Senior Machine Learning Engineer

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 Team as a Machine Learning Infrastructure EngineerAt Fauna Robotics, we are on the forefront of revolutionizing robotics through cutting-edge machine learning technologies. As a Machine Learning Infrastructure Engineer, you will play a pivotal role in constructing and enhancing the machine learning systems that drive our innovative robotic solutions. Your expertise will be essential in designing, managing, and optimizing the infrastructure required for training, evaluating, and deploying ML models that facilitate robot locomotion, perception, manipulation, navigation, and interaction with humans.This position is an exciting opportunity to work at the convergence of machine learning and systems engineering, ensuring that our ML training and deployment systems are resilient, efficient, and scalable as we transition from prototypes to fully functional production systems.

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.

Unity Technologies is looking for a Staff Machine Learning Engineer to focus on Offline Infrastructure in New York, NY. Key Responsibilities Design, build, and refine machine learning models that power the Unity platform, working closely with teams across the company. Apply machine learning expertise to enhance infrastructure, with an emphasis on efficiency and reliability. Develop and optimize systems that function offline, ensuring robust performance without constant connectivity. Collaboration This role involves frequent collaboration with cross-functional teams. Sharing knowledge and aligning on technical solutions will help advance Unity’s capabilities.

We are seeking a talented Cloud Infrastructure Engineer to join our dynamic team at Mindlance. In this role, you will be responsible for designing, implementing, and maintaining scalable cloud infrastructures to support our robust applications and services. You'll work closely with cross-functional teams to ensure optimal performance and security of cloud resources.

At Hugging Face, we are dedicated to making AI accessible to everyone. We have developed the fastest-growing platform for AI creators, boasting over 11 million users who have collectively contributed more than 2 million models, 700,000 datasets, and 600,000 applications. Our open-source libraries have gained over 600,000 stars on GitHub.About the RoleAs a Cloud Machine Learning Evangelist, you will play a pivotal role in enhancing the influence of the Hugging Face ML Cloud team. Your mission is to educate machine learning practitioners on how they can optimize their training and inference workloads.The Hugging Face ML Cloud team collaborates strategically with leading cloud providers (AWS, GCP, Azure, Cloudflare), AI accelerators (including NVIDIA, AMD, Intel, Gaudi, Inferentia, TPU), and system integrators (Dell, Nutanix) to facilitate the use of Hugging Face models and libraries across these platforms.These partnerships are essential to our strategy as an open platform (ensuring no customer lock-in) and our monetization approach to enhance usage and revenue for our partners through commercial collaborations and product extensions.This role is distinct from marketing or business development; your focus will be on increasing visibility and usage of integrations with strategic partners through various activities such as:Writing technical blog postsEnhancing documentation and providing code examplesPresenting to both business and technical audiences at partner conferencesEngaging in or facilitating webinarsCreating and promoting demosLeading go-to-market discussions with strategic partnersYou will be at the cutting edge of Generative AI, exploring practical applications with open-source technologies. This role offers significant autonomy and creative freedom, aiming for a tenfold impact compared to similar positions in large tech companies.About YouYou are enthusiastic about ML Engineering, developing actionable AI applications, and optimizing them for the cloud. Your passion for learning new engineering concepts and technologies is evident, and you enjoy discussing these topics with peers. You value a positive Developer Experience and take pride in writing easily comprehensible code.Excellent communication skills are vital, and you are comfortable speaking publicly to technical audiences. You engage positively with the ML community, and existing involvement in platforms such as GitHub, LinkedIn, Twitter, Reddit, or other educational channels is expected. Experience in Open Source development will be advantageous.More about Hugging FaceWe are actively working to create a culture that values diversity, equity, and inclusion.We are committed to building a team that reflects a variety of backgrounds and perspectives, fostering a collaborative atmosphere where all voices are heard.

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.

About Us:Modal is revolutionizing the AI infrastructure landscape. We provide seamless access to GPUs, rapid container startups, and integrated storage solutions, making it effortless for teams to train models, execute batch jobs, and deliver low-latency inference. Notable companies such as Suno, Lovable, and Substack trust Modal to transition from concepts to production while alleviating infrastructure management burdens.Based in New York City, San Francisco, and Stockholm, we are a rapidly expanding team that has achieved a 9-figure ARR and recently secured a Series B funding round at a valuation of $1.1 billion. With thousands of customers relying on us for their production AI workloads, our clientele includes industry leaders like Lovable, Scale AI, Substack, and Suno.Joining Modal means becoming part of one of the most dynamic AI infrastructure teams at an early stage, opening doors for personal and professional growth. Our team comprises creators of widely-used open-source projects (e.g., Seaborn, Luigi), distinguished academic researchers, international competition medalists, and seasoned engineering and product leaders with decades of experience.The Role:Modal is on the lookout for a skilled Forward Deployed Machine Learning Engineer (FDE) to collaborate with our sales team and spearhead technical sales initiatives. As an FDE, you will serve as the technical expert in our sales engagements, partnering with Account Executives to help enterprise customers grasp how Modal can transform their AI/ML infrastructure. Your responsibilities will include:Collaborating with Account Executives to identify, evaluate, and finalize strategic enterprise opportunitiesLeading technical discovery sessions with potential clients to assess their current infrastructure, pain points, and specific requirementsCrafting and presenting compelling technical solutions that illustrate how Modal meets client needsConducting technical demonstrations, experiments, and proof-of-concept projects that highlight Modal's capabilitiesNavigating complex technical evaluations while addressing security, compliance, and integration concernsEstablishing trusted advisor relationships with technical decision-makers, including CTOs, VPs of Engineering, and ML Engineering leadsWorking alongside product and engineering teams to relay customer feedback and influence the product roadmap

