Senior Machine Learning Engineer - Conversion Modeling at unity3d | San Francisco

Join the Revolution in Behavioral IntelligenceAmplify Your InfluenceYou have achieved remarkable success in your career, creating robust behavioral or neuroscience models that have driven significant outcomes. You possess a talent for discerning patterns in user behavior, comprehending motivations, and optimizing end-to-end user experiences.Now, envision extending your impact across multiple products and organizations, enhancing the entire app ecosystem. Every application at your fingertips becomes smarter, more engaging, and indispensable to its users.Your expertise can empower product teams to innovate more rapidly, delight users, and boost revenue, all thanks to the behavioral intelligence you develop once and deploy universally.We share this vision: our team has accomplished this repeatedly at industry leaders like Uber, Apple, Google, and Chime, generating tens of billions of dollars in value for products vital to billions globally. We are poised to elevate our impact even further.Does this resonate with the next chapter you're seeking? If so, continue reading.Palladio: Pioneering BreakthroughsPalladio AI is an innovative AI platform aimed at transforming product-led growth and enhancing the value our clients provide in users’ daily lives.Our initial focus is on mobile gaming, where development is swift, user engagement is high, and experimentation yields immediate results—making it the perfect testing ground for our platform.Your ContributionsOur team is constructing foundational systems in behavioral modeling, causal inference, forecasting, and agentic platforms. You will play a pivotal role in extending these areas: creating machine learning and AI-driven behavioral models to identify and highlight product opportunities while deploying self-improving learning loops with each iteration. Your work will analyze user sentiments, thoughts, decisions, and actions—translating behavioral insights into opportunities that enhance product intuitiveness, engagement, and rewards. In essence, you will convert first-principles data science, neuroscience, cognitive science, and machine learning into scalable solutions across various industries.Your ProfileUser-Focused. You empathize with users' challenges, needs, and goals throughout their journeys, measure success through user outcomes, and convert insights into innovative and engaging product experiences.Scientific Innovator. You...

Join latentlabs, a pioneering company at the forefront of biotechnology, as we seek a talented Machine Learning Researcher specializing in generative modeling. You will become part of a dynamic, interdisciplinary team comprising machine learning experts, protein engineers, and biologists, all committed to revolutionizing biological control and disease treatment. In this role, you will design innovative generative models aimed at creating new proteins that exhibit functionality in wet lab assays.

The Bot CompanyAt The Bot Company, we are on a mission to create an innovative robotic assistant for every household.Our dynamic team, composed of talented engineers, designers, and operators, is based in San Francisco. We have a rich background from industry leaders such as Tesla, Cruise, OpenAI, Google, and Pixar, and we have successfully delivered products to hundreds of millions of users, honing our ability to create exceptional products and experiences.We pride ourselves on maintaining a streamlined team structure that fosters swift decision-making and minimizes bureaucracy. Each member is considered an Individual Contributor, granted substantial autonomy, ownership, and accountability. Our culture enables us to work across the technology stack with an emphasis on rapid iteration and execution.What We Seek in CandidatesCandidates for all positions at The Bot Company must exhibit remarkable sharpness and the capacity to thrive in high-pressure environments. We expect candidates to showcase:Exceptional Cognitive Abilities: You possess quick thinking, instant learning capabilities, and the ability to reason across diverse domains.Engineering Curiosity: You demonstrate an innate desire to understand how systems function, even beyond your area of expertise.Performance-Driven Attitude: You excel in fast-paced settings, effectively navigate ambiguity, and thrive under demanding circumstances.Machine Learning: Multimodal Foundation ModelsWe are developing unified foundation models capable of reasoning across text, images, video, and kinematics to inform intelligent robotic behaviors.You will engage with large-scale multimodal networks, overseeing the complete process from data handling to model training and deployment.Your ResponsibilitiesConstruct Native Multimodal Policies: Create architectures where vision, language, and other modalities are represented in a unified manner.Enhance Cross-Modal Reasoning: Explore and implement strategies to ensure that the model not only correlates modalities but also comprehends them (e.g., linking visual physics to kinematic constraints).Manage the Training Loop from Start to Finish: Design, execute, troubleshoot, and refine large-scale training experiments; identify failure points, enhance data mixtures, and tighten evaluations to achieve measurable improvements.Deploy and Refine Real Systems: Integrate models into practical robotic frameworks, enhance robot code for model deployment, and optimize performance for edge inference.

