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Experience Level
Entry Level
Qualifications
Strong foundation in machine learning algorithms and frameworks. Experience with Python and data processing libraries such as Pandas and NumPy. Familiarity with cloud platforms (e.g., AWS, Azure) and deployment tools. Ability to work collaboratively in a team-oriented environment. Excellent problem-solving skills and attention to detail.
About the job
Achira is seeking a Machine Learning Research Engineer to help improve workflows and systems for artificial intelligence projects. This position is based in the San Francisco office.
Role overview
This role centers on developing and refining machine learning pipelines. The focus is on efficient deployment and scaling of AI models in production environments. Collaboration with colleagues from different disciplines is a key part of the work, aiming to bring forward new ideas and solid practices in machine learning systems.
What you will do
Design and optimize machine learning workflows for better performance and scalability
Work closely with cross-functional teams to implement improvements in AI systems
Support the deployment process, helping ensure models run efficiently in real-world settings
Location
This position is based at Achira's San Francisco office.
About Achira
Achira is a leading organization at the forefront of AI technology, dedicated to developing innovative solutions that enhance the efficiency of workflows and systems. Our team comprises passionate individuals who strive to push the boundaries of what's possible in machine learning and artificial intelligence.
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 application…
Full-time|$350K/yr - $475K/yr|On-site|San Francisco
At Thinking Machines Lab, our mission is to enhance humanity's potential through the advancement of collaborative general intelligence. We envision a future where everyone can access the knowledge and tools necessary to leverage AI for their individual needs and objectives.As a team of scientists, engineers, and innovators, we have developed some of the most widely utilized AI products, such as ChatGPT and Character.ai, along with open-weight models like Mistral, and popular open-source projects including PyTorch, OpenAI Gym, Fairseq, and Segment Anything.Role OverviewAt Thinking Machines, we adopt a multimodal-first approach, where multimodality is integral to our scientific goals and infrastructure. We are seeking skilled researchers to push the boundaries of audio capabilities. In this role, you will delve into how audio models can facilitate more natural and efficient communication and collaboration by preserving information and accurately capturing user intent.This position requires strong collaboration across pre-training, post-training, and product development with top-tier researchers, infrastructure engineers, and designers. Here, you will have the chance to influence the foundational capabilities of AI systems that will be utilized by millions globally.This role marries fundamental research with practical engineering, as we do not separate these functions internally. You will be expected to write high-performance code as well as engage with technical reports. It is an ideal position for someone who enjoys both extensive theoretical research and hands-on experimentation while laying the groundwork for how AI learns.Note: This is an evergreen role that remains open continuously to gauge interest in this research area. We receive numerous applications, and there may not always be an immediate match for your skills and experience. Nevertheless, we encourage you to apply, as we routinely review applications and reach out as new opportunities arise. You are welcome to reapply if you gain additional experience, but please avoid applying more frequently than every six months. Occasionally, we also post specific roles for distinct project or team needs, in which case you are welcome to apply directly alongside an evergreen submission.
Bland Inc. seeks a Machine Learning Researcher specializing in Multimodal Large Language Models (LLMs) to join the team in San Francisco. The focus is on advancing AI systems that integrate language with other types of data. Role overview This position centers on research and development aimed at improving how AI models process and understand information from multiple sources, such as text combined with images or other modalities. What you will do Investigate how language interacts with additional data types within multimodal LLMs Create and evaluate new methods to enhance AI model performance Work closely with colleagues on projects designed to push the boundaries of machine learning Location This role is based in San Francisco.
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.
About CartesiaAt Cartesia, we are on a mission to revolutionize artificial intelligence by creating interactive, ubiquitous intelligence that seamlessly adapts to your environment. Our groundbreaking approach tackles the challenge of processing and reasoning over extensive streams of audio, video, and text—1 billion text tokens, 10 billion audio tokens, and 1 trillion video tokens—all while maintaining on-device functionality.Founded by PhDs from the Stanford AI Lab who pioneered State Space Models (SSMs), we combine profound expertise in model innovation and systems engineering with a design-oriented product engineering team. Our aim is to build and deploy cutting-edge models and experiences that push the boundaries of AI.Supported by prominent investors including Index Ventures and Lightspeed Venture Partners, alongside a network of exceptional advisors and over 90 angel investors from diverse industries, we are at the forefront of AI advancement.The RoleAs a Senior Applied Researcher in Audio Understanding, you will confront some of the most complex challenges in audio perception. Your work will extend beyond traditional speech recognition to encompass a comprehensive range of audio understanding tasks, such as speaker identification, emotional interpretation, and navigation of intricate acoustic environments. You'll spearhead high-impact projects that are essential to our vision of developing truly aware AI.What You’ll DoDesign and implement innovative, large-scale models for complex audio understanding tasks, including multi-speaker automatic speech recognition (ASR), diarization, and non-speech audio classification, deploying them effectively at scale.Lead groundbreaking research in areas such as self-supervised learning for audio, few-shot learning, and resilient audio-visual perception.Establish new benchmarks and evaluation standards for our audio understanding systems.Create and manage extensive pre-training and fine-tuning datasets to enhance audio understanding capabilities.What We’re Looking ForIn-depth expertise in ASR, audio understanding, language modeling, or generative modeling.Experience with large-scale training, GPU/TPU acceleration, and model optimization.A strong practical mindset—capable of integrating scientific rigor with real-world applications.
