Senior Machine Learning Engineer - Distributed ML Systems

About Pinterest:At Pinterest, we empower millions of users to discover creative ideas, envision new possibilities, and curate memories that last a lifetime. Our mission is to inspire everyone to create a life they love, driven by the passion and creativity of our dedicated team.Join a vibrant career where you can ignite innovation for millions, turn your passion into growth opportunities, and celebrate diverse experiences while enjoying the flexibility to perform at your best. Building a career you love is within reach.With over 500 million global users and 300 billion ideas saved, our Machine Learning engineers are at the forefront of creating personalized experiences that enhance how Pinners interact with our platform. With a team of just over 3,000 talented individuals, you'll have unparalleled access to a wealth of data and contribute to large-scale recommendation systems like never before.

About UsAt Applied Compute, we are pioneering the development of Specific Intelligence for enterprises, creating agents that continuously learn from a company’s processes, data, expertise, and objectives. Our mission is to bridge the gap between isolated AI capabilities and their effective application within real business environments. Traditional AI systems often fall short as they lack the ability to adapt based on feedback. Our innovative continual learning layer captures context, memory, and decision-making processes across the enterprise, enabling specialized agents to engage in meaningful work.What Excites Us: We operate at the exciting intersection of product development and cutting-edge research. Our product team designs the platform that empowers a new generation of digital coworkers, while our research team drives advancements in post-training and reinforcement learning to enhance user experiences. As an applied research engineer, you will work directly with clients to implement models in production, combining robust product development with deep research insights to facilitate AI integration in enterprises.Meet Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have previously built reinforcement learning infrastructure at OpenAI, established data foundations at Scale AI, and contributed to significant systems at companies like Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, including DoorDash, Mercor, and Cognition, and are proud to be backed by reputable investors such as Benchmark, Sequoia, and Lux.Who Thrives Here: We seek individuals who are passionate about applying innovative research and complex systems to solve real-world challenges. You should feel comfortable navigating new environments rapidly—be it a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment for customer interaction, empathy, and a deep understanding of their operational workflows are essential. Candidates with entrepreneurial backgrounds, extensive side projects, or a proven track record of end-to-end ownership typically excel in our environment.

Join Our Team at MacroscopeAt Macroscope, we are dedicated to being the definitive source of truth for any software development company. Our mission is to empower leaders with clarity and provide engineers with the time they need to innovate.We enable leaders to gain insights into the evolution of their products and codebases—tracking changes, understanding team contributions, and identifying progress—all grounded in the ultimate source of truth: the code itself.Founded by experienced entrepreneurs who have successfully built and sold multiple companies, and held executive positions in public tech firms, we are backed by top-tier venture capital firms such as Lightspeed Venture Partners, Thrive Capital, Google Ventures, and Adverb.The RoleWe are seeking a Senior Applied Machine Learning Engineer who will be responsible for designing, developing, and optimizing the ML and AI systems that drive our core offerings. You will have full ownership of the systems, overseeing everything from data collection and evaluation to model experimentation and large-scale production deployment.This cross-functional position entails leading the ML/AI lifecycle for one of our most vital features: AI Code Review. Collaborating closely with our co-founders, you will make pivotal decisions that shape our product's development—ranging from building high-quality datasets to interpreting experimental results and enhancing model performance architecture. Additionally, you will play a significant role in crafting and implementing software that seamlessly integrates our models with our backend applications and user experience, offering a unique opportunity to influence our product's evolution significantly.Technology Stack: Typescript/React (frontend), Golang (backend), Temporal, Google Cloud (GCP), Postgres, Terraform, and custom-built AST "code walkers" in several programming languages including Golang, Typescript, Swift, Python, and Rust.