About AdaptiveAdaptive Security stands at the forefront of AI cybersecurity, recognized as NVIDIA and OpenAI’s exclusive investment in this domain. Our mission is to thwart AI-driven cyberattacks. In December 2025, we proudly announced an $81M Series B funding round led by NVIDIA and Bain Capital Ventures, joined by esteemed investors including Capital One Ventures, Citi Ventures, and ongoing support from Andreessen Horowitz (a16z), the OpenAI Startup Fund, and Abstract Ventures. This round signifies NVIDIA’s inaugural foray into AI cybersecurity investments.Founded by seasoned entrepreneurs Brian Long and Andrew Jones, who have a proven track record of building and scaling industry-defining companies, Adaptive is set to shape the security landscape for the AI era. Brian and Andrew previously co-founded Attentive, which achieved over $500M in annual revenue and a valuation exceeding $10B, and TapCommerce, acquired by Twitter. Their wealth of experience in creating high-growth, product-focused businesses is instrumental as Adaptive secures enterprises against ever-evolving threats.With a growing clientele that includes leading banks, technology firms, and healthcare organizations, Adaptive is dedicated to safeguarding teams from emerging threats like deepfakes, smishing, and AI-generated voice scams. As we experience rapid enterprise adoption and explore a market exceeding $200B, we are just scratching the surface of our potential.Role OverviewWe are on the lookout for a Staff Machine Learning Engineer to spearhead the development of Adaptive's ML capabilities. As an AI cybersecurity firm, our products leverage LLMs and ML models to identify, classify, and respond to threats in real time. The role of ML is pivotal to the future of our offerings, and we seek an individual who can define our strategy, establish the infrastructure, and execute hands-on initiatives.Currently, we lack dedicated ML infrastructure or a team; you will have the unique opportunity to build this from the ground up. You will set the technical direction for ML applications across the organization, establish the necessary infrastructure, and engage in hands-on development.Key ResponsibilitiesCraft and define Adaptive's ML strategy: identify optimal applications of ML across our product suite, determine required infrastructure, and guide build vs. buy decisions.Design and implement end-to-end production ML systems, including data pipelines, model training, evaluation frameworks, and inference serving.Establish a robust evaluation methodology to measure model quality, identify regressions, and facilitate data-driven decisions regarding model modifications.Take ownership of data strategy: ensure the acquisition of necessary data in the required formats, define labeling processes, and establish feedback loops to enhance model performance over time.Collaborate with product engineers to integrate ML capabilities seamlessly into our products.

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.

Role overview Quizlet is looking for a Machine Learning Engineer to join the Monetization and Decision Systems team. The focus is on building models that help drive user engagement and support revenue growth using data-driven approaches. What you will do Design and implement machine learning models that contribute to monetization strategies and decision-making systems. Collaborate with engineering, product, and design teams to deliver solutions that scale. Apply machine learning skills to develop products used by millions of learners. Locations Denver, CO New York, NY San Francisco, CA Seattle, WA

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.

About InfoTrackInfoTrack is a leading platform that connects law firms with the essential services and courts needed for successful litigation. As global pioneers in legal technology, we excel in creating integrations that significantly enhance law firm efficiency and improve the legal system.Our ambitious culture values the contributions of our people, making professional development, open dialogue, and transparent leadership cornerstones of our operations. If you are intelligent, committed, and motivated to develop a market-leading solution that positively impacts our clients' lives, we invite you to join our team.About the RoleIn the capacity of Senior Cloud Infrastructure Engineer at InfoTrack, you will be instrumental in defining and implementing our cloud strategy. This is a dynamic, hands-on role where you will design, construct, and optimize secure and scalable infrastructure while collaborating closely with developers, product teams, and international colleagues. Your efforts will drive enhancements across tools, processes, and technologies, ensuring our cloud platform remains cost-effective, high-performing, and aligned with business objectives.Key ResponsibilitiesLead and implement InfoTrack US's cloud infrastructure strategy, ensuring systems are secure, current, and optimized for performance and cost.Deliver robust, scalable solutions through the continual enhancement of tools, processes, and technologies.Collaborate with developers, product teams, and global stakeholders to ensure infrastructure aligns with business requirements.Establish and monitor KPIs to measure operational excellence, security, and compliance.Cultivate strong relationships with cloud and DevOps teams in Australia and the UK.

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 Team as a Machine Learning Engineer – Search, Ranking & Personalization!Are you passionate about leveraging machine learning to create intelligent, personalized experiences for users? At fuku, a rapidly growing shopping platform, we are on a mission to revolutionize the way consumers discover products. With a vibrant user base of over 350,000 active users and a remarkable 90% retention rate, our focus is on developing advanced search and ranking systems that build trust and enhance product discovery at scale.As a Machine Learning Engineer, you will play a pivotal role in designing, constructing, and scaling machine learning systems that impact search, ranking, and personalization for our platform, which serves hundreds of millions of items daily. Collaborating with a talented team of engineers from leading tech firms like Pinterest and Amazon, you will have the opportunity to influence user engagement and retention significantly.

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