Senior Machine Learning Engineer - Ads Research and Development

Join Spotify's innovative Ads Research and Development team as a Senior Machine Learning Engineer, where you will lead the charge in developing advanced algorithms that enhance our advertising capabilities. Your expertise in machine learning and data analysis will be crucial in driving impactful decisions and improving the overall user experience.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by dual objectives that enhance each other.Our primary focus is to understand and construct intelligence. This encompasses establishing the fundamental mathematical principles of reasoning, learning, decision-making, comprehension, and explanation, alongside developing software that embodies these principles.Secondly, we aim to empower society to tackle complex challenges. This involves broadening the scale, complexity, and scope of problems we can currently address and, crucially, accelerating our future problem-solving capabilities.To realize these ambitions, we are establishing an innovative technological framework inspired by human reasoning and fostering a collaborative environment that prioritizes human values.About the RoleAs a Research Engineer, you will play a vital role in advancing Basis’ mission by converting research concepts into accurate, robust, and scalable high-quality code.We are looking for technically proficient individuals who are enthusiastic about delving deep into foundational concepts. Our research engineers are committed to conducting rigorous, high-quality science, unafraid to experiment, learn from mistakes, and explore innovative ideas.Basis thrives on collaboration, both within our team and with external partners. We seek individuals who enjoy tackling challenges greater than they can manage alone.Machine Learning Research Engineer Focus AreasThis position is aimed at experts in machine learning engineering. Key areas of focus include:Probabilistic programming and statistical inferenceDeep learningCausal inferenceProgram synthesis and analysisML Ops and systems engineeringThese areas will be explored in the context of developing reasoning systems. Research engineers will also engage with topics including programming language design and implementation, automatic differentiation, and SAT/SMT solvers.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research. Our mission is twofold: to deepen our understanding of intelligence and to empower society in solving complex, challenging problems.Our first objective is to comprehend and construct intelligence. This involves establishing foundational mathematical principles for reasoning, learning, decision-making, comprehension, and explanation, while also developing software that embodies these principles.Secondly, we aim to enhance society’s capability to tackle intractable issues. This includes broadening the scope and complexity of problems we can address today and accelerating our future problem-solving abilities.To accomplish these objectives, we are creating a technological infrastructure inspired by human reasoning and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis’ initiatives to unravel the conceptual, mathematical, and computational foundations of intelligence. We seek individuals with exceptional technical skills who are eager to explore foundational concepts. Our research scientists and engineers are committed to conducting rigorous, high-quality scientific investigations, while also embracing the opportunity to experiment, learn from errors, and explore innovative ideas.Collaboration is integral to our work, both internally and with external partners. We are searching for individuals who thrive in team settings, tackling challenges that transcend individual capabilities.Key Expectations:Proven ability to conduct high-quality scientific research, demonstrated through publications, technical reports, or software projects.Preferred Qualifications:PhD or equivalent experience in relevant fields such as statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, or mathematics.Enthusiasm for addressing real-world challenges and contributing to positive societal change.ResponsibilitiesDevelop and investigate computational theories of intelligence, encompassing reasoning, learning, and decision-making.Collaborate closely with domain experts, both within Basis and externally, to contribute to solving scientific problems.