Join David AIAt David AI, we are pioneering the audio data research landscape. Our research and development approach to data ensures that we deliver datasets with the same precision and rigor that leading AI labs apply to their models. Our mission is to seamlessly integrate AI into everyday life, leveraging audio as a key channel. As we witness advancements in audio AI and the emergence of new use cases, we recognize that high-quality training data is the critical component. This is where David AI steps in.Founded in 2024 by a group of former engineers and operators from Scale AI, we have rapidly established partnerships with major FAANG companies and AI labs. Recently, we secured a $50M Series B funding round from prominent investors including Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, and First Round Capital.Our team is sharp, humble, and ambitious. We are on the lookout for talented individuals in research, engineering, product management, and operations to join us in our mission to redefine the audio AI landscape.About Our Machine Learning TeamOur Machine Learning team operates at the forefront of innovative research and practical application, transforming raw audio into high-quality data for top AI labs and enterprises. We manage the entire machine learning lifecycle—from exploring novel speech processing algorithms to deploying models that handle terabytes of audio data daily.Your RoleAs an Applied ML Engineer at David AI, you will develop state-of-the-art speech and audio models, establish production inference systems, and create robust pipelines that demonstrate the true potential of high-quality data.Key ResponsibilitiesResearch and Design: Create solutions using advanced signal processing algorithms and cutting-edge ML models tailored for speech and audio applications.Development: Build production-grade inference algorithms, pipelines, and APIs in collaboration with cross-functional teams to extract valuable insights for our clients.Collaboration: Work alongside our Operations team to gather valuable training and evaluation datasets to enhance our model quality.Architecture: Design systems that ensure durable and resilient inference and evaluations.

At Exa, we are revolutionizing the way AI applications access information by building a cutting-edge search engine from the ground up. Our team is dedicated to developing a robust infrastructure capable of crawling the web, training advanced embedding models, and creating high-performance vector databases using Rust to facilitate seamless searches.As part of our ML team, you'll be instrumental in training foundational models that refine search capabilities. Our mission? To deliver precise answers to even the most complex queries, effectively transforming the web into an incredibly powerful knowledge database.We are seeking a talented Machine Learning Research Engineer who is passionate about crafting embedding models that enhance web search efficiency. Your responsibilities will include innovating novel transformer-based architectures, curating extensive datasets, conducting evaluations, and continuously improving our state-of-the-art models.

SentiLink is at the forefront of delivering cutting-edge identity and risk management solutions, providing both individuals and institutions the ability to transact with assurance. We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative approach; our real-time APIs have successfully verified hundreds of millions of identities, initially focusing on the financial sector and quickly expanding into various new markets. SentiLink enjoys the support of prestigious investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We are proud to have received accolades from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and we have been featured in the Forbes Fintech 50 list every year since 2023. Notably, we made history as the first company to deploy the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.SentiLink accommodates a flexible work environment, ranging from fully remote positions to in-office roles. As a digital-first company, we emphasize collaboration across teams in the U.S. and India. We have physical locations in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., alongside offices in Gurugram (Delhi) and Bengaluru in India. For those near our offices, we encourage regular office attendance. Certain roles, such as our engineering team in India, are designed to be primarily in-office.Role Overview:As a Senior Applied ML Scientist at SentiLink, you will be instrumental in developing our core products: advanced models aimed at identifying fraudulent activities while enhancing our expanding array of financial risk solutions. Your expertise as a seasoned researcher will be essential, making you the authoritative figure in your domain. You will frequently engage in high-impact projects that necessitate a profound understanding of the field, critical analytical skills, and robust technical capabilities. Collaboration with various teams across the organization will be key as you investigate new fraud types, innovate product offerings, and conduct analyses to support our sales and marketing efforts.

About HebbiaHebbia is an innovative AI platform designed specifically for investors and bankers, empowering them to generate alpha and unlock new opportunities.Founded in 2020 by George Sivulka and backed by industry leaders like Peter Thiel and Andreessen Horowitz, Hebbia supports investment decisions for major firms including BlackRock, KKR, Carlyle, Centerview, and accounts for 40% of the world's largest asset managers. Our flagship product, Matrix, is recognized for its unparalleled accuracy, speed, and transparency in AI-driven analysis, managing assets exceeding $30 trillion globally.We provide critical insights that give finance professionals a competitive advantage by revealing signals that are invisible to the human eye and identifying hidden opportunities while expediting decision-making with remarkable speed and certainty. We aim to revolutionize the way capital is allocated, risk is mitigated, and value is generated across markets.Hebbia is not just a tool; it is the competitive edge that enhances performance, alpha, and market leadership.The TeamOur Agents team is dedicated to building sophisticated reasoning, copiloting, and retrieval capabilities that unlock significant insights for real-world applications. We develop everything from foundational document understanding features to co-piloting experiences for matrix and extensive, multi-source research. Our proprietary agentic frameworks are designed for scalability, utilizing distributed systems.We focus on creating systems that are not only successful but also reliable, explainable, and adaptable for the vast data our clients encounter. Our mission is to unveil the unknowable unknown for customers worldwide.Our goal is to create a product that becomes indispensable to our users, offering an experience as delightful as their favorite consumer products. We prioritize swift innovation and the development of first-of-their-kind systems.

