Machine Learning Data Scientist

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 We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our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.

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 We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative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 Scale AI At Scale AI, we are dedicated to propelling the advancement of AI applications. Over the past eight years, we have established ourselves as the premier AI data foundry, supporting groundbreaking innovations in fields such as generative AI, defense technologies, and autonomous vehicles. Following our recent Series F funding round, we are intensifying our efforts to harness frontier data, paving the way toward achieving Artificial General Intelligence (AGI). Our work with enterprise clients and governments has enhanced our model evaluation capabilities, allowing us to expand our offerings for both public and private evaluations. About the ACE Team The Agent Capabilities & Environments (ACE) team, a vital part of Scale’s Research organization, unites customer-focused Researchers and Applied AI Engineers. Our primary mission is to conduct research on agent environments and reinforcement learning reward signals, benchmark autonomous agent performance in real-world contexts, and develop robust data programs aimed at enhancing the capabilities of Large Language Models (LLMs). We are committed to creating foundational tools and frameworks for evaluating models as agents, focusing on autonomous agents that interact dynamically with a wide range of external environments, including code repositories and GUI interfaces. About This Role This position sits at the cutting edge of AI research and its practical applications, concentrating on the data types necessary for the development of state-of-the-art agents, including browser and software engineering agents. The ideal candidate will investigate the data landscape required to propel intelligent and adaptable AI agents, steering the data strategy at Scale to foster innovation. This role demands not only expertise in LLM agents and planning algorithms but also creative problem-solving skills to tackle novel challenges pertaining to data, interaction, and evaluation. You will contribute to influential research publications on agents, collaborate with customer researchers, and partner with the engineering team to transform these advancements into scalable real-world solutions.

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.

Role overview Coframe is looking for Applied Scientists based in the San Francisco Bay Area. This position focuses on transforming platform data into actionable insights and results. The work brings together reinforcement learning, experimentation, and systems for personalization or ranking. What you will do Build models and strategies that support customer growth with limited manual intervention Use reinforcement learning and experimentation methods to address practical challenges Convert raw data into recommendations that guide strategic choices Location This role is based in the San Francisco Bay Area.

About Wispr FlowAt Wispr Flow, we strive to make device interaction as seamless as conversing with a friend.Wispr Flow has revolutionized voice dictation, now preferred by users over traditional keyboards due to its unparalleled accuracy on the first attempt. Our platform is context-aware, personalized, and effective across all devices, whether desktop or mobile.By 2026, we aim to expand beyond dictation to develop native actions within an agentic framework that comprehends and responds to user needs reliably.Our diverse team comprises AI researchers, designers, growth specialists, and engineers dedicated to reimagining human-computer interaction. We value team members who prioritize open communication, exhibit a user-centric mindset, and pay meticulous attention to detail. Our collaborative environment fosters spirited discussions, truth-seeking, and tangible impact.Having achieved a remarkable 150% revenue growth quarterly for the past year, we have successfully raised $81 million from top-tier venture capitalists and renowned angel investors.

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.

At Causal Labs, we are on a groundbreaking mission to develop general causal intelligence—artificial intelligence that not only predicts future events but also determines the most effective actions to influence those outcomes.To achieve this monumental goal, we are constructing a Large Physics Foundation Model (LPM). Our focus is on domains governed by physical laws, which inherently exhibit cause-and-effect relationships, setting them apart from traditional visual or textual data.Weather serves as the ideal training environment for our LPM, being one of the most extensively observed physical systems available. It provides immediate, objective feedback from sensory observations and boasts data scales significantly larger than those currently employed to train existing language models.Our team at Causal Labs includes leading researchers and engineers with backgrounds in self-driving technology, drug discovery, and robotics, hailing from prestigious organizations such as Google DeepMind, Cruise, Waymo, Meta, Nabla Bio, and Apple. We firmly believe that achieving general causal intelligence will represent one of the most critical technological advancements for our civilization.We are seeking innovative researchers eager to confront unsolved challenges in the field.This role presents an opportunity to create powerful models rooted in observable feedback and verifiable ground truths. If you possess experience in pioneering research and training large-scale models from the ground up in areas such as language and vision models, robotics, or biology, we invite you to join our mission.

At Scale AI, we are the premier partner for data and evaluation in the rapidly evolving field of artificial intelligence. Our commitment to advancing the assessment and benchmarking of large language models (LLMs) positions us at the forefront of AI innovation. We are dedicated to creating leading-edge LLM evaluation methodologies that set new benchmarks for model performance. Our research teams collaborate with the top AI laboratories in the industry to provide high-quality data, accelerate progress in generative AI research, and inform what excellence looks like in this domain. As a Staff Machine Learning Research Scientist on our LLM Evals team, you will spearhead the creation of novel evaluation methodologies, metrics, and benchmarks to assess the strengths and weaknesses of cutting-edge LLMs. Your work will shape our internal strategies and influence the broader AI research community, making this role essential for establishing best practices in data-driven AI development.

Join Handshake as a Machine Learning Research Scientist and contribute to groundbreaking projects that leverage advanced algorithms and data analysis to drive innovation. In this role, you will collaborate with a dynamic team to design, implement, and evaluate machine learning models that enhance our products and services. Your expertise will be pivotal in unlocking new insights from data, improving user experiences, and shaping the future of our technology.