Hello! I’m Aidan, the founder of Maple.At Maple, we are on a mission to revolutionize local businesses by creating intelligent AI agents. Our agents efficiently manage tasks such as answering calls, taking orders, and booking appointments, providing seamless interactions through natural voice communication.Our deeper mission: We are developing automated ontologies that accurately reflect the operational realities of businesses — capturing their services, workflows, constraints, and unique language — allowing our agents to adapt instantly to diverse business needs. We strive to meet businesses where they are, rather than imposing a rigid software framework.With a growing customer base, strong revenue growth, a secure financial runway, and support from esteemed investors, we are positioned for exciting advancements. More details will be shared during our conversation.Role OverviewAs a Machine Learning Research Engineer at Maple, you will be integral to our core product team, transforming innovative research into production-ready voice agents that facilitate millions of customer interactions for small businesses. You will collaborate with experts from prestigious institutions such as Google Brain, Two Sigma, Stanford, MIT, Columbia, and IBM to swiftly deploy sophisticated models and systems that have a direct impact on small enterprises.Our team operates in person, five days a week in our vibrant NYC office. Our collaborative environment is characterized by rapid-paced, dynamic interactions filled with trust and transparency. We embrace a culture of speed and adaptability, tackling challenges head-on.Key ResponsibilitiesEnhance automatic speech recognition (ASR), large language models (LLMs), and text-to-speech (TTS) systems for practical applications, ensuring high accuracy in diverse and noisy environments.Fine-tune LLMs utilizing retrieval-augmented generation (RAG), reinforcement learning (RL), and prompt engineering for engaging, contextually aware dialogues.Integrate AI components into autonomous agents capable of executing complex tasks such as scheduling, order management, and problem resolution.Design human-in-the-loop and automated systems for monitoring performance, identifying anomalies, and iteratively improving models based on real-world feedback.Develop pipelines for building knowledge graphs from business data, enhancing dynamic AI interactions.Collaborate with infrastructure teams to scale models effectively, ensuring robust performance and reliability.

OverviewAt OXMAN, a pioneering nature-focused research and design firm based in Manhattan, we leverage nature-centric solutions to tackle pressing challenges at the intersection of Nature and Humanity. Our interdisciplinary approach spans various sectors, fostering innovative concepts that redefine the interaction between the built environment and the natural ecosystem.Our initiative, EDEN, is dedicated to applied ecological systems operating on architectural, urban, and landscape scales. We are at the forefront of creating a digital design framework that engineers biodiverse and resilient ecosystems by developing software that empowers designers and engineers to incorporate essential ecosystem services—such as carbon sequestration, thermal buffering, and biodiversity—into their master planning and design processes. Our mission is to elevate ecosystem services from undervalued byproducts to vital infrastructure elements. We invite talented professionals to join us in revolutionizing the future of nature-centric design.We are currently seeking a Machine Learning Research Engineer to integrate into our dynamic design team in New York City. This role will be pivotal in supporting our efforts to deliver exceptional, data-driven design proposals utilizing EDEN’s innovative suite of ecosystem engineering tools.

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by two key objectives.The first objective is to comprehend and develop intelligence. This encompasses establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation, while also creating software that embodies these principles.The second objective is to enhance society’s capacity to tackle complex challenges. This involves broadening the scope, scale, and complexity of problems we can address today, and crucially, accelerating our capacity to solve future problems.To fulfill these missions, we are constructing an innovative technological infrastructure inspired by human reasoning, along with a collaborative organization that prioritizes human values.About the RoleAs an ML Systems Engineer at Basis, you will ensure that our training and evaluation infrastructure is fast, reliable, and scalable. You will manage the entire stack, from distributed training frameworks to cloud administration, enabling researchers to rapidly iterate on complex models while efficiently managing computational resources.We are seeking engineers who possess a profound understanding of ML systems paired with operational excellence. The ideal candidate will have experience in distributed training at scale, expertise in debugging numerical instabilities, and the ability to manage cloud infrastructure that seamlessly transitions from experimentation to production. You will be the steward of training stability, an optimizer of computational costs, and a facilitator of reproducible research.This position encompasses both traditional ML engineering and cloud/DevOps responsibilities. You will oversee GPU clusters, optimize cloud expenditures, ensure security and compliance, and build the infrastructure that allows researchers to focus on algorithms rather than operations.We are looking for individuals who are committed to developing robust ML infrastructure, maintaining a culture of documentation for issues and solutions, and prioritizing operational excellence as a core value.

Join Our TeamAt Unity, we are pioneering a cutting-edge ad-tech ecosystem that connects billions of users with the games and experiences they cherish. The Advertiser Growth team is integral to this vision, managing the online ads delivery stack, including auction, pacing, and bidding systems. As a Senior Machine Learning Engineer, you will play a crucial role in modernizing our core infrastructure and developing the backend systems for next-generation AI agents that transform the campaign experience. This position provides the opportunity to tackle intricate system challenges at a massive scale while directly impacting Unity's revenue growth.

