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Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. We're looking for a Staff Machine Learning Engineer to lead our Generative AI efforts. This is a rare opportunity to shape the future of manufacturing by applying cutting-edge AI research to real-world problems: from multimodal document understanding, to extracting structured data from technical drawings, to building new ways of reasoning across text, images, and 3D data. If you're passionate about building state-of-the-art AI systems and want to see your work have immediate business and customer impact, we'd love to talk. What You'll Do Lead with vision - Set the technical direction for our Generative AI team, establish best practices, and inspire high-impact innovation. Drive strategy - Help shape the AI roadmap, identifying the most valuable opportunities to apply generative AI across Xometry's marketplace. Build cutting-edge models - Develop and deploy large language and generative models for multimodal document processing and structured data extraction. Innovate across modalities - Explore new ways to combine text, images, and 3D data to unlock smarter, faster solutions. Engineer at scale - Create data pipelines and training workflows that can handle massive, complex datasets. Deploy in the cloud - Use AWS and other platforms to train, optimize, and deploy models into production at scale. Collaborate widely - Work with engineers, product leaders, and business teams to bring AI solutions into real products and customer workflows. Mentor and grow - Guide teammates on advanced ML methods, model architecture, and best practices, elevating the entire team. Stay ahead - Keep up with the latest generative AI and deep learning research, and bring fresh ideas into production. What We're Looking For Bachelor's degree required; advanced degree (M.S. or PhD) in Computer Science, Machine Learning, AI, or related field is a big plus. 5+ years of experience in machine learning or data science, with deep expertise in generative models, LLMs, or computer vision. Strong track record working with large-scale language and vision models (Transformers, GPT, VLMs). Hands-on experience with multimodal data (text, images, 3D). Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy). Solid grounding in probability, statistics, and optimization for generative modeling. Experience deploying ML and AI models using cloud microservice architecture (AWS preferred). Strong software engineering skills, including object oriented programming, testing, version control, CI/CD best practices and IaC (terraform preferred). A proven ability to communicate effectively with all levels of the organization, from executives to product managers and various stakeholders. Background in manufacturing, supply chain, or related industries is a plus - but curiosity and drive matter more. Must be a U.S. Citizen or Green Card holder (ITAR compliance) Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Machine Learning Engineer role at PitchBook Get AI-powered advice on this job and more exclusive features. At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We're deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company. Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there's going to be some ambiguity along the way, but we excel when we challenge ourselves. We're willing to take risks, fail fast, and do it all over again in the pursuit of excellence. If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you. About the Role As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation. We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands on approach to designing, building, and optimizing ML solutions that power user facing features on the PitchBook Platform. You will be deeply involved in the end to end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy. Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources and applying ML to enrich our datasets with predictive and generative intelligence. Primary Job Responsibilities Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities. Provide hands on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high performance systems that meet production grade reliability and efficiency standards. Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best practices. Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams. Collaborate with engineering, product management, and data collection teams to ensure models are informed by high quality data and support strategic product goals. Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook's AI capabilities. Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects. Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge sharing practices. Apply principles from Agile, Lean, and Fast Flow methodologies to support efficient model development and deployment cycles. Support the vision and values of the company through role modeling and encouraging desired behaviors. Participate in various company initiatives and projects as requested. Skills and Qualifications Bachelor's degree in Computer Science, Mathematics, Data Science, or related technical field; advanced degrees are preferred. 2+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction. Demonstrated expertise in natural language processing (NLP) and machine learning, including hands on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch. Experience delivering production grade GenAI or LLM based systems with measurable business impact. Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus. Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake. Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus. Practical experience with cloud native development, containerization, and orchestration technologies such as Docker and Kubernetes. Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high performance, reliable solutions. Excellent communication and collaboration skills, with experience working cross functionally with product managers, engineers, and data scientists in globally distributed teams. Experience working in fast paced, data driven environments. Prior exposure to fintech or financial data platforms is a strong advantage. Experience authoring research papers for peer reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred. Must be authorized to work in the United States without the need for visa sponsorship now or in the future. Benefits + Compensation at PitchBook Physical Health Comprehensive health benefits Additional medical wellness incentives STD, LTD, AD&D, and life insurance Emotional Health Paid sabbatical program after four years Paid family and paternity leave Annual educational stipend Ability to apply for tuition reimbursement CFA exam stipend Robust training programs on industry and soft skills Employee assistance program Generous allotment of vacation days, sick days, and volunteer days Social Health Matching gifts program Employee resource groups Subsidized emergency childcare Dependent Care FSA Company wide events Employee referral bonus program Quarterly team building events Financial Health 401k match Shared ownership employee stock program Monthly transportation stipend Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment. Compensation Annual base salary: $125,000-$180,000 Target annual bonus percentage: 10% Working Conditions Our culture is built on spontaneous moments-those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices-that simply can't be replicated remotely. This role is expected to be in the office 5 days a week. The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events. Life At PB We are consistently recognized as a Best Place to Work and our culture is at the heart of our success. It's our fundamental belief that people do and create great things and that people are the cornerstone of prosperity. We believe that proactively seeking out different points of view, listening to others, learning . click apply for full job details

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you. Every mile driven by a Waymo car is a unique and valuable piece of data that can be leveraged into improving our machine learning models, and ultimately the safety and capabilities of the Waymo Driver. Charting the path from collection of a piece of data, to curation, (auto labeling), model training and evaluation, all the way to model deployment and monitoring is a process of continuous scaling and quality improvement of the entire ML lifecycle. The Area Technical Lead for the Waymo machine learning flywheel is responsible for architecting, connecting, automating and improving the entire span of this self improvement process in close collaboration with Waymo's infrastructure, modeling and evaluation teams. They are directly accountable to Waymo's leadership for the organization's ML data strategy and its impact on Driver quality. You will report directly to our Distinguished Engineer, Foundation Models. You Will: Architect a path towards every autonomous mile driven by a Waymo car to be automatically incorporated into an automated data driven self improvement loop for the Waymo Driver. Enable a data flywheel to serve the demands of scalable pre training, post training targeted to relevant critical behaviors, as well as Driver simulation and validation. Enable a modeling flywheel to efficiently consume that data to reliably generate updated models that are validated and deployable with minimal human toil. Coordinate cross functional efforts in partnership with data and ML infrastructure teams, resource planning, logging infrastructure, modeling and validation teams to accelerate the velocity, impact and leverage of driving data on the Waymo Driver. Act as the steward of data quality, by providing tooling and metrics to evaluate the impact of mining, selection and curation on the modeling pipeline performance. Articulate the strategy for incorporating diverse data sources, including third party and synthetic data into that improvement flywheel. Drive innovation across all axes of performance and efficiency, from Driver quality, to scalability, cost, engineering velocity, model architecture and performance. You Have: Master's degree or PhD in Computer Science, Engineering, or a related technical field 10+ years of experience in ML model development, and you have 2+ years experience with large scale vision, video, or multi modal foundation model development and their integration in end to end models 6+ years of experience in ML driven production systems that develops models with large scale data, training, evaluation, and deployment 6+ years of experience in a technical leadership role leading technical teams and setting technical directions in large ML Engineering organizations Demonstrated expertise in large scale machine learning and its key components: pre training, post training, and validation. Deep understanding of both infrastructure and quality aspects. Track record of architecting and standing up a machine learning flywheel at scale for mission critical applications. Experience with driving model quality improvements through systematic data scaling and curation. Communication and interpersonal skills. Ability to inspire, influence and coordinate across functions and disciplines. We Prefer: PhD in computer science. Experience in multi modal LLM model development, and their infrastructure. Familiarity with multi task, end to end models and their development challenges. The expected base salary range for this full time position across US locations is listed below. Actual starting pay will be based on job related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $332,000 - $421,000 USD

