Machine Learning Platform Engineer

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!

Join the cutting-edge team at sola as a Software Engineer focused on our Machine Learning Platform. In this role, you will contribute to the development and optimization of innovative machine learning solutions that drive our business forward. Collaborate with a talented group of engineers and data scientists to deliver high-quality software that supports advanced machine learning models and applications.

Join Hinge – The Dating App Designed to Be DeletedIn an era where forging genuine connections is increasingly challenging, Hinge is committed to fostering meaningful relationships and reducing loneliness. Our obsession lies in understanding user behavior to facilitate love, with our success measured by a straightforward yet vital metric – helping users set up great dates. With millions of users worldwide, we've established ourselves as the most reliable platform for finding relationships.About the OpportunityAs a key member of Hinge’s AI Platform Core team, you will play a pivotal role in shaping and enhancing our evolving Machine Learning platform. This position focuses on accelerating the development, deployment, and operation of AI-driven features within Hinge. If you are passionate about tackling challenges such as optimizing our training and serving frameworks for real-time predictions, implementing automatic model performance monitoring systems, and architecting generative AI solutions, we invite you to explore this opportunity!Our mission is to democratize AI at Hinge, ensuring it remains accessible, robust, scalable, cost-effective, and trustworthy. You will collaborate closely with product and platform teams and engage with external stakeholders, including data scientists and backend engineers. By understanding the needs of our internal customers, you will deliver incremental value aligned with their challenges. In a small, impactful team, you’ll have a broad scope of responsibilities and the chance to significantly influence the future of Machine Learning at Hinge.

Join The New York Times as a Software Engineer specializing in Machine Learning Platforms to enhance the digital experience for our 150 million readers worldwide. In this hybrid role based in New York City, you'll collaborate with data scientists and engineers to develop and maintain the infrastructure hosting real-time machine learning inference models. Your expertise in MLOps will drive innovative solutions for content recommendations and personalization, contributing to our mission of delivering truth through independent journalism.

Join Anthelion CapitalAnthelion Capital is an innovative investment firm dedicated to creating a cutting-edge AI and data platform that streamlines the entire investment lifecycle, from underwriting to portfolio management. Our platform harnesses both structured and unstructured data, advanced analytics, and automated workflows to achieve exceptional, risk-adjusted returns in private credit and structured finance.As a team of engineers and investors, we are committed to transforming how institutional investment decisions are made—ensuring they are executed faster, smarter, and with greater transparency.Your RoleWe are seeking a talented Machine Learning Infrastructure/Platform Engineer to develop the foundational systems that support our data science and AI platform.You will engage with the underlying infrastructure that drives our ML and AI workflows, including data pipelines, orchestration, compute provisioning, model serving, and observability. Additionally, you will be instrumental in operationalizing our agentic AI platform, ensuring agents are efficiently hosted, monitored, and integrated into production-level systems.Key ResponsibilitiesData Pipelines & OrchestrationDesign, implement, and manage robust production data pipelines that process and deliver structured and unstructured data to downstream ML workflows.Take ownership of our Prefect-based orchestration framework, focusing on flow scheduling, error management, retry mechanisms, and human-in-the-loop (HITL) workflows.Build and oversee feature stores, data contracts, and promotion workflows to guarantee data quality and traceability from raw ingestion to model consumption.Collaborate with data scientists to convert experimental workflows into reliable and repeatable pipelines.ML/AI Infrastructure & DeploymentEstablish and maintain scalable infrastructure for model training, retraining, and inference (both batch and real-time), including GPU compute provisioning and container orchestration.Implement and oversee model serving infrastructure, such as containerized endpoints, API gateways, and self-service deployment frameworks for the data science team.Deploy and manage monitoring systems to track model performance, data drift, prediction usage, and pipeline reliability.Ensure all deployed systems are highly available, resilient, and well-documented, with clear data lineage and operational runbooks.Agentic AI Platform & ToolingAssist in the development and operationalization of agentic AI workflows, including agent hosting, lifecycle management, and integration with Model Content.

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.

Dandy is building technology to modernize dental practices, with a focus on delivering tools and support that help clinicians and their teams. Backed by leading venture capital firms, the company aims to create the operating system for dental offices worldwide. In this Senior Software Engineer I, Machine Learning Platform role, the focus is on bridging advanced computer vision research with reliable, production-ready systems. The position centers on designing and scaling infrastructure for large 3D datasets, orchestrating training pipelines, and supporting robust generative model deployments. Role overview Work closely with Machine Learning Engineers to build training pipelines that manage large 3D datasets, support model training, and enable ongoing model improvements. Refine internal ML components to streamline the lifecycle from data labeling and experimentation through deployment, reducing technical debt along the way. Develop and maintain cloud-native systems and tools, particularly using GCP and Kubernetes, to support the company’s 3D dental products with a focus on security, efficiency, and performance. Write clean, maintainable code and tests that align with internal best practices. Collaborate with stakeholders across Engineering to set long-term architectural goals and uphold high standards for quality. Requirements At least 5 years of experience as a Machine Learning Engineer or Software Engineer, ideally in a startup setting. Deep experience building and maintaining ML Platform components such as feature stores, model registries, or distributed training systems. Strong skills in Python-based ML frameworks like PyTorch or TensorFlow; familiarity with 3D geometric computer vision is a plus. Proven ability in large-scale data processing and developing ML data pipelines for complex model training. Strong problem-solving abilities and an interest in building solutions that improve system performance.

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 The New York Times as a Senior Software Engineer specializing in Machine Learning Platform development. In this pivotal role, you will be an integral part of our Machine Learning & AI team, tackling innovative challenges associated with Machine Learning infrastructure that enhances the experience of our 150 million global digital readers. You will contribute to building and maintaining the robust infrastructure that supports real-time ML inference models, collaborating closely with Data Scientists and engineering teams to ensure high-performance, low-latency service levels. This hybrid position is based in New York City and reports directly to the Engineering Manager of the Machine Learning Platform team.

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.