Join us at Foxglove, where we are revolutionizing the robotics industry by building robust data infrastructure for real-world applications.As robotics transitions from research environments to practical implementations in factories, warehouses, vehicles, and field operations, data becomes essential for engineers to troubleshoot failures, understand unexpected behaviors, and enhance robotic systems.At Foxglove, we provide the observability, visualization, and data infrastructure that enable robotics and autonomous systems teams to efficiently ingest, store, query, replay, and analyze extensive volumes of multimodal sensor data from live systems and production fleets.About the RoleWe are seeking a talented Applied Machine Learning Engineer with strong infrastructure insights to design, deploy, and scale the machine learning systems that power our data platform. In this impactful role, you will be responsible for optimizing production ML infrastructure—from enhancing inference pipeline throughput to establishing training and evaluation workflows. You will focus on high-priority challenges, such as developing retrieval applications for petabyte-scale multimodal robotics data, utilizing cutting-edge models to create high-performance search and data mining products, and fostering an internal ML flywheel for rapid iteration. This is a hands-on, application-driven position rather than a research-focused role.Key ResponsibilitiesDeploy and manage inference infrastructure for production ML workloads, focusing on model serving, scalability, and cost efficiency.Build and oversee vector database integrations and embedding applications to facilitate semantic search across various multimodal robotics data types (image, video, point cloud, and time series).Design and implement evaluation and training infrastructure to enhance model performance rapidly.Lead cloud architecture decisions and tools to optimize inference latency, throughput, cost, and reliability at scale.Collaborate closely with product engineers to deliver application-driven ML features that empower developers at the forefront of robotics and physical AI, steering clear of prototype experiments.Identify appropriate off-the-shelf solutions for production and determine when to build versus buy.

Join Our Innovative TeamAt OpenAI, we are pioneering the field of artificial intelligence, empowering innovation and shaping the future through transformative research. Our mission is to democratize AI, ensuring its benefits are accessible to all. We are on the lookout for forward-thinking Research Engineers to join our Applied Group, where you will convert groundbreaking research into practical applications that can revolutionize industries, enhance human creativity, and tackle complex challenges.Your Impactful RoleAs a Research Engineer within OpenAI's Applied Group, you will collaborate with some of the brightest minds in AI. Your work will involve deploying cutting-edge models in production settings, transforming theoretical breakthroughs into impactful solutions. If you are passionate about making AI technology accessible and effective, this is your opportunity to leave a significant impact.In this role, you will:Innovate and Deploy: Create and implement advanced machine learning models addressing real-world issues. Translate OpenAI's research from theory to practice, developing AI-driven applications that make a meaningful difference.Collaborate with Experts: Engage closely with researchers, software engineers, and product managers to comprehend intricate business challenges and deliver AI-based solutions. Become part of a vibrant team where creativity and ideas flourish.Optimize and Scale: Develop scalable data pipelines, fine-tune models for peak performance and precision, and ensure readiness for production. Contribute to projects that leverage state-of-the-art technology and innovative methodologies.Learn and Lead: Stay at the forefront of advancements in machine learning and AI. Participate in code reviews, share insights, and exemplify best practices to maintain high standards in engineering.Make a Difference: Oversee and maintain deployed models, ensuring they consistently deliver value. Your contributions will directly shape how AI benefits individuals, businesses, and society as a whole.You may excel in this position if you possess:A Master's or PhD in Computer Science, Machine Learning, Data Science, or a related discipline.Proven experience in deep learning and transformer models.Expertise with frameworks such as PyTorch or TensorFlow.A robust understanding of data structures, algorithms, and software engineering principles.Experience with cloud platforms and deploying machine learning models in production.

SentiLink is at the forefront of transforming identity verification and risk management, enabling both institutions and individuals to conduct transactions with confidence. We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our rapid growth reflects the significant traction we've garnered, with our real-time APIs successfully verifying hundreds of millions of identities, especially within the financial services sector, while swiftly expanding into other markets. SentiLink enjoys the backing of top-tier investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We have received accolades from major publications including TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and have consistently ranked on the Forbes Fintech 50 list since 2023. Notably, we made history by being the first company to implement the eCBSV and provided testimony before the United States House of Representatives regarding the future of identity verification.SentiLink promotes a flexible working environment, offering various work arrangements ranging from fully remote to in-office. As a digital-first organization, we emphasize strong collaboration across teams in the U.S. and India. Our offices are located in cities including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram (Delhi) and Bengaluru in India. If you are near any of these locations, we encourage regular in-office engagement. Some positions are designed to be hybrid or in-office. For instance, our engineering team in India primarily operates from our Gurugram office.