Azumo is currently looking for a highly motivated Data Scientist / Machine Learning Engineer to develop and enhance our data and analytics infrastructure. The position is FULLY REMOTE, based in Latin America. Professional English proficiency (B2/C1). This position will provide you with the opportunity to collaborate with a dynamic team and talented data scientists in the field of big data analytics and applied AI. If you have a passion for designing and implementing advanced machine learning and deep learning models, particularly in the Generative AI space, this role is perfect for you. We are seeking a skilled professional with expertise in Python for production level projects, proficiency in machine learning and deep learning techniques such as CNNs and Transformers, and hands on experience working with PyTorch. We're looking for a versatile Machine Learning Engineer / Data Scientist to join our big data analytics team. In this hybrid role you'll not only design and prototype novel ML/DL models, but also productionize them end to end, integrating your solutions into our data pipelines and services. You'll work closely with data engineers, software developers and product owners to ensure high quality, scalable, maintainable systems. Key Responsibilities Model Development & Productionization Design, train, and validate supervised and unsupervised models (e.g., anomaly detection, classification, forecasting). Architect and implement deep learning solutions (CNNs, Transformers) with PyTorch. Develop and fine tune Large Language Models (LLMs) and build LLM driven applications. Implement Retrieval Augmented Generation (RAG) pipelines and integrate with vector databases. Build robust pipelines to deploy models at scale (Docker, Kubernetes, CI/CD). Data Engineering & MLOps Ingest, clean and transform large datasets using libraries like pandas, NumPy, and Spark. Automate training and serving workflows with Airflow or similar orchestration tools. Monitor model performance in production; iterate on drift detection and retraining strategies. Implement LLMOps practices for automated testing, evaluation, and monitoring of LLMs. Software Development Best Practices Write production grade Python code following SOLID principles, unit tests and code reviews. Collaborate in Agile (Scrum) ceremonies; track work in JIRA. Document architecture and workflows using PlantUML or comparable tools. Cross Functional Collaboration Communicate analysis, design and results clearly in English. Partner with DevOps, data engineering and product teams to align on requirements and SLAs. About Azumo Based in San Francisco, California, Azumo is an innovative software development firm specializing in AI software development services. We help companies of all sizes build intelligent applications by combining expertise in data, cloud, and AI. Our talented AI developers are trusted to deliver Top AI Development services in Generative AI, intelligent automation, and custom machine learning solutions. At Azumo, we believe in professional and personal growth. As a recognized AI Development company, we support our engineers in mastering the latest technologies and delivering Top AI Development services worldwide. Our culture emphasizes collaboration, continuous learning, and solving complex problems with modern AI solutions. We believe in giving back to our community and will volunteer our time to philanthropy, open source initiatives and sharing our knowledge. If you are qualified for the opportunity and looking for a challenge please apply online at Azumo/join our team or connect with us at . Requirements Minimum Qualifications Bachelor's or Master's in Computer Science, Data Science or related field. 5+ years of professional experience with Python in production environments. Solid background in machine learning & deep learning (CNNs, Transformers, LLMs). Hands on experience with PyTorch or similar frameworks (training, custom modules, optimization). Proven track record deploying ML solutions. Expert in pandas, NumPy and scikit learn. Familiarity with Agile/Scrum practices and tooling (JIRA, Confluence). Strong foundation in statistics and experimental design. Excellent written and spoken English. Preferred Qualifications Experience with cloud platforms (AWS, GCP, or Azure) and their AI specific services like Amazon SageMaker, Google Vertex AI, or Azure Machine Learning. Familiarity with big data ecosystems (Spark, Hadoop). Practice in CI/CD & container orchestration (Jenkins/GitLab CI, Docker, Kubernetes). Exposure to MLOps/LLMOps tools (MLflow, Kubeflow, TFX). Experience with Large Language Models, Generative AI, prompt engineering, and RAG pipelines. Hands on experience with vector databases (e.g., Pinecone, FAISS). Experience building AI Agents and using frameworks like Hugging Face Transformers, LangChain or LangGraph. Documentation skills using PlantUML or similar. Benefits Paid time off (PTO) U.S. Holidays Training Udemy free Premium access Mentored career development Profit Sharing $US Remuneration

