Technical Program Manager, R&D & Technology Transfer
Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control by designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for high precision manipulation of complex or deformable objects. Work with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.
2026 New Grad | Software Engineer, Full-Stack
Ship critical infrastructure managing real-world logistics and financial data for large enterprises. Own the why by building deep context through customer calls and understanding Loop's value to customers, pushing back on requirements if better solutions exist. Work full-stack across system boundaries including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to handle routine tasks enabling focus on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise velocity.
Member of Technical Staff - Post Training, Applied
The role involves acting as the technical owner for enterprise customer post-training engagements, owning post-training projects end-to-end from customer requirements through delivery and evaluation. Responsibilities include translating customer requirements into concrete post-training specifications and workflows, designing and executing data generation, filtering, and quality assessment processes, running supervised fine-tuning, preference alignment, and reinforcement learning workflows, as well as designing task-specific evaluations, interpreting results, and feeding learnings back into core post-training pipelines.
Senior Machine Learning Engineer - Payments
As a machine learning engineer on the core ML payments team, you will design, build, and deploy scalable machine learning solutions and systems. You will experiment with new modeling approaches and strategies, collaborate closely with a team of engineers on ingesting signals, and productionize these models. Your work will empower millions of users through well-known and emerging Fintech applications with access to financial services. Responsibilities also include working on both 0-1 stage problems and 1-10 stage problems, developing AI/ML models through the full lifecycle from offline training to online serving and monitoring, collaborating with teams across the company to define the ML roadmap, and applying data-driven decisions in day-to-day work in a high ownership, bottom-up driven team.
Research Engineer/Scientist - Generative UI, Consumer Products
As a Research Engineer/Scientist on the Consumer Products Research team, you will train and evaluate state-of-the-art models along important axes for future devices, work through challenges to transform nascent research capabilities into usable capabilities, and help define software frameworks for long-term future use.
Senior Research Engineer/Scientist - Edge, Consumer Products
As a Research Engineer/Scientist on the Consumer Products Research team, you will train and evaluate multimodal state-of-the-art (SoTA) models along axes important to the vision for future devices. You will develop novel architectures that improve model performance when scaling the models themselves is not an option. You will also work to transition nascent research capabilities into capabilities that can be built upon.
Staff Research Engineer
On the Research team, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. You will design and implement state of the art methods for instruction tuning and information retrieval. You will develop models for customer support tasks that exceed the performance of closed source models, experiment with small open-source models to drive order of magnitude reductions in latency across channels, and break down ambiguous research ideas into clear, iterative milestones and roadmaps. Engineers own their work end-to-end, making real impact by diving deep into complex system challenges, building elegant solutions that scale to millions of users, and creating automation that prevents problems before they happen.
Senior Data Scientist
Designing and building agents in high-consequence environments where outputs need to be validated to a high standard, performing exploratory data analysis, model building, validation, and performance monitoring, leading data science efforts within cross-functional delivery teams by partnering with engineers, designers, and product leads for successful outcomes, understanding deeply core customer problems to ensure technical solutions drive real value, and translating real-world problems into technical strategies and measuring model impact with scientific rigor.
Member of Technical Staff (Applied AI)
As a Member of Technical Staff on Applied AI, you will productionize frontier AI models to solve complex real-world problems, collaborate closely with researchers and other teammates on the latest advancements in AI and ML, work closely with customers to integrate models into their technology stack, make direct business impact with a high level of product ownership, and be a founding member of a fast-growing team while wearing many hats.
Machine Learning Engineer (Foundation Models & Personalization)
The Machine Learning Engineer is responsible for building and deploying machine learning models that enhance sleep experiences through personalization, prediction, and behavior understanding, including readiness forecasting, event detection, and individualized recommendations. They will apply and adapt foundation-model capabilities to product workflows, develop user behavior models connecting longitudinal signals to actionable interventions, and design evaluation strategies for offline metrics, slice-based analysis, calibration, reliability, and fairness. The role involves partnering with Product teams to run high-quality online experiments, productionizing models via scalable training and inference pipelines, model monitoring, drift detection, alerting, and continuous improvement loops. Collaboration with cross-functional partners such as Product, Mobile, Backend, and Clinical teams is essential to scope requirements and deliver high-impact features.
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