Join Perplexity as an Applied Machine Learning Engineer and be at the forefront of innovation in artificial intelligence. You will design, develop, and refine advanced AI models that enhance user experiences globally. Your expertise in machine learning will allow you to create scalable solutions for user personalization, query comprehension, and content discovery, catering to the curiosity of millions.Key ResponsibilitiesUtilize cutting-edge ML and LLM techniques to address challenges in:Personalization (LLM memory, context summarization, retrieval, and ranking);Query Understanding (intent modeling, rewriting, agentic decomposition);Content Discovery (feed ranking and surfacing).Conduct thorough evaluations of LLM/ML models through offline and online methods, designing comprehensive experiments and metrics that yield insights into quality and impact.Manage the full model lifecycle from research to deployment, including data analysis, modeling, evaluation, A/B testing, and iterative enhancements.Collaborate with cross-functional teams, including engineers, PMs, data scientists, and designers, to ensure AI implementations yield significant product enhancements.Stay updated on ML/AI advancements by assessing and integrating new research and algorithms into the product lifecycle.Preferred QualificationsOver 5 years of experience in developing and deploying robust ML/AI models for large-scale, user-centric or data-driven applications.Extensive knowledge in deep learning frameworks (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and ranking.Proficient software engineering skills (Python, production-level codebases, collaborative development).Comprehensive experience across the entire ML lifecycle: data analysis, feature engineering, model development, evaluation, and ongoing monitoring/improvement.Effective collaborator and communicator; thrives in fast-paced, cross-functional environments.Inquisitive, motivated by user/product impact, and passionate about advancing applied ML and AI.Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field (or equivalent experience).

About NationGraphAt NationGraph, we are revolutionizing the accessibility and usability of public sector data for businesses targeting municipalities, state agencies, educational institutions, and specialized districts. Our advanced data intelligence engine extracts actionable insights from millions of public sector sources, empowering organizations to make informed decisions. Established in 2024, our mission is to democratize information, ensuring that public data is genuinely accessible to everyone. Discover more at nationgraph.comOur TeamComprises seasoned entrepreneurs who have successfully built, scaled, and exited multiple companies.Developed robust software infrastructure capable of processing billions in transactions.Supported by top-tier venture capitalists and seasoned operating partners with a track record of investing in and nurturing iconic brands.Role OverviewDesign and implement end-to-end machine learning pipelines.Extract and mine data from various online sources through large-scale web crawling and scraping techniques to enhance our models and insights.Convert unstructured text data into structured knowledge using natural language processing (NLP), entity recognition, and bespoke models.Develop and refine text classification models to systematically organize intricate datasets.Enhance retrieval-augmented generation (RAG) systems utilized in our product offerings.Drive our data strategy by identifying and integrating new data sources.Tackle open-ended technical challenges, fostering a culture of learning and collaboration within the team.Primarily utilize Python and SQL for development.QualificationsA strong quantitative background in fields such as computer science, physics, mathematics, or engineering.Solid foundation in mathematics and statistics.A PhD in a quantitative discipline.Expertise in Python programming.Proactive ownership mentality with the ability to address complex technical challenges to create commercial value.A genuine enthusiasm for continuous learning, growth, and uncovering insights from complex datasets.Strong problem-solving, communication, and collaboration abilities in a dynamic work environment.

About UsAt Applied Compute, we specialize in creating Specific Intelligence solutions for enterprises, developing agents that learn continuously from an organization’s processes, data, expertise, and objectives. We recognize a significant gap between the capabilities of AI models in isolation and their practical applications in real-world business contexts. Our systems often fall short because they lack adaptability to feedback. To address this, we are building a continual learning infrastructure that captures context, memory, and decision-making processes throughout the enterprise, enabling specialized agents to effectively execute real tasks.What Excites Us: We operate at a unique intersection where our product team constructs the platform that fuels a new generation of digital coworkers. Our research team pushes the boundaries of post-training and reinforcement learning, creating innovative product experiences. Our applied research engineers collaborate closely with clients to deploy models into production. This blend of strong product focus, deep research, and hands-on customer engagement is crucial for integrating AI into the enterprise. We are product-driven, research-informed, and actively engaged with our clients.Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have built RL infrastructure at leading organizations like OpenAI and Scale AI, and developed systems at Together, Two Sigma, and Watershed. We proudly serve Fortune 50 clients alongside companies like DoorDash, Mercor, and Cognition. Our work is supported by renowned investors, including Benchmark, Sequoia, and Lux.Who Thrives in Our Environment: We seek individuals eager to apply cutting-edge research and complex systems to tackle real-world challenges. You should be adept at quickly adapting to new environments, whether it’s a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment of customer interactions—listening, empathizing, and understanding how tasks are accomplished within their organizations—is essential. Those with entrepreneurial backgrounds, extensive side projects, or demonstrated end-to-end ownership typically excel in our company.

