Machine Learning Performance Engineer

Join our innovative Machine Learning team at Jane Street as a Performance Engineer, where your expertise in low-level systems programming and optimization will play a critical role in enhancing our machine learning capabilities. Machine learning is a vital component of Jane Street's global operations. Our dynamic trading environment acts as a unique, rapid-feedback platform for ML experimentation, allowing us to seamlessly integrate new concepts and methodologies. Your primary responsibility will be to optimize the performance of our models during both the training and inference phases. We prioritize efficient large-scale training, low-latency inference in real-time systems, and high-throughput inference in research scenarios. This involves not only refining CUDA implementations but also taking a holistic approach that encompasses storage systems, networking, as well as host and GPU-level considerations. We aim to ensure that our platform operates efficiently at the lowest levels—questioning whether high throughput translates into effective goodput and analyzing the actual time taken to load vectors from the L2 cache. If you're curious and passionate about tackling complex problems, you’ll find a welcoming environment here, even if you haven't previously considered a career in finance.

Jane Street is seeking a talented engineer with a strong background in low-level systems programming and optimization to join our dynamic Machine Learning team.As a key component of Jane Street's global operations, machine learning plays a pivotal role in our continually evolving trading environment. This unique setting offers rapid feedback for ML experimentation, enabling us to seamlessly integrate fresh ideas into our processes.Your primary responsibility will be to enhance the performance of our machine learning models during both training and inference phases. We prioritize efficient large-scale training, low-latency inference in real-time systems, and high-throughput inference for research purposes. This involves improving standard CUDA implementations, while also adopting a holistic approach that considers storage systems, networking, and both host and GPU-level factors. Furthermore, we aim to ensure our platform's efficiency down to the granular level—how effective is our throughput? How long does it realistically take to load a vector from the L2 cache?If finance is not your primary background, rest assured—you are not alone. Many of our team members come from diverse fields. If you possess a curious mindset and a passion for tackling challenging problems, you will likely find a home here.

Why Choose Charlie Health?Across the nation, countless individuals are facing mental health challenges, substance use disorders, and eating disorders. Unfortunately, many encounter obstacles to obtaining the care they need, such as limited local options and lengthy wait times. Behavioral healthcare often fails to provide the personalized support that individuals require, leaving them feeling overlooked and unsupported.At Charlie Health, our mission is to transform this landscape. We strive to connect individuals to crucial behavioral health treatment through personalized, virtual care that fosters connections between clients and clinicians, care teams, loved ones, and their supporting communities. By prioritizing those with complex needs, we are enhancing access to significant care and achieving improved outcomes—all from the comfort of home.As a rapidly expanding organization, we are reaching more communities daily, and we are assembling a team dedicated to redefining behavioral health treatment. If you are eager to leverage your skills to create meaningful change and help individuals access the care they deserve, we invite you to join us.About the RoleCharlie Health is a leader in high-acuity virtual behavioral care, having provided life-saving treatment to over 100,000 clients across the nation. Our Matching and Outcomes team is responsible for developing products that assess and enhance clinical outcomes, including systems for provider recommendations and clinical decision support tools, ensuring effective treatment. You will design predictive models and workflows to connect patients with the most suitable therapists and peers, enabling clinicians to customize care to meet each client's unique needs. The systems you develop will empower clinicians to condense and synthesize insights from our clients and providers into actionable guidance at every step. If you are passionate about utilizing data-driven insights to enhance outcomes, this team is for you.

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.

