Staff Machine Learning Engineer

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.

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 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.

At Confido, we are revolutionizing the AI infrastructure for consumer packaged goods (CPG) brands, streamlining everything from deductions to production planning. Our platform integrates cash applications, deductions, disputes, trade promotion management, forecasting, demand planning, and analytics into a cohesive system. The outcome is significant time savings, enhanced decision-making capabilities, and accelerated growth potential.We proudly serve over 200 brands, managing more than $20 billion in revenue, with clients like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana.With our recent successful $15 million Series A funding round led by Footwork Ventures and Y Combinator, we are poised for rapid expansion.As a Staff AI / ML Engineer, you will play a crucial role in developing and implementing the core AI systems that power our platform, including LLM-driven document understanding and predictive models that assist brands in making informed decisions.This foundational position will involve direct collaboration with our CEO and CTO to define our long-term AI strategy and architecture.

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.

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.

Supported by top-tier Silicon Valley investors, Peregrine Technologies is dedicated to assisting public safety organizations, state and local governments, federal agencies, and private-sector institutions in tackling societal challenges with unmatched speed and precision. Our AI-driven platform transforms fragmented data into actionable insights—quickly presenting mission-critical information that empowers informed decisions and enhances outcomes at every level. Currently, we serve hundreds of clients across over 30 states and two countries, impacting more than 125 million individuals, and we are poised to broaden our reach into enterprise sectors and international markets.TeamAt Peregrine, we hold a strong belief that empathy is key to our solutions. Understanding user interactions with our products is crucial, and our engineers work closely with the team on-site to explore the diverse use cases that our platform addresses.We prioritize both accountability and teamwork; you will take full ownership of significant features while collaborating with fellow engineers to ensure their successful completion. We value humility and empathy as vital components in crafting effective solutions—you'll engage directly with our deployment team and users as we refine our offerings to meet their needs. Creativity and perseverance are essential in realizing our vision.RoleAs a key member of our engineering team, you will play a pivotal role in delivering unique value to our clients. Your mission will be to create powerful, intuitive user experiences powered by generative AI, allowing users to engage with our platform in innovative ways. Your contributions will help develop safe, impactful AI-driven features that enable customers to solve real-world challenges more swiftly and effortlessly.Your responsibilities will encompass a variety of complex tasks, including scaling our platform to manage terabytes of data from multiple sources, efficiently querying and notifying users in real-time, and optimizing search algorithms for rapid result delivery.Our technology stack is continuously evolving, built on a backend foundation of Python, Django, Celery, Airflow, and Kafka; a frontend developed with React, Redux, and Mapbox; data storage solutions including PostgreSQL and Elasticsearch; machine learning models hosted on Bedrock and Sagemaker; and supported by AWS, Pulumi, Terraform, and Kubernetes for our infrastructure.About YouA strong desire and initiative to take ownership of large components of our projects.Experience with machine learning frameworks and concepts.Proficient in Python and familiar with web development frameworks.Ability to work collaboratively in a team environment.A passion for developing innovative solutions to complex problems.

Location: New York, NYStart date: ASAPLanguages: English (required)About the RoleJoin Pragmatike as we partner with a dynamic AI cybersecurity firm, recognized by top-tier investors and visionary AI leaders. This innovative company is dedicated to establishing robust security measures for the AI era, safeguarding enterprises from advanced threats, including deepfakes, smishing, and synthetic voice attacks.Following a successful Series B funding round with industry-leading AI and venture partners, the organization is poised for substantial growth. Trusted by major financial institutions, technology giants, and healthcare providers, they are rapidly scaling to meet the demands of a $200 billion market opportunity.We are seeking a Staff Machine Learning Engineer to architect and enhance the company’s machine learning capabilities from the ground up. This role is pivotal to our product vision and focuses on strategic ownership, infrastructure development, and comprehensive execution of machine learning across the organization.Currently, there is no dedicated machine learning infrastructure or team. You will lay the groundwork: identifying where machine learning can add product value, designing end-to-end production systems, and setting the technical roadmap for the evolution of machine learning within the company.This position is highly impactful and offers significant autonomy, ideal for candidates experienced in building production ML systems and ready to develop a robust ML function from inception to full-scale operation.What You'll DoDefine the company's machine learning strategy: identifying application areas across products, determining necessary infrastructure, and making informed build vs. buy decisions.Design and construct production ML systems from scratch, including data pipelines, model training workflows, evaluation frameworks, and inference serving.Establish a rigorous evaluation methodology to assess model quality, identify regressions, and support iterative improvements based on data.Oversee data strategy: define necessary data, structure labeling, establish feedback loops, and ensure models evolve continuously.Collaborate closely with product and backend engineers to integrate machine learning into customer-facing systems.Contribute production-quality code to the existing codebase and participate in architectural decision-making.In time, assist in recruiting, mentoring, and leading the ML team as the function grows.

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 Nagarro as an Associate Staff Engineer specializing in Machine Learning, where you'll be at the forefront of innovation in AI technology. In this role, you will collaborate with cross-functional teams to design, implement, and optimize machine learning algorithms that drive impactful business solutions. Your expertise will help shape the future of our products and services.