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.
Full-time|$140K/yr - $250K/yr|On-site|San Francisco
About AlljoinedAt Alljoined, we are pioneering the future of communication between humans and technology by developing non-invasive methods to decode brain activity. By leveraging cutting-edge deep learning techniques on extensive EEG datasets collected through cost-effective hardware, we aim to interpret images, text, and video, with a long-term vision of understanding internal thoughts. Our capabilities are industry-leading, and we are fully vertically integrated. Our mission is to create a universal consumer interface that revolutionizes daily interactions both at home and in the workplace.We are on the lookout for exceptional researchers to expand our elite team, dedicated to creating the next transformative interface that enhances individual lives and contributes positively to society.About the RoleWe invite you to apply for the position of Machine Learning Researcher within our core R&D team. In this role, you will be responsible for conceptualizing and executing advanced machine learning models for EEG-based neural decoding, disseminating impactful research, and establishing the foundational infrastructure for our brain decoding systems. You'll collaborate with top-tier experts in neural decoding and AI, driving innovation in brain-computer interfaces.Key ResponsibilitiesResearch & Model Development:Craft, train, and enhance state-of-the-art deep learning models for neural decoding, utilizing the latest advancements in machine learning architectures such as transformers and diffusion models.Investigate innovative methodologies for modeling high-frequency time-series EEG datasets alongside various other data modalities.Convert research findings into production-ready code that seamlessly integrates with our proprietary brain-computer interface stack.Collaboration & Publication:Work in tandem with a multidisciplinary team of neuroscientists and ML engineers to develop scalable, end-to-end neural decoding solutions.Publish research outcomes in leading ML and AI conferences such as NeurIPS, ICML, ICLR, and CVPR, and actively engage in open-source communities as appropriate.
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.
Join Our Team at Rad AIAt Rad AI, we are dedicated to transforming the healthcare landscape through the power of artificial intelligence. Established by a radiologist, our innovative AI solutions are revolutionizing the field of radiology, enhancing patient care, alleviating clinician burnout, and significantly reducing the time required for report generation. With access to one of the largest proprietary datasets of radiology reports globally, our AI technologies have facilitated the discovery of numerous new cancer diagnoses and halved error rates across tens of millions of reports.Having raised over $140 million in funding, including a highly successful Series C round of $68 million led by Transformation Capital, we are now valued at $528 million. Our prestigious investors, such as Khosla Ventures, World Innovation Lab, Gradient Ventures, and Cone Health Ventures, are all committed to supporting our mission to empower healthcare professionals with cutting-edge AI tools.Our latest breakthroughs in generative AI are utilized by thousands of radiologists every day, supporting nearly half of all medical imaging across the United States, in partnership with esteemed healthcare organizations like Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked as the 19th fastest-growing company in North America by Deloitte, we are committed to creating AI-powered solutions that make a real difference. Recently, Rad AI was also featured on CNBC’s Disruptor 50 list, showcasing the innovation and momentum behind our mission.If you are eager to impact the future of healthcare positively, we would be thrilled to have you join our talented team!Why You Should Join UsWe are seeking a Staff Machine Learning Research Scientist to define and lead Rad AI's next wave of applied research in Natural Language Processing (NLP) and clinical AI. You will engage with large language models, retrieval systems, representation learning, speech processing, and multimodal modeling, prioritizing evaluation and reliability alongside achieving state-of-the-art outcomes. This role offers you the chance to take ownership of projects and establish a direct pathway from research to product implementation.As part of our team, you will work closely with clinicians, engineers, and product leaders to translate foundational research into practical applications that enhance healthcare delivery.
OverviewPluralis Research is at the forefront of Protocol Learning, innovating a decentralized approach to train and deploy AI models that democratizes access beyond just well-funded corporations. By aggregating computational resources from diverse participants, we incentivize collaboration while safeguarding against centralized control of model weights, paving the way for a truly open and cooperative environment for advanced AI.We are seeking a talented Machine Learning Training Platform Engineer to design, develop, and scale the core infrastructure that powers our decentralized ML training platform. In this role, you will have ownership over essential systems including infrastructure orchestration, distributed computing, and service integration, facilitating ongoing experimentation and large-scale model training.ResponsibilitiesMulti-Cloud Infrastructure: Create resource management systems that provision and orchestrate computing resources across AWS, GCP, and Azure using infrastructure-as-code tools like Pulumi or Terraform. Manage dynamic scaling, state synchronization, and concurrent operations across hundreds of diverse nodes.Distributed Training Systems: Design fault-tolerant infrastructure for distributed machine learning, including GPU clusters, NVIDIA runtime, S3 checkpointing, large dataset management and streaming, health monitoring, and resilient retry strategies.Real-World Networking: Develop systems that simulate and manage real-world network conditions—such as bandwidth shaping, latency injection, and packet loss—while accommodating dynamic node churn and ensuring efficient data flow across workers with varying connectivity, as our training occurs on consumer nodes and non-co-located infrastructure.