At Garner Health, we are dedicated to revolutionizing the healthcare economy by making high-quality and affordable care accessible to all.We are fundamentally reimagining the healthcare landscape in the U.S. by collaborating with employers to redesign healthcare benefits using transparent incentives and powerful, data-driven insights. Our innovative approach directs employees toward higher-quality, lower-cost care, fostering a healthcare system that benefits everyone. This means improved health outcomes for patients, more effective spending of healthcare dollars for employers, and rewarding physicians for providing exceptional care rather than performing unnecessary procedures.Garner is recognized as one of the fastest-growing healthcare technology companies nationally. Our products are trusted by the most sophisticated employers and providers in the industry, and we are building a team of talented, mission-driven individuals who are eager to make a significant impact on healthcare at scale.About the Role:We are on the lookout for an outstanding Staff Machine Learning Engineer to join our dynamic team. At Garner, our Engineering team addresses complex technical challenges that have a meaningful impact on our mission. Our systems analyze billions of medical records to evaluate healthcare providers nationwide. We operate on AWS with Kubernetes and consistently integrate new technologies as our system load grows exponentially each year. We encourage our engineers to advocate for cutting-edge industry practices as we wholeheartedly incorporate AI into every aspect of our operations and standards. We value teammates who take pride in delivering exceptional work and nurturing a robust team culture.Where You Will Work:This position is based in our New York City office located in the Financial District. Candidates must be available to work in the office three days a week: Tuesday, Wednesday, and Thursday.What You Will Do:Lead technical strategy and execution at the team level over multi-quarter time frames.Utilize AI to build, optimize, and maintain machine learning, data, and software systems.Elevate the technical capabilities of engineers throughout the organization.Collaborate across disciplines to deepen domain understanding and iterate on projects.Ensure user privacy and security through adherence to best practices.

Join Spotify as a Machine Learning Engineer and be at the forefront of innovation in music streaming. In this role, you will leverage cutting-edge machine learning algorithms and data-driven insights to enhance user experiences and drive business decisions. Collaborate with cross-functional teams to develop scalable solutions that improve our recommendation systems and user engagement.

Join our innovative team at Sunset Technologies as a Machine Learning Engineer. We are dedicated to pushing the boundaries of artificial intelligence and machine learning to deliver advanced solutions that enhance our products and services. You will be involved in designing, implementing, and optimizing machine learning models to analyze large datasets, develop predictive algorithms, and contribute to the overall growth of our technology stack.

Role Overview root-access is hiring a Machine Learning Engineer in New York City. This role works closely with the tech team to design and build machine learning algorithms that support and improve our products. The position involves hands-on development, data analysis, and delivering solutions that scale as our business grows. What You Will Do Develop machine learning models tailored to product needs Analyze complex data sets to extract insights and guide model improvements Create solutions that can scale to meet increasing demand Collaborate with engineers and product teams to integrate AI-driven features Who We’re Looking For Experience building and deploying machine learning algorithms Strong interest in artificial intelligence and its practical applications Ability to work with large, complex data sets Comfort working in a collaborative, evolving tech environment

Join Spotify's innovative team as a Machine Learning Engineer, where you'll be at the forefront of developing cutting-edge algorithms that enhance user experiences. In this role, you will leverage your expertise in machine learning to create scalable solutions and drive impactful projects that shape the future of music streaming.

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 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.

Role Overview Spotify is hiring a Machine Learning Engineer focused on Personalization in New York, NY. This role centers on developing and applying machine learning algorithms to improve how users discover and enjoy music and podcasts. The work directly shapes the personalized experiences that keep listeners engaged and coming back. What You Will Do Design and implement machine learning models that tailor content recommendations to individual users Analyze user behavior and preferences to inform algorithm improvements Collaborate with product and engineering teams to integrate personalization features into the Spotify platform

About TennrAt Tennr, we are transforming the way healthcare referrals are managed. When patients are referred to specialists, they often face frustrating delays. Our innovative platform, powered by RaeLM™, ensures that every referral is processed swiftly and accurately, allowing healthcare providers to capture more referrals and reduce denials. Join us in revolutionizing the healthcare experience.About the RoleAs the pioneering ML Ops Engineer at Tennr, you will be instrumental in developing and refining our Machine Learning and AI infrastructure. You will be responsible for creating and optimizing machine learning training and inference pipelines that can manage escalating traffic demands and an expanding range of products. Your expertise will ensure that our AI-driven healthcare platform operates on robust, scalable, and efficiently deployed models.Our Machine Learning team is at the forefront of innovation, developing proprietary VLMs, LLMs, and other specialized models tailored to address critical healthcare challenges. This is not just a position of maintaining existing systems; it is an opportunity to lead groundbreaking experimentation and the introduction of new capabilities. Your contributions will significantly impact our ML and data systems, enhancing Tennr's ability to solve vital issues for patients and healthcare providers.Key ResponsibilitiesDesign, architect, and implement scalable ML software systems for model deployment and management.Maintain infrastructure that supports efficient ML operations, including data pipelines, model evaluations, and large-scale training.Work collaboratively with ML engineers, software developers, and cross-functional teams to integrate models seamlessly with data pipelines and products.Identify and resolve production issues while continuously enhancing system performance and efficiency.Develop tools for online and offline evaluation of ML and LLM systems.