Join Spotify as a Staff Machine Learning Engineer and become part of a forward-thinking team that is shaping the future of music streaming technology. We are seeking a talented engineer who is passionate about leveraging machine learning to drive innovation and enhance user experiences. In this pivotal role, you will collaborate closely with cross-functional teams to design, implement, and scale sophisticated machine learning models and algorithms.

Join modal as a Member of Technical Staff specializing in Machine Learning Training Systems. In this role, you will contribute to the development and optimization of cutting-edge machine learning platforms that enhance the training and deployment of AI models. Collaborate with a talented team of engineers and data scientists to innovate and drive impactful solutions in the realm of artificial intelligence.

Join Hinge: The Dating App Designed to Be Deleted!In a world where meaningful connections are increasingly elusive, Hinge is committed to fostering authentic relationships. Our mission is to inspire intimate connections and reduce loneliness, empowering users to find love through a deeper understanding of their behaviors. With millions of users globally, Hinge stands as the most trusted platform for relationship-seekers.About the Position:We are looking for a Senior Machine Learning Engineer to spearhead the design, development, and implementation of innovative machine learning systems that enhance our core products focused on User Growth and Monetization. Your expertise will help create highly personalized user experiences that not only drive business growth but also cater to individual preferences. By aligning the right users with the right products at the right time, you will empower our product teams to achieve significant revenue growth and heightened user satisfaction.The Growth Product Group is dedicated to crafting paid features that accelerate dating success while enhancing engagement throughout the user lifecycle, making Hinge the go-to dating app for diverse communities. You can anticipate tackling a wide array of challenges, from ensuring optimal messaging to users at pivotal moments to fine-tuning the effectiveness of our paid offerings. This rapidly evolving team presents an exciting opportunity to shape the vision and strategy that will drive substantial growth and deepen the impact of machine learning at Hinge.

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

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 Hinge: The Dating App Built for Real ConnectionsIn an increasingly digital era, forging authentic relationships can be a challenge. At Hinge, our mission is clear: to foster intimate connections that reduce loneliness. We are deeply committed to analyzing user behavior to facilitate meaningful relationships, with our success measured by one key criterion—creating exceptional dates. With millions of users worldwide, Hinge has established itself as the most reliable platform for finding genuine relationships.About the Opportunity: Our Dating Outcomes team is pivotal in ensuring users encounter their most compatible matches, present themselves effectively, and spark engaging conversations. In essence, we are dedicated to helping individuals enjoy fantastic dates!We are seeking experienced Staff Machine Learning Engineers to shape an AI-driven dating experience by leveraging Hinge’s extensive preference data. You will lead the development of end-to-end recommendation systems, explore the potential of large language models (LLMs), and craft photo and mixed-input embedding models. Additionally, you will build and deploy real-time predictive models that significantly enhance the user experience for millions. As part of our rapidly expanding team, you will have the chance to define the strategy, vision, and roadmap for advancing machine learning at Hinge.

Role Overview Spotify is hiring a Staff Machine Learning Engineer to join the Home Podcast team in New York, NY. This position focuses on building and improving machine learning models that power podcast experiences for millions of listeners. What You Will Do Design, implement, and refine machine learning models for podcast features and recommendations Work closely with teams across engineering, product, and design to deliver solutions that improve user experience Contribute technical expertise to shape the direction of podcasting services on the Spotify platform Impact This role directly influences how Spotify listeners discover and enjoy audio content, helping define the future of podcasts on the platform.

Why Join Shiftsmart?Be Part of the Future of Labor. At Shiftsmart, we are innovating the labor market by combining comprehensive workforce management technology with a rapidly expanding global network of over 5 million flexible workers. Our platform enables scalable labor solutions for major companies including Circle K, Pepsi, Dollar General, and Starbucks. As one of the fastest-growing startups in the nation, we have experienced 2-3x growth annually since inception and secured over $120 million from esteemed investors such as D1 Capital and Imaginary Ventures. And we’re just getting started!Our Mission: Empowering Workers and Enterprises. We aim to create the leading platform for hourly workers and enterprises, providing flexibility, choice, and opportunities for upward social mobility.Be a Part of Our Growth Journey. This is a unique chance to join a rapidly scaling business that is transforming hourly labor dynamics and addressing a $2 trillion opportunity in the U.S. alone.Drive Impact and Ownership. Collaborate with a team that challenges and supports one another, dedicated to building a remarkable business that enhances flexibility and choice for workers everywhere.Shape Your Career Trajectory. Experience accelerated learning and growth alongside a world-class team hailing from top tech companies (e.g., Uber, Airbnb, Google, Amazon), prestigious business schools (e.g., Harvard Business School, Stanford GSB, Wharton), and elite professional services (e.g., Bain, BCG, Goldman).Master Execution. At Shiftsmart, we believe that #ExecutionIsBinary, and we are committed to helping you develop this vital skill for your career and beyond.Role Overview: What You Will DoAs a Machine Learning Engineer, you will play a critical role in determining how machine learning is utilized to derive insights from the expansive data generated by our labor marketplace. You will design, develop, and deploy end-to-end machine learning systems while navigating ambiguity, leveraging our marketplace data to address complex challenges and drive business value for Shiftsmart.