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.

Join Our Team as a Senior Applied Scientist!At Gridware, we are on a mission to revolutionize grid management through innovative technology. Based in San Francisco, we are pioneering a cutting-edge approach known as Active Grid Response (AGR). This initiative focuses on enhancing the reliability and safety of the electrical grid by monitoring its electrical, physical, and environmental parameters. Our advanced platform leverages high-precision sensors to identify potential issues early, facilitating proactive maintenance and minimizing outages. Backed by leading climate-tech and Silicon Valley investors, we are poised to make a significant impact in the energy sector. For more insights on our work, visit www.Gridware.io.Role Overview:We are looking for a talented Senior Applied Scientist with a strong background in machine learning and digital signal processing (DSP). In this role, you will be responsible for designing sophisticated models that operate on diverse time-series sensor data within resource-constrained environments. Your work will involve developing algorithms that optimize for accuracy while adhering to strict power and memory constraints, thereby advancing Gridware’s edge intelligence capabilities. This position requires a blend of applied research, model optimization, and close collaboration with hardware and firmware teams to implement low-level solutions.

Join Reka as a Member of the Technical Staff in Applied AI!Leverage cutting-edge AI models to tackle intricate real-world challenges.Engage in close collaboration with researchers and fellow team members to explore the latest developments in AI and ML.Partner with our customers to seamlessly integrate our innovative models into their existing technology frameworks.Drive business success with a strong sense of product ownership and accountability.Be part of a pioneering team in a rapidly growing environment, taking on diverse roles.

At Tzafon, we are pioneering the development of scalable computing systems and pushing the boundaries of machine intelligence with our foundation model lab. Located in vibrant cities such as San Francisco, Zurich, and Tel Aviv, we have successfully secured over $12 million in funding to fuel our mission of expanding the horizons of AI technology.Our dynamic team comprises engineers and scientists with extensive expertise in machine learning infrastructure and research. Founded by IOI and IMO medalists, PhDs, and seasoned professionals from top tech firms, we specialize in training advanced models and constructing robust infrastructures to automate tasks across various real-world scenarios.In this role, you will collaborate closely with our product and post-training teams to deploy Large Action Models that drive impactful results. Your responsibilities will include building evaluation frameworks, establishing benchmarks, and creating fine-tuning pipelines to ensure optimal model performance.

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.

Join our dynamic team at Laurel as a Senior Machine Learning Data Scientist specializing in Analytics. In this pivotal role, you will leverage your expertise in machine learning and data analysis to drive innovative solutions that enhance our decision-making processes. You will collaborate with cross-functional teams to design and implement predictive models, analyze complex datasets, and translate insights into actionable strategies.Your contributions will be key in shaping the future of our analytics framework, enabling us to better serve our clients and stakeholders. If you’re passionate about data science and eager to make a significant impact, we want to hear from you!

About UsAt Speak, our mission is to revolutionize language learning.Learning a new language can transform lives by unlocking opportunities in diverse cultures, careers, and communities. With over two billion individuals around the globe striving to learn a language, we recognize that traditional one-on-one tutoring remains difficult to access at scale and has seen little innovation over recent decades. Speak is pioneering an AI-driven, human-level tutor accessible right from your pocket, providing a conversation-first experience where learners can practice speaking, receive immediate feedback, and progress through meticulously crafted lessons. Our goal is to facilitate a comprehensive journey from beginner to proficient speaker across various languages.Launched in South Korea in 2019, Speak has quickly become the leading language learning app in the region, now reaching learners across numerous markets and offering instruction in 15+ languages. Supported by over $150 million in venture capital from prestigious investors such as OpenAI, Accel, Founders Fund, and Khosla Ventures, our team is distributed across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.Role OverviewWe are seeking a skilled Machine Learning Engineer specializing in speech to join our innovative team. In this role, you will take charge of the entire modeling pipeline for speech recognition, encompassing training, experimentation, deployment, and ongoing monitoring. Collaborating closely with Product teams, you will design cutting-edge learning experiences and assess the effectiveness of production models on our users. As part of a nimble and dynamic team, you'll contribute as both a developer and a thought partner on projects related to ASR, assessments, pronunciation improvements, content personalization, and more. This is an exhilarating opportunity to be part of an ML team focused on crafting personalized learning experiences that will transform language education for millions worldwide.

Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through advanced cell rejuvenation techniques aimed at reversing diseases, injuries, and age-related disabilities.For more information, please visit our website at altoslabs.com.Our ValueWe embrace a singular value at Altos: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe recognize that diverse perspectives are vital to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders collaborate from around the globe, united by a common mission. Our commitment to fostering a sense of belonging ensures that every employee feels valued for their unique insights. We all share the responsibility of maintaining a diverse and inclusive workplace.What You Will Contribute To AltosAs a Senior or Principal Machine Learning Scientist, you will be pivotal in developing groundbreaking generative AI/ML models that address multi-modal, multiscale biological challenges—from virtual cell simulations to agentic target assessments. We seek an innovative, hands-on individual who thrives in a collaborative and fast-paced environment, emphasizing teamwork, transparency, scientific excellence, originality, rigor, and integrity.