Join headway as a Senior Machine Learning Engineer and make a significant impact in the field of machine learning and artificial intelligence. In this role, you will leverage your expertise to develop innovative solutions, improve existing algorithms, and collaborate with cross-functional teams to drive forward our mission of transforming the healthcare experience.

Who is Nexxen?Nexxen is revolutionizing the advertising landscape with a data-driven approach that empowers advertisers, agencies, publishers, and broadcasters globally. Our innovative technology framework unifies a demand-side platform (DSP) and supply-side platform (SSP), anchored by the Nexxen Data Platform, to deliver meaningful advertising solutions.Why become a part of the Nexxen team?Join us in our mission to transform advertising through our flexible and creative solutions. At Nexxen, we value a culture that emphasizes the 3Cs - Customer Centricity, a Curious Mindset, and Collaboration without Ego. Become part of a dynamic team that thrives on commitment and ingenuity.Your Safety is Our PriorityAt Nexxen, we prioritize the safety and well-being of our employees. We are vigilant against online scams and fraudulent job postings. Please note that we will never ask for payment as a condition of employment or promote dubious financial schemes. If you encounter any suspicious communications, contact us at infosec@nexxen.com. Your trust is paramount; stay safe and informed.Position OverviewAs a Senior Machine Learning Engineer, you will join our Applied Data Science group within the Nexxen DSP Software Development team. This hands-on role involves collaborating closely with data scientists to develop cutting-edge data science infrastructure aimed at real-time performance optimization and machine learning applications. The ideal candidate will possess extensive experience in implementing machine learning technologies or data-driven algorithms, and should display a proactive and innovative mindset.We operate in a hybrid model, with team members working three days a week at our New York office and remotely for the remainder of the week.Key Responsibilities:Design and develop high-performance, large-scale services for Nexxen DSP programmatic integrations and platform products.Drive innovative solutions and implement machine learning algorithms for enhanced performance.

Join SoundCloud, a leading platform that enables artists and fans to connect and share their passion for music. Established in 2007, our artist-first approach empowers creators to develop their careers with innovative tools, services, and resources. With a catalog featuring over 400 million tracks from 40 million artists, the future of music is unfolding at SoundCloud. We are seeking a Senior Machine Learning Engineer to become an integral member of our Reco-Core team. This role presents an exciting opportunity to influence and steer the machine learning initiatives for one of SoundCloud's most essential product areas. You will collaborate closely with machine learning, data, and backend engineers to design, implement, and deploy models that facilitate music discovery for millions of users across our extensive audio catalog.Key Responsibilities:Create and deploy comprehensive machine learning solutions for recommendation systems, focusing on candidate generation, personalization, user and item modeling, and ranking algorithms.Oversee the entire machine learning lifecycle, from prototyping and evaluation to deploying scalable models and monitoring performance in production.Enhance and expand the foundation for ML engineering and MLOps within the Reco-Core team, establishing best practices and developing tools for rapid iteration.Collaborate with analysts and data scientists to convert research findings into production-ready systems.Work alongside fellow ML engineers to utilize shared infrastructure and collective expertise.

About the Role current81 is looking for a Senior Software Engineer focused on Applied Machine Learning to join the team in New York, NY. This position centers on building machine learning solutions that support business goals and improve how users interact with our products. What You Will Do Design and implement machine learning models for real-world applications Work with teams across engineering, product, and data to deliver practical ML features Apply advanced algorithms and data analysis to solve business challenges

Become part of an innovative team that is pioneering the development of the world's first biological reasoning model. Collaborate with us to create generative foundational models that unravel biological systems on various scales—from molecules to entire organisms—empowering us to predict, comprehend, and manipulate living systems in unprecedented ways.Output Biosciences is currently operating in stealth mode, led by a team of experienced founders and biotech experts with a proven track record in AI and biology, supported by top-tier venture capital firms including Y Combinator.As a Machine Learning Research Scientist specializing in Interpretability, you will collaborate closely with our founders and dedicated team to create AI systems that can process and reason across diverse biological data modalities simultaneously.Develop specialized techniques to enhance the understanding of our biological reasoning models, reverse-engineering their representation and processing of complex biological information.Design and perform experiments aimed at discovering interpretable features across various biological scales.Tackle unique challenges in biological model interpretation, including disentangling multi-scale, hierarchical representations of biological systems.Create biology-specific visualization tools that effectively map model activations to meaningful biological concepts.