Join Prima MenteAt Prima Mente, we are pioneers in the field of biology-focused artificial intelligence. Our mission is to generate unique datasets, develop versatile biological foundation models, and translate scientific breakthroughs into real-world clinical applications. Our primary focus is on understanding the brain in-depth, safeguarding it from neurological disorders, and enhancing its function during health. Our dynamic team of AI researchers, experimentalists, clinicians, and operational experts are strategically located in London, San Francisco, and Dubai.Your Role: Foundation Models for BiologyAs a Machine Learning Engineer, you will be instrumental in the design, implementation, and scaling of foundational AI models and infrastructure for multi-omics at an unprecedented scale. Your contributions will facilitate significant advancements in scientific comprehension and lead to groundbreaking applications in the medical and biological fields.Key Responsibilities:Develop high-performance machine learning algorithms optimized for large-scale applications, ensuring utmost reliability and efficiency.Design, implement, and maintain comprehensive experimentation pipelines that allow for rapid iterations, precise assessments, and reproducible research results.Refactor and enhance prototype research code into clean, maintainable, and efficient repositories prepared for production-level deployments.Create fast data processing workflows that can effectively manage extensive datasets to expedite research and model development.Engage in experimental design, with a focus on high-impact experiments that yield the greatest signal-to-noise ratio.Growth ExpectationsIn 1 month, you will initiate initial experiments utilizing state-of-the-art machine learning models, review and apply advanced research papers, and enhance existing code for improved efficiency and precision.By 3 months, you will take ownership of a prototype model architecture, showcasing notable algorithmic enhancements, and contribute to methods for large-scale data ingestion and training.Within 6 months, you will have significantly impacted the implementation of a high-performance foundation model, incorporating key algorithmic optimizations that improve scalability and throughput, along with publishing internal benchmarks that demonstrate substantial effects.

About Sygaldry TechnologiesSygaldry Technologies is at the forefront of innovation, developing quantum-accelerated AI servers designed to significantly enhance the speed of AI training and inference. By merging quantum computing with AI, we are navigating the challenges of increasing compute costs and energy constraints, paving the way towards superintelligence. Our AI servers leverage a diverse range of qubit types in a fault-tolerant architecture, achieving the necessary balance of cost, scalability, and speed for advanced AI applications. We are committed to pioneering new frontiers in physics, engineering, and AI, tackling the most complex challenges with a culture grounded in optimism and rigor. We seek individuals passionate about defining the convergence of quantum and AI and making a meaningful global impact.About the RoleGenerative AI is revolutionizing computational possibilities but reveals the limitations of classical hardware. While diffusion models yield remarkable outcomes, their iterative sampling and high-dimensional score estimation often lead to computational inefficiencies.We are convinced that quantum computing holds the key to overcoming these challenges. As an ML Research Scientist, you will operate at the intersection of generative modeling and quantum acceleration, formulating theoretical foundations and practical applications that merge these domains. Your focus will be on identifying areas where quantum methods can deliver substantial advantages in generative workflows, providing not just incremental enhancements but transformative improvements grounded in mathematical principles.Your ResponsibilitiesGenerative Model Architecture & EfficiencyInnovate state-of-the-art diffusion and score-based generative models.Investigate computational bottlenecks in sampling, denoising, and likelihood estimation.Design and evaluate novel solver techniques for diffusion ODEs/SDEs.Quantum-Classical IntegrationDiscover mathematical structures in generative models that are suitable for quantum acceleration.Prototype hybrid workflows that utilize quantum subroutines to enhance classical processes.Conduct rigorous benchmarks comparing theoretical advantages against practical benefits in realistic scenarios.Research to ProductionTransform research findings into scalable implementations.Collaborate with quantum hardware teams to guide architectural specifications.Facilitate the integration of research insights into production environments.

Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through innovative cell rejuvenation techniques aimed at reversing diseases, injuries, and disabilities that can arise throughout life.For further insights, please visit our website at altoslabs.com.Our ValueOur singular Altos Value is: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe firmly believe that diverse perspectives are crucial for scientific innovation. At Altos, exceptional scientists and industry leaders collaborate globally to further our shared mission. We prioritize Belonging, ensuring all employees feel valued for their unique perspectives, and we hold ourselves accountable for maintaining a diverse and inclusive environment.Your Contributions to AltosAs a member of our team, you will accelerate and enhance our efforts in developing unified, multi-modal generative foundation models tailored for multiscale biology. You will be a key player in multidisciplinary teams that create the computational platforms essential for Altos to fulfill its mission.In this position, you will collaborate with other scientists and engineers across the Institute of Computation to design, develop, and scale cutting-edge foundation models that address biological inquiries and assist in discovering novel interventions for aging and disease. Your focus will be on synthesizing unstructured multimodal signals with structured relational data and knowledge graphs that depict biological realities.The ideal candidate will excel in a dynamic environment that values teamwork, transparency, scientific excellence, originality, and integrity.

Join Our Team at GridwareAs a Senior Machine Learning Engineer specializing in Multi-Sensor Modeling, you will be at the forefront of developing innovative solutions that enhance the reliability and safety of the electrical grid. Our groundbreaking Active Grid Response (AGR) platform leverages cutting-edge technology to monitor various aspects of the grid, enabling proactive maintenance and fault mitigation. Your expertise will play a pivotal role in advancing our mission to protect the grid and ensure efficient operations. Are you ready to make a significant impact?

The Bot CompanyJoin us in creating a revolutionary robot designed to enhance everyday living.Based in San Francisco, our dynamic team consists of talented engineers, designers, and operators hailing from industry leaders like Tesla, Cruise, OpenAI, Google, and Pixar. We've successfully delivered exceptional products and experiences to hundreds of millions of users.Our deliberately streamlined team structure fosters prompt decision-making, eliminating bureaucracy and hierarchy. Each team member is an individual contributor empowered with significant scope, radical ownership, and direct accountability, working collaboratively across the stack in a fast-paced environment focused on rapid iteration and execution.What We Value in CandidatesAt The Bot Company, we seek individuals who exhibit remarkable sharpness and can thrive in high-pressure situations. Throughout the selection process, we expect candidates to showcase:Exceptional mental acuity: You think quickly, absorb information rapidly, and navigate unfamiliar domains with ease.Engineering curiosity: You possess an innate desire to understand system functionalities, extending beyond your primary expertise.High performance mindset: You excel in ambiguous environments and maintain high productivity under challenging conditions.Machine Learning Engineer: World ModelsWe are developing neural simulators capable of comprehending the fundamental

Senior Machine Learning Engineer - Model Evaluations for the Public Sector The Public Sector Machine Learning team at Scale AI pioneers the deployment of cutting-edge AI systems, including Large Language Models (LLMs), agentic models, and comprehensive multimodal pipelines, within critical government operations. We establish robust evaluation frameworks that ensure these models function reliably, safely, and effectively in real-world scenarios. As a Senior Machine Learning Engineer, you will architect, implement, and enhance automated evaluation pipelines that empower our clients to trust and effectively utilize advanced AI systems in defense, intelligence, and federal missions. Your Responsibilities Include: Creating and maintaining automated evaluation pipelines for machine learning models, focusing on functional, performance, robustness, and safety metrics, including evaluations based on LLM judges. Designing test datasets and benchmarks to assess generalization, bias, explainability, and potential failure modes. Building evaluation frameworks for LLM agents, which includes the infrastructure for scenario-based and environment-based testing. Conducting comparative analyses of model architectures, training procedures, and evaluation results. Implementing tools for continuous monitoring, regression testing, and quality assurance of machine learning systems. Designing and executing stress tests and red-teaming workflows to identify vulnerabilities and edge cases. Collaborating with operations teams and subject matter experts to generate high-quality evaluation datasets. This position requires an active security clearance or the ability to obtain one.