Join latentlabs, a pioneering company at the forefront of biotechnology, as we seek a talented Machine Learning Researcher specializing in generative modeling. You will become part of a dynamic, interdisciplinary team comprising machine learning experts, protein engineers, and biologists, all committed to revolutionizing biological control and disease treatment. In this role, you will design innovative generative models aimed at creating new proteins that exhibit functionality in wet lab assays.
Join us at Physical Intelligence as a Research Scientist, where you will be at the forefront of innovation in machine learning and robotics. We are in search of exceptional researchers across all experience levels who demonstrate a strong track record of impactful research results. Ideal candidates will possess a solid foundation in both practical implementation and theoretical frameworks, showcasing a blend of system-building capabilities and significant conceptual, algorithmic, or theoretical advancements. We value diverse backgrounds and encourage applications from both traditional academic researchers and those with unique, unconventional experiences.We are committed to fostering a diverse and inclusive workplace. In accordance with the San Francisco Fair Chance Ordinance, we welcome applications from qualified individuals with arrest and conviction records.
OverviewPluralis Research is at the forefront of innovation in Protocol Learning, specializing in the collaborative training of foundational models. Our approach ensures that no single participant ever has or can obtain a complete version of the model. This initiative aims to create community-driven, collectively owned frontier models that operate on self-sustaining economic principles.We are seeking experienced Senior or Staff Machine Learning Engineers with over 5 years of expertise in distributed systems and large-scale machine learning training. In this role, you will design and implement a groundbreaking substrate for training distributed ML models that function effectively over consumer-grade internet connections.
Full-time|$218.4K/yr - $273K/yr|On-site|San Francisco, CA; Seattle, WA; New York, NY
Join Scale AI's ML platform team (RLXF) as a Machine Learning Research Engineer, where you will play a pivotal role in developing our advanced distributed framework for training and inference of large language models. This platform is vital for enabling machine learning engineers, researchers, data scientists, and operators to conduct rapid and automated training, as well as evaluation of LLMs and data quality.At Scale, we occupy a unique position in the AI landscape, serving as an essential provider of training and evaluation data along with comprehensive solutions for the entire ML lifecycle. You will collaborate closely with Scale's ML teams and researchers to enhance the foundational platform that underpins our ML research and development initiatives. Your contributions will be crucial in optimizing the platform to support the next generation of LLM training, inference, and data curation.If you are passionate about driving the future of AI through groundbreaking innovations, we want to hear from you!
Full-time|Remote|Remote-Friendly (Travel-Required) | San Francisco, CA | New York City, NY
Anthropic is looking for a Research Engineer with a focus on Machine Learning, particularly Reinforcement Learning (RL) Velocity. This position involves collaborating with a team to design, build, and refine machine learning systems. Much of the work centers on experimenting with new ideas and advancing AI research. What you will do Work alongside researchers and engineers to develop and optimize machine learning models Explore new methods in reinforcement learning to accelerate progress Contribute to projects that push the boundaries of AI capabilities Location and travel This role offers flexibility to work remotely, with some required travel. Anthropic maintains offices in San Francisco, CA and New York City, NY.
Achira is seeking a Machine Learning Research Engineer to help improve workflows and systems for artificial intelligence projects. This position is based in the San Francisco office. Role overview This role centers on developing and refining machine learning pipelines. The focus is on efficient deployment and scaling of AI models in production environments. Collaboration with colleagues from different disciplines is a key part of the work, aiming to bring forward new ideas and solid practices in machine learning systems. What you will do Design and optimize machine learning workflows for better performance and scalability Work closely with cross-functional teams to implement improvements in AI systems Support the deployment process, helping ensure models run efficiently in real-world settings Location This position is based at Achira's San Francisco office.
Full-time|$275K/yr - $350K/yr|On-site|San Francisco, CA; Seattle, WA; New York, NY
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.
Full-time|$252K/yr - $315K/yr|On-site|San Francisco, CA; Seattle, WA; New York, NY
At Scale AI, we collaborate with leading AI laboratories to supply high-quality data and foster advancements in Generative AI research. We seek innovative Research Scientists and Research Engineers with a strong focus on post-training techniques for Large Language Models (LLMs), including Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and reward modeling. This position emphasizes optimizing data curation and evaluation processes to boost LLM performance across text and multimodal formats. In this pivotal role, you will pioneer new methods to enhance the alignment and generalization of extensive generative models. You will work closely with fellow researchers and engineers to establish best practices in data-driven AI development. Additionally, you will collaborate with top foundation model labs, providing critical technical and strategic insights for the evolution of next-generation generative AI models.
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.