P-1380 Join Databricks as a Senior Applied AI Engineer, where you will harness the power of machine learning, scheduling, and optimization algorithms to enhance the efficiency and performance of our engineering systems and infrastructure. Our Applied AI team tackles some of the most challenging and fascinating issues in the industry, ensuring that Databricks infrastructure and products operate at peak performance and cost efficiency. This role is critical, as our customers depend on us to deliver the most optimized workloads. Your Impact: Develop comprehensive systems from the ground up within a dynamic team of seasoned professionals. Influence the direction of our applied machine learning investment areas by collaborating with engineering and product teams across the organization. Lead the design and implementation of advanced AI models and systems that enhance the capabilities and performance of Databricks' products, infrastructure, and services. Architect and deploy robust, scalable machine learning infrastructure, including data storage, processing, model training, serving components, and monitoring systems to facilitate seamless integration of AI/ML models into production environments. Explore innovative modeling techniques in the realm of machine learning for systems. Contribute to the wider AI community by publishing research, presenting at conferences, and actively engaging in open-source projects, thereby strengthening Databricks' reputation as an industry leader.

Why Join Achira?Become part of an elite team comprising scientists, machine learning researchers, and engineers dedicated to transforming the predictability of the physical microcosm and revolutionizing drug discovery.Explore uncharted territories: we are on a mission to innovate next-generation model architectures that merge AI with chemistry.Engage in large-scale operations: harness massive computational resources, extensive datasets, and ambitious objectives.Take ownership of significant projects from inception to deployment on large-scale infrastructures.Thrive in a culture that values precision, speed, execution, and a proactive mindset.About the PositionAt Achira, we are committed to developing state-of-the-art foundation models that tackle the most complex challenges in simulation for drug discovery and beyond. Our atomistic foundation simulation models (FSMs) serve as world models of the physical microcosm, incorporating machine learning interaction potentials (MLIPs), neural network potentials (NNPs), and various generative models.We are seeking a Machine Learning Research Engineer (MLRE) who excels at the intersection of advanced machine learning and rigorous research methodologies. Collaborate closely with our research scientists to design and enhance intelligent training systems that propel us beyond contemporary architectures into a new era of ML-driven molecular modeling.Your mission is clear yet ambitious: to establish the foundational frameworks for training atomistic simulation models at scale. This entails a deep dive into architecture, data, optimizers, losses, training metrics, and representation learning, all while constructing high-performance systems that maximize the potential of our models. In this role, you will be instrumental in creating a blueprint for pretraining FSMs similar to today’s large-scale generative AI systems, making a significant impact on drug discovery.At Achira, you will have the chance to pioneer models that comprehend and simulate the physical world at an atomic level, achieving unprecedented speed and accuracy.

Company Overview:At Specter, we are pioneering a software-defined control plane for the physical realm, beginning with safeguarding American enterprises through comprehensive monitoring of their physical assets.Our innovative approach leverages a connected hardware-software ecosystem built on advanced multi-modal wireless mesh sensing technology. This breakthrough enables us to reduce the deployment costs and time for sensors by a factor of 10. Our ultimate goal is to establish a perception engine that provides real-time visibility of a company’s physical environment and facilitates autonomous operations management.Co-founders Xerxes and Philip are dedicated to empowering our partners in the rapidly evolving landscape of physical AI and robotics. Join our dynamic and rapidly expanding team comprised of talents from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview:We are seeking a Perception AI Engineer who will be instrumental in transforming sensor data pipelines into actionable insights for our clients.Key Responsibilities:Implement and deploy a range of deep-learning models, including vision, vision-language, and large language models, within our sophisticated distributed perception system.Design and scale a production-ready data collection, labeling, and model retraining platform.Lead the design of a multimodal software user interface.