Overview Data Science contributes to Cardinal Health within the Data & Analytics Function, which oversees the analytics life-cycle to identify, analyze and present insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. Data Science applies base scientific methodologies from various disciplines, techniques and tools to extract knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems. At Cardinal Health's Artificial Intelligence Center of Excellence (AI CoE), we are pushing the boundaries of healthcare with cutting-edge Data Science and AI. Our mission is to leverage data to create innovative solutions that improve patient outcomes, streamline operations, and enhance the healthcare experience. We are seeking a highly motivated and experienced Senior Data Scientist to join our team as a thought leader and architect of our AI strategy. You will play a critical role in fulfilling our vision through delivery of impactful solutions that drive real-world change. Responsibilities Lead the Development of Innovative AI solutions: design, implement, and scale sophisticated AI solutions that address key business challenges within healthcare by leveraging areas such as Machine Learning, Generative AI, and RAG Technologies. Develop advanced ML models for forecasting, classification, risk prediction, and other critical applications. Explore and leverage Generative AI (GenAI) technologies, including Large Language Models (LLMs), for applications like summarization, generation, classification and extraction. Build robust Retrieval Augmented Generation (RAG) systems to integrate LLMs with vast repositories of healthcare and business data, ensuring accurate outputs. Shape Our AI Strategy: Work with stakeholders across the organization to understand needs and translate them into actionable AI-driven or AI-powered solutions. Act as a champion for AI within Cardinal Health, influencing the technology roadmap and aligning with business objectives. Guide and mentor a team of Data Scientists and ML Engineers by providing technical guidance, mentorship, and support to a distributed team, fostering a collaborative and innovative environment. Embrace an AI-Driven Culture: promote data-driven decision-making and use AI insights to drive business outcomes and improve customer experience and patient care. Qualifications 8-12 years of experience with a minimum of 4 years in data science, with a strong track record of success in developing and deploying complex AI/ML solutions, preferred Bachelor's degree in related field, or equivalent work experience, preferred GenAI Proficiency: Deep understanding of Generative AI concepts, including LLMs, RAG technologies, embedding models, prompting techniques, and vector databases, along with evaluating retrievals from RAGs and GenAI models without ground truth Experience building production-ready Generative AI Applications involving RAGs, LLMs, vector databases and embeddings models. Extensive knowledge of healthcare data, including clinical data, patient demographics, and claims data. Understanding of HIPAA and other relevant regulations, preferred. Experience with cloud platforms like Google Cloud Platform (GCP) for data processing, model training, evaluation, monitoring, deployment and support, preferred. Proven ability to lead data science projects, mentor colleagues, and effectively communicate complex technical concepts to both technical and non-technical audiences, preferred. Proficiency in Python, statistical programming languages, ML libraries (Scikit-learn, TensorFlow, PyTorch), cloud platforms, and data engineering tools, preferred. Experience in Cloud Functions, Vertex AI, MLFlow, Storage Buckets, IAM Principles and Service Accounts, preferred. Experience building end-to-end ML pipelines from data ingestion and feature engineering to model training, deployment, and scaling, preferred. Experience implementing CI/CD pipelines for ML models and other solutions, ensuring seamless production deployment, preferred. Familiarity with RESTful API design and implementation, including building APIs to integrate ML models and GenAI solutions with existing systems, preferred. Understanding of software engineering patterns, solutions architecture, information architecture, and security architecture with emphasis on ML/GenAI, preferred. Experience in Agile development environments (Scrum or Kanban) and strong understanding of Agile principles, preferred. Familiarity with DevSecOps principles and practices, incorporating coding standards and security into the development lifecycle, preferred. What is expected of you and others at this level Applies advanced knowledge to manage a wide variety of projects Participates in developing policies and procedures to achieve goals Recommends new practices, processes, metrics, or models Works on or may lead complex projects of large scope Projects may have significant and long-term impact Provides solutions that may set precedent Independently determines methods for completion of new projects Receives guidance on overall project objectives Acts as a mentor to less experienced colleagues Anticipated salary range: $121,600 - $173,700 Bonus eligible: Yes Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being. Medical, dental and vision coverage Paid time off plan Health savings account (HSA) 401k savings plan Access to wages before pay day with myFlexPay Flexible spending accounts (FSAs) Short- and long-term disability coverage Work-Life resources Paid parental leave Healthy lifestyle programs Application window anticipated to close: 11/05/2025 If interested in opportunity, please submit application as soon as possible. The salary range listed is an estimate. Pay at Cardinal Health is determined by factors including geographical location, relevant education, experience and skills and an evaluation of internal pay equity. Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply. Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law. To read and review this privacy notice click here ()