The OpportunityJoin us at ComfyOrg as a Senior/Staff Applied Machine Learning Engineer! We are on the hunt for a passionate innovator who is enthusiastic about optimizing model inference. You will play a pivotal role in developing the heart of ComfyUI, our cutting-edge visual AI platform. Your expertise will help us push the limits of AI model performance, making them run faster and more efficiently than ever before.Are You a Match?You are fascinated by model inference, memory management, and torch optimizations.You possess experience in writing production-level PyTorch code that challenges performance standards.You have a passion for understanding the inner workings of AI models.You thrive on developing highly optimized code that consistently delivers results.You believe that the current landscape of ML deployment holds significant room for improvement.Your Responsibilities:Develop and enhance the core inference engine that drives ComfyUI.Optimize large models for speed and memory efficiency.Collaborate with our core team to architect new features.Tackle complex technical challenges within the visual AI domain.Contribute to the future direction of our technology.Experience with diffusion or LLM models, as well as creating custom nodes for ComfyUI, is highly beneficial.

About NomadicMLAt NomadicML, we are harnessing the power of artificial intelligence to revolutionize the way machines understand and interpret motion. Our vision-language models (VLMs) transform vast amounts of video data into actionable insights, paving the way for advancements in self-driving technology, robotics, and industrial automation.Founded by Mustafa Bal and Varun Krishnan, both alumni of Harvard University, our team is comprised of experts who have previously developed critical AI systems at industry giants like Snowflake, Lyft, Microsoft, Amazon, and IBM Research. With a commitment to innovation, we are dedicated to mining insights from the 5 trillion miles driven by Americans annually, uncovering the next frontier in machine intelligence.About the RoleWe are looking for a passionate Machine Learning Engineer who excels at the intersection of foundational model research and production engineering. In this role, you will play a key part in optimizing how machines learn from motion, focusing on training and refining large-scale Vision-Language Models that analyze complex real-world video data.You will be responsible for creating multi-modal architectures that accurately perceive, localize, and describe motion events across millions of video frames, transforming these innovations into robust APIs and SDKs for enterprise clients.Working closely with the founders, your contributions will include:Training and assessing VLMs tailored for motion comprehension within autonomous driving and robotics datasets.Designing and scaling GPU-accelerated pipelines for training, fine-tuning, and inference on diverse data types (video, language, and sensor metadata).Developing evaluation frameworks that benchmark spatiotemporal reasoning and localization precision.

Mach9’s Machine Learning Infrastructure Engineers create and maintain the backbone for production AI models used in civil engineering and surveying. The team manages a machine learning pipeline that processes over 10,000 miles of labeled survey data, supports image segmentation networks, and runs 3D prediction models. These systems deliver real-time inference capabilities directly to surveyors and engineers working in the field. Role overview This position is designed for mid-career engineers with a strong background in both training and inference aspects of machine learning infrastructure. The work involves handling large-scale data and ensuring reliable performance for demanding, real-world applications. What you will do Build and improve training pipelines for deep transformer models using hundreds of terabytes of 3D point cloud and image data. Design and implement inference infrastructure to support both offline detection algorithms and responsive, real-time inference integrated with CAD software. Location Based in San Francisco.

About LightfieldAt Lightfield, we are pioneering the future of CRM with our AI-native platform that seamlessly integrates with your email, calendar, and meetings. Our innovative solution captures every interaction, transforming it into structured context, including accounts, tasks, follow-ups, and insights, ensuring that nothing is overlooked.We are fundamentally reimagining CRM by employing a flexible approach that adapts to how teams operate, rather than imposing rigid systems. Lightfield continuously learns, automates processes, and surfaces valuable insights that fuel growth. We are dedicated to creating a CRM platform that is not only fast and intelligent but also genuinely helpful.Our team is backed by prestigious investors like Greylock, Lightspeed, and Coatue, and has a rich history in building successful products, including Tome, a generative AI presentation tool utilized by over 25 million users. Our collective experience spans notable companies such as Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleJoin our dynamic AI/ML team at Lightfield, where we are developing the core experiences of our product through cutting-edge applications that amaze our customers. We are currently focused on creating a robust, domain-specific AI that surpasses conventional LLMs.We thrive on the challenge of crafting innovative AI solutions for professionals engaged in significant work, and we're eager to expand our AI/ML team to rise to this challenge.Your ResponsibilitiesDesign and deliver extraordinary AI experiences that empower sales teams.Collaborate closely with founders and executives to shape Lightfield's AI/ML strategy.Lead the training of new models utilizing both historical and synthetic training data.Develop and prototype innovative LLM-driven experiences, transforming them into robust product features.Contribute to building a top-tier AI/ML engineering team through recruitment and mentorship.Your Profile5+ years of industry experience in Natural Language Processing (NLP) with a strong portfolio of model training.Solid understanding of deep learning AI/ML frameworks and cloud services.Hands-on experience in ML Operations (ML Ops).Deep expertise in NLP and model training, particularly with Large Language Models (LLMs).Demonstrated ability to adapt open-source generative models for specific applications, with a comprehensive understanding of their architecture.