Machine Learning Developer Experience EngineerAbout Our TeamAt Adaptive ML, we are at the forefront of AI innovation, developing a cutting-edge Reinforcement Learning Operations (RLOps) platform that empowers enterprises to specialize and deploy Large Language Models (LLMs) with tangible outcomes. Our platform provides the foundational infrastructure needed to tune, evaluate, and serve specialized models at scale, enabling the pioneering of task-specific LLM development and the execution of production-ready workflows that manage millions of requests while optimizing for both cost and performance across distributed systems.Our dynamic team has previously contributed to the development of state-of-the-art open-access large language models. We successfully raised $20M in seed funding led by Index Ventures and ICONIQ in early 2024, and we are already operational with clients such as Manulife, AT&T, and Deloitte, spanning the travel and financial services sectors, with many more partnerships on the horizon.About This RoleWe are searching for a talented ML Developer Experience Engineer who will empower ML engineers and development teams to utilize reinforcement learning effectively, without needing extensive RL expertise. You will be responsible for creating developer-focused tools, abstractions, and workflows that simplify the training, evaluation, and deployment of RL models, making them intuitive, robust, and scalable. Your contributions will enhance our customers' ability to adopt, grow, and manage RL use cases independently.This position plays a crucial role in our growth strategy: your work will facilitate independent scaling for our customers, minimizing friction and enabling self-service adoption throughout their organizations. You will closely collaborate with Technical Success, Product, and Engineering teams to identify common patterns, extract reusable solutions, and delineate the boundaries between tooling and product.This position is based in Paris, New York, or Toronto.Your ResponsibilitiesDesign and build user-friendly SDKs, libraries, APIs, and tools that enhance RL workflows for developers and ML engineers.Achieve a balance between simplicity and flexibility—supporting common patterns while allowing for advanced configurations and extensibility.Collaborate with internal teams to refine core components into documented, reusable modules that drive customer success.Engage with technical and customer success teams to identify recurring customer patterns and workflow impediments.Translate user feedback into tooling enhancements, error messaging improvements, onboarding processes, and example references.Maintain comprehensive documentation to support user engagement.

About the RoleAt Zencastr, we are dedicated to creating innovative end-to-end AI systems and core microservices that revolutionize the podcasting landscape. By harnessing the latest technologies, we aim to enhance the user experience for millions of podcast creators and listeners every day.We invite an exceptional Senior Machine Learning Engineer to become a vital member of our dynamic team. In this role, you will engage in large-scale machine learning projects aimed at enriching the podcast creation journey for Zencastr users.You will collaborate with a group of dedicated engineers who are enthusiastic about understanding the factors that influence long-term user satisfaction with Zencastr. Your contributions will help shape our recommendations and content strategies. As a key player in the team, you will work alongside research scientists and data professionals to prototype and implement cutting-edge machine learning solutions that intertwine speech processing with user satisfaction.Key ResponsibilitiesDesign, research, and develop pioneering machine learning applications and algorithms to enhance the experiences of podcasters and their audiences globally.Collaborate with cross-functional teams to create new product features that enhance Zencastr's machine learning services.Advance audio and text capabilities within the machine learning team.Engage with leading experts in signal processing.Ideal Candidate ProfileA Master's degree or higher in Machine Learning, Mathematics, Computer Science, or a related quantitative discipline.A minimum of 5 years of experience in Python programming.At least 3 years of experience in machine learning research, particularly with a focus on speech processing.3+ years of experience in training and deploying neural networks.Extensive experience with machine learning frameworks such as PyTorch, TensorFlow, and Scikit-Learn.Proficiency in building and maintaining production-ready machine learning systems.Ability to lead the design and implementation of significant software components and features.A passion for rapidly building model prototypes.Familiarity with cloud platforms such as Google Cloud, AWS, or Modal.A proactive mindset with the ability to spearhead projects and foster positive collaborations with partners and colleagues.