About Nooks.ai:Nooks is a cutting-edge AI Sales Assistant Platform (ASAP) designed to streamline sales processes, allowing representatives to concentrate on building relationships and closing deals. Our innovative platform has empowered thousands of sales professionals to achieve their targets, saving clients countless hours and generating substantial revenue. Trusted by sales teams at industry leaders like Hubspot, Rippling, and Toast, Nooks is transforming the sales landscape.Backed by over $70M in investments from top-tier venture capital firms, including Kleiner Perkins, Nooks has experienced remarkable growth, achieving a 4x and 3x increase in ARR over the past two years. We are on an ambitious trajectory to triple our growth once again this year.For more information, visit Nooks.ai.The RoleNote: Job title will be aligned with candidate experience.We are seeking a passionate Applied Machine Learning Engineer to join our dynamic team, tackling exciting technical challenges in the emerging field of AI-powered real-time collaboration. This role is pivotal in integrating machine learning features into the Nooks platform. The ideal candidate will have hands-on experience in a business where machine learning plays a central role.Key responsibilities will involve training production models to enhance their accuracy for specific sales applications, while aligning our technical strategy with performance, cost, and feasibility factors.Examples of Engineering Challenges You Might EncounterThese examples are illustrative; prior experience in all areas is not required. We hope you find some of these challenges intriguing!Real-time Audio AI & Precision/Recall/Latency Trade-offs (Algorithms & Models)Utilizing audio data, transcription, silence detection, and multiple signals to discern if a live call is a voicemail, a human, or a dial tree. Managing latency alongside precision/recall trade-offs is crucial for prompt human detection, involving advanced techniques like LLM embeddings, few-shot learning, data labeling, and continuous performance monitoring.Intelligent Call Funnels & Playbooks (Data Wrangling, Backend Engineering, GPT-3, UX)Analyzing the conversational flow to optimize call funnels and playbook strategies, focusing on data visibility and user experience.

bland is looking for a Machine Learning Researcher with a focus on audio. This position is based in San Francisco and centers on advancing how machines process and understand sound. The team works on pushing the boundaries of audio technology for a range of platforms. Responsibilities Research and develop new machine learning techniques for audio applications Contribute to projects that improve audio processing and analysis Collaborate with colleagues to bring research ideas into real-world audio products Location This role requires working onsite in San Francisco.

About UsAt Applied Compute, we are pioneering Specific Intelligence for enterprises through advanced AI agents that learn continuously from organizational processes, data, and objectives. We recognize the significant gap between what AI models can achieve in isolation and their performance within actual business contexts, often failing to adapt to feedback. Our mission is to build a continual learning layer that captures context, memory, and decision traces across enterprises, creating environments where specialized agents excel at real tasks.Why Join Us? We operate at a unique intersection of product development and research. Our product team is developing the platform that empowers a new generation of digital coworkers, while our research team is advancing post-training and reinforcement learning to enhance product experiences. As applied research engineers, we work closely with customers to deploy models into production effectively. This blend of robust product focus, deep research, and customer engagement is our strategy for successfully integrating AI into enterprise operations. We are product-led, research-enabled, and strategically deployed.Meet Our Team: Our team consists of engineers, researchers, and operators, many of whom are former founders. We have established RL infrastructure at OpenAI, developed data foundations at Scale AI, and built systems at Together, Two Sigma, and Watershed. We collaborate with Fortune 50 clients, including DoorDash, Mercor, and Cognition, and are backed by esteemed investors such as Benchmark, Sequoia, and Lux.Who Excels Here: We seek individuals passionate about applying innovative research and complex systems to overcome real-world challenges. Candidates should thrive in unfamiliar environments, whether it involves navigating new codebases, understanding new customer data architectures, or tackling unfamiliar problem domains. A genuine enjoyment of customer interactions—listening, empathizing, and comprehending how work is accomplished within organizations—is essential. Those with prior entrepreneurial experience, extensive side projects, or a proven ability to manage initiatives from start to finish will thrive in our culture.Your RoleAs a Research Systems Engineer, you will be responsible for training cutting-edge models and developing methodologies that facilitate continual learning within enterprise settings. You will design and execute large-scale experiments, delve into advanced reinforcement learning techniques, and create tools that enhance our understanding of the training process. This role uniquely positions you at the crossroads of research and systems engineering, where you will innovate new algorithms in collaboration with researchers and work alongside infrastructure engineers to deploy them on GPUs.