Company OverviewEcho Neurotechnologies is a pioneering startup in the Brain-Computer Interface (BCI) sector, dedicated to revolutionizing the lives of individuals with disabilities through advanced hardware engineering and artificial intelligence solutions. Our vision is to develop innovative technologies that empower users, restoring autonomy and enhancing their quality of life.Team CultureWe pride ourselves on cultivating an inclusive and dynamic team of skilled professionals who are passionate about their work. Our startup environment encourages ownership of impactful decisions and fosters continuous learning and collaboration, where every contribution is essential to our collective success.Job SummaryWe are on the lookout for a talented Machine Learning Research Engineer specialized in speech modeling to join our innovative team. The successful candidate will leverage ML/AI methodologies to create and refine adaptable speech models aimed at brain-computer interface applications, ultimately making a difference in the lives of patients facing severe disabilities. Candidates should possess significant expertise in speech modeling, feature engineering, time-series analysis, and the development of custom ML models.Key ResponsibilitiesDesign and evaluate diverse model architectures and strategies to enhance the accuracy and resilience of models for interpreting speech from brain activity.Investigate and implement cutting-edge speech features and representations within neural-decoding frameworks, informed by speech science and functional neurophysiology.Create pipelines for generating personalized and naturalistic speech from both text and brain activity inputs.Develop algorithms to analyze both intact and compromised speech signals, identifying biomarkers linked to various diseases and disabilities.Collaborate within a tight-knit team to build models, define R&D workflows, and translate scientific discoveries into practical applications.Contribute to best practices ensuring reliability, observability, reproducibility, and scientific rigor across the R&D landscape.Maintain well-documented, versioned code, analysis pipelines, and results for maximum interpretability and reproducibility.

About the RoleIn this exciting position, you will address comprehensive challenges to enhance the performance of our AI models deployed on robotic systems. Your responsibilities will include adding new features to our video processing data pipeline, updating our machine learning data loaders, training models to validate your modifications, and testing these changes in real-world robotic applications. This role requires the integration of numerous distributed Python services to achieve specific data processing and application tasks, alongside managing substantial cloud infrastructure for efficient business logic processing at scale.Your responsibilities will include:Conceptualizing and implementing innovative solutions to enhance system robustness, scalability, and speed.Revamping existing systems and services to accommodate significant future growth.Developing business logic to ensure our robots access the necessary data and that customers receive appropriate access to our robotic solutions.You may excel in this role if you:Possess extensive experience in building complex distributed applications or data pipelines at scale.Have a background in processing petabytes of data, especially video data.Demonstrate expertise in Python, with foundational knowledge in distributed infrastructure and solid understanding of modern machine learning principles.Have a robust foundation in contemporary ML techniques with experience in large-scale ML training and production deployments.Have familiarity with distributed cloud infrastructure and a deep understanding of cloud networking, permissions, and container orchestration (Kubernetes).About GeneralistAt Generalist, our mission is to realize the potential of general-purpose robots. We envision a future where industries and homes thrive on the collaboration between humans and machines. Our robots are designed to enhance productivity and efficiency.We focus on developing embodied foundation models, starting with dexterity, which necessitates pushing the boundaries of data, models, and hardware to enable robots to intelligently interact with their environments.Our company is deeply rooted in large-scale AI and robotics, with a team drawn from leading organizations like OpenAI, Boston Dynamics, and Google DeepMind, all committed to delivering groundbreaking advancements in AI technology.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