Join Jane Street as a Senior Weather Analyst and Machine Learning Researcher, where your expertise will contribute to advanced weather prediction models and data analysis. You will collaborate with a talented team to leverage machine learning techniques in analyzing complex meteorological datasets, improving our forecasting capabilities.

Join our innovative Match Team as a Senior Machine Learning Engineer at Enigmaio, where you will play a pivotal role in developing advanced algorithms and models that enhance our matching capabilities. You will collaborate with cross-functional teams to design, implement, and optimize machine learning solutions that drive business outcomes.

Join the dynamic Internal Alpha Capture (IAC) team at Point72, where we harness artificial intelligence to create cutting-edge equity trading signals. Our team thrives on collaboration, utilizing rigorous research methodologies, advanced machine learning techniques, proprietary data, and exceptional computational power. We are seeking outstanding machine learning researchers to contribute to our innovative projects, working closely with seasoned professionals to apply their expertise to unique datasets and develop impactful trading signals. No prior financial industry experience is necessary.

Become a pivotal part of our innovative team at Output Biosciences, where you will contribute to the groundbreaking development of the world's inaugural biological reasoning model. Collaborate with us in creating generative foundational models that decode biological systems at all scales—from molecules to entire organisms—allowing us to predict, understand, and manipulate living systems in unprecedented ways.Currently operating under stealth mode, Output Biosciences is spearheaded by a team of accomplished founders and seasoned biotech veterans with a proven track record of successful exits in both AI and biology. We are proudly backed by leading venture capital firms including Y Combinator.As a Machine Learning Research Scientist specializing in Generative AI, you will work closely with our founders and collaborative team members to forge advanced generative models capable of synthesizing and designing biological systems across various scales. Building on our biological reasoning model, your focus will be on creating generative capabilities that translate insights into innovative applications.Design and develop state-of-the-art generative models tailored for biological data, enabling AI systems to generate novel molecular structures, protein designs, cellular components, and biological pathways.Implement cutting-edge generative algorithms including diffusion models, language diffusion models, diffusion transformers, and flow matching approaches, customized for biological constraints and properties.Train and scale pioneering AI models utilizing large, diverse multimodal biological datasets across distributed GPU clusters.Solve complex AI research challenges at scale, addressing crucial aspects like model architecture, scaling, pre-training and fine-tuning strategies, and rigorous evaluation methods.Explore and implement various advanced generative AI architectures, such as transformers, diffusion models, and autoencoders, to push the boundaries of biological AI innovation.

Join Virtu Financial, a leading quantitative trading firm, where innovation meets impact in the financial markets. As a Machine Learning Researcher, you will engage in groundbreaking research opportunities within a dynamic and agile organization. This role presents a unique blend of intellectual challenge and immediate business influence, as you navigate complex problems that lack straightforward solutions.Your responsibilities will encompass our entire modeling ecosystem, from feature engineering and deep learning architecture to training dynamics and execution strategies. Your pioneering contributions will shape our market operations globally, making a real difference in a fast-evolving industry that thrives on creative problem-solving and first-principles thinking.We seek individuals with a strong sense of curiosity, a robust technical skill set, and a collaborative spirit, regardless of their industry background.

Trunk Tools seeks a Senior Machine Learning Engineer to join its team onsite in New York City. This role centers on creating and deploying models that drive the company’s main objectives. Working alongside colleagues from various backgrounds is a key part of the job. Responsibilities Design and build machine learning models for practical use cases Collaborate with cross-functional teams to gather requirements and deliver effective solutions Deploy models into production environments and monitor their scalability Work Location This position is based at the Trunk Tools headquarters in New York City. Regular onsite presence is required.