models. You will collaborate closely with our pre-training team to ensure that your findings are seamlessly integrated into our next-generation models.Qualifications:A strong research acumen and intuition.Proven ability to navigate research projects from initial conception to execution and final write-up.Exceptional implementation and prototyping skills, with the capability to swiftly transform ideas into experimental outcomes.A collaborative spirit and the ability to thrive in a fast-paced research environment.A deep curiosity and enthusiasm for understanding intelligence.Requirements:Experience with long-term memory, RAG/retrieval systems, dynamic/adaptive computation, and alternative credit assignment strategies.Knowledge of reinforcement learning, control theory, and signal processing techniques.A passion for exploring and critically evaluating unconventional ideas, with the ability to maintain a unique perspective.Familiarity with modern training pipelines and the hardware necessities for designing efficient architectures compatible with GPU hardware.Strong understanding of experimental methodologies for conducting rigorous ablations and hypothesis testing.High proficiency in PyTorch and Python programming.Ability to quickly assimilate into large pre-existing codebases and contribute effectively.Prior publication of machine learning research in reputable venues.Postgraduate degree in a scientific discipline (e.g., Computer Science, Electrical Engineering, Mathematics, Physics).Why Join Zyphra?We emphasize a structured research methodology that systematically addresses ambitious challenges in AI.

At Merge Labs, we are at the cutting edge of research, striving to connect biological and artificial intelligence for the enhancement of human capabilities, agency, and experiences. Our mission is to create groundbreaking brain-computer interfaces that facilitate high-bandwidth interactions with the brain, seamlessly integrated with advanced AI technologies, while remaining safe and accessible for all.About Our TeamWe are dedicated to pioneering the most sophisticated interfaces to the brain, enabling interaction with neurons on an unprecedented scale. Achieving this vision requires innovative engineering that pushes the boundaries of what's achievable. Our team is a collective of exceptional builders in electrical engineering, mechanical engineering, mixed-signal IC design, materials science, systems engineering, and engineering physics. We approach challenges from fundamental principles, collaborate across disciplines, and develop scalable technologies. Our rapid prototyping, testing, and iterative processes are driven by a commitment to excellence.Role OverviewWe are searching for a Staff Electrical Engineer to take charge of the architecture, design, and validation of our core electronic systems, as well as the infrastructure utilized in R&D, manufacturing, and clinical settings. This position requires profound technical knowledge of complex electronic systems, including mixed-signal, power, and FPGA/ASIC integration, along with strong software skills (Python/C) to spearhead the development of our testing infrastructure. You will manage the entire lifecycle, from architectural design to validation and manufacturing transfer, while nurturing critical vendor relationships and establishing benchmarks for electrical engineering excellence at Merge.Key Responsibilities:Design, simulate, and verify complex electronic systems to meet rigorous product specifications.Oversee the design and layout of essential PCBAs, emphasizing mixed-signal integrity, power architecture, and thermal management solutions.Create and implement automated test infrastructure (ATE), including developing test firmware (C) and system-level scripting (Python).Maintain technical relationships with design vendors and PCBA assembly/test houses, defining DFT strategies, acceptance criteria, and yield goals.Collaborate closely with internal software, mechanical, and clinical teams to ensure flawless system-level integration and performance.

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.