About Scale AI At Scale AI, we are committed to propelling the advancement of AI technologies. For over eight years, we have been a pioneer in the AI data sector, supporting groundbreaking innovations in areas such as generative AI, defense solutions, and autonomous driving. Following our recent Series F funding round, we are enhancing access to premium data to accelerate the journey towards Artificial General Intelligence (AGI). Building on our legacy of model evaluation for both enterprise and governmental clients, we are expanding our capabilities to establish new benchmarks for evaluations in both public and private domains. About This Role This position is at the leading edge of AI research and practical implementation, concentrating on reasoning within large language models (LLMs). The successful candidate will investigate critical data types vital for evolving LLM-based agents, including browser and software engineering agents. You will significantly influence Scale’s data strategy by pinpointing optimal data sources and methodologies to enhance LLM reasoning. To excel in this role, you will require a profound understanding of LLMs, planning algorithms, and fresh approaches to agentic reasoning, alongside inventive solutions to challenges in data generation, model interaction, and evaluation. Your contributions will lead to transformative research on language model reasoning, facilitate collaboration with external researchers, and engage closely with engineering teams to translate cutting-edge advancements into scalable, real-world applications.

Join the Sleep Fitness RevolutionAt Eight Sleep, we are dedicated to unlocking human potential through the power of optimal sleep. As pioneers in the sleep fitness domain, we are transforming the concept of well-being by developing cutting-edge hardware, software, and AI technologies designed to enhance sleep quality. Our innovative products are engineered to maximize mental, physical, and emotional performance, turning each night into a tailored, data-driven recovery session.Trusted by elite athletes and health-conscious individuals across over 30 countries, Eight Sleep has been recognized as one of Fast Company’s Most Innovative Companies in 2019, 2022, and 2023, as well as featured twice in TIME's “Best Inventions of the Year.” Our team operates like a high-performance unit: agile, focused, and driven by impactful results. We prioritize refining and iterating on our offerings to enhance our members' sleep experiences and empower them to wake up rejuvenated.Every position at Eight Sleep offers an opportunity to contribute to groundbreaking technology, collaborate with exceptional talent, and influence a future where sleep is a proactive element of living well. If you are passionate about pushing boundaries and creating innovative solutions, this is your chance to make a difference in how the world experiences sleep and its potential.High Standards. No Compromises.At Eight Sleep, we operate with intensity and commitment, reflecting the mindset of top performers. We embrace a relentless focus on excellence in our endeavors, akin to the mamba mentality applied to innovative ideas and next-gen technology. We are not just about meeting expectations; we strive to exceed them, working diligently not out of obligation, but from a passion for impactful work. If you flourish under pressure and seek to engage in the most meaningful projects of your career, you will find a home here. If you desire an easier path, this may not be the right place for you.The RoleWe are in search of a Machine Learning Engineer to develop and deploy consumer-oriented AI systems that enhance personalization, coaching, and next-gen “sleep intelligence.” You will collaborate across data science, modeling, product development, and engineering to convert research insights into tangible, measurable improvements for our members.This role is perfect for individuals who thrive on end-to-end ownership, from defining problems and prototyping to offline evaluations, online experimentation, production deployment, and continuous iteration.

About the RolePerplexity is seeking a talented Model Behavior Architect to join our innovative AI team in San Francisco. In this role, you will be instrumental in developing and evaluating AI products that enhance user experiences across various domains. Collaborating closely with both research and product teams, you will design strategies for prompt and context engineering that ensure high-quality interactions.This position uniquely blends creativity and analytical skills. You will gain a profound understanding of our answer engine by rigorously testing model capabilities and working with our AI infrastructure, including system prompts, tool prompts, skills, and evaluations, to create an exceptional product experience for our users.As the go-to expert on prompting, model quality, and behavioral consistency, you will be pivotal in the deployment of new product features and model releases.Key ResponsibilitiesContext Engineering: Create, test, and refine context strategies and system prompts that influence answer engine behavior across various products, features, and use cases.Evaluation Systems: Develop automated and semi-automated evaluation pipelines to assess model quality, detect regressions, and scale across product surfaces.Model Launch Support: Collaborate with research and engineering teams to validate model behavior prior to and during rollouts, ensuring seamless transitions without any degradation.Research & Analysis: Identify inconsistencies and potential failure modes in model outputs through meticulously designed research initiatives for both internal and production-facing systems.Cross-functional Collaboration: Work closely with design, product, and research teams to translate product objectives into specific model behavior requirements.Knowledge Sharing: Assist engineers across teams in developing a strong understanding of prompt design, context engineering, and evaluation best practices.Staying Current: Keep abreast of the latest alignment, evaluation, and prompting techniques from both industry and academia, and integrate the best ideas into the team.