About Us:At Fireworks AI, we are pioneering the future of generative AI infrastructure. Our platform is recognized for delivering the highest-quality models with the fastest and most scalable inference capabilities in the industry. Proudly benchmarked as a leader in LLM inference speed, we are at the forefront of innovation with projects like function calling and multimodal models. As a Series C company valued at $4 billion, we are supported by prestigious investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. Our team comprises ambitious builders, many of whom hail from Meta PyTorch and Google Vertex AI.The Role:As an Applied Machine Learning Engineer, you will play a crucial role in bridging the gap between advanced AI research and practical applications. Your responsibilities will include developing, fine-tuning, and operationalizing machine learning models that deliver significant business value and enhance user experiences. This hands-on engineering position demands a blend of deep technical expertise and a strong customer-centric approach to create scalable AI solutions.Key Responsibilities:Customer Success: Collaborate with the Go-To-Market (GTM) team, including Account Executives and Solutions Architects, to ensure seamless integration and successful deployment of machine learning solutions.Demo / Proof of Concept (PoC): Develop and present engaging PoCs that showcase the capabilities of our AI technology.Application Build: Design, develop, and deploy end-to-end AI-powered applications customized to meet customer needs.Platform Features / Bug Fixes: Contribute to the internal machine learning platform by adding features and resolving issues.New Model Enablements: Integrate and enable new machine learning models within the existing platform or client environments.Performance Optimizations: Enhance the performance, efficiency, and scalability of deployed models and applications.Partnership Enablement: Collaborate closely with partners to facilitate joint AI solutions and ensure effective collaboration.

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.

Join Our Team as a Machine Learning Engineer! At FanDuel, we recognize that data is the lifeblood of our organization. As a Machine Learning Engineer, you will harness the power of our extensive real-time and relational datasets to drive insights that enhance user experiences. Your analytical skills will transform every interaction—from user clicks to game outcomes—into actionable intelligence, enabling us to make faster, more informed decisions that keep us ahead of the competition. Your role will be pivotal in fostering collaboration across teams. You will serve as the bridge between engineering teams, facilitating the development of our online applications while ensuring that essential data is available for feature engineering. Collaborating with Data Scientists and Analysts, you will help bring AI-driven insights into production and validate their effectiveness. Your efforts will be instrumental in organizing, modeling, and presenting data in a manner that provides a unified information structure, empowering FanDuel to respond intelligently to market dynamics and on-field events. If you are a Machine Learning Engineer with aspirations to thrive in a big data environment, we encourage you to apply! Your Responsibilities: Design and implement intelligent search systems incorporating typeahead search, vector search, and ML personalization to optimize user experience. Contribute to the creation of scalable serving systems for ML and GenAI/LLM models. Develop platform features and tools (e.g., CLI, SDK, Infrastructure Automation) that enhance the ML model lifecycle and GenAI/LLM application deployment. Utilize business intelligence tools such as Tableau, Knime, and Looker. Ensure data security and privacy compliance (e.g., GDPR, CPP). Implement data governance and testing frameworks. Support continuous integration and delivery of data products. Participate in an inclusive culture that prioritizes excellence, personal growth, and well-being.

Join Schrödinger as a Machine Learning Platform Engineer, where you will play a crucial role in developing innovative machine learning solutions that drive advancements in scientific research and technology. You will collaborate with a talented team of scientists and engineers, leveraging cutting-edge tools and methodologies to enhance our computational platforms.Your expertise in machine learning algorithms and software engineering will be vital in creating scalable and efficient systems that facilitate data-driven decision-making. If you are passionate about harnessing the power of AI in scientific endeavors, we invite you to apply!

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.