Overview Let's face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. You'll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you've ever met (each with their own personal BetterUp Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it's not for everyone. But for people with fire in their belly, it's a game-changing, career-defining, soul-lifting move. Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture. If that sounds exciting-and the job description below feels like a fit-we really should start talking. AI is transforming the future of coaching-and BetterUp is at the forefront of that transformation. We're seeking a creative, product-minded machine learning engineer who's eager to roll up their sleeves and help shape what comes next alongside our world-class team. The ideal candidate is motivated by impact, thrives in fast-paced and ambiguous environments, and brings clarity where there's complexity. You're someone who values empowering your teammates as much as your own growth, and who stays focused on what matters most: delivering meaningful, human-centered value to our members and customers. At BetterUp, we support and challenge one another to grow, always with empathy and excellence. We're looking for someone who shares our commitment to continuous learning, who takes pride in craftspersonship, and who believes deeply in the power of technology to drive positive change in the world. And because we know peak performance comes from balance, we foster a culture that supports you in bringing your full self to our mission. We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Arlington, VA metro area. Please ensure you can realistically commit to this structure before applying. What You'll Do Design and deliver state-of-the-art Generative AI systems and experiences that set the standard for quality, engagement, and trust in coaching. Mentor and elevate engineers at all levels through technical guidance, code and design reviews, and thought partnership, raising the bar for engineering excellence. Collaborate deeply with cross-functional partners across product, research, design, and engineering, to ship and scale first-of-their-kind AI coaching products. Shape direction and scope by developing a deep understanding of customer needs and translating them into technical strategy and product roadmaps. Stay ahead of the curve in Generative AI research and practice, leading conversations on emerging technologies and how to responsibly bring them into production. Qualifications 7+ years as an ML engineer and 3+ years of hands-on experience building and shipping products on top of leading LLMs Proven track record designing, implementing, and evaluating LLM outputs Experience fine-tuning smaller models or adapting foundation models to improve quality, engagement, and scalability Background at a leading AI research lab or equivalent experience staying at the forefront of Applied ML/AI, GenAI, with strong software engineering skills and a deep understanding of LLM internals A high degree of initiative and ownership, combined with the ability to navigate ambiguity and adapt quickly to change Experience working collaboratively in a cross-functional team and with people at all levels in an organization Alignment with BetterUp's mission of enabling individuals to maximize their potential Ability to communicate complex ideas effectively to both technical and non-technical audiences, verbally and in writing A passion for continuous learning, customer empathy, and a desire to innovate within a fast-paced environment. AI at BetterUp Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology - people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you'll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. Benefits At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community. Access to BetterUp coaching; one for you and one for a friend or family member A competitive compensation plan with opportunity for advancement Medical, dental, and vision insurance Flexible paid time off Per year: All federal/statutory holidays observed 4 BetterUp Inner Workdays 5 Volunteer Days to give back Learning and Development stipend Company wide Summer & Winter breaks Year-round charitable contribution of your choice on behalf of BetterUp 401(k) self contribution We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don't hesitate to reach out - we encourage everyone interested in joining us to apply. BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. The base salary range for this role is as follows: New York City and San Francisco: $228,000 - $313,500 Austin, Arlington, and Chicago: $205,200 - $282,150 Protecting your privacy and treating your personal information with care is very important to us, and central to the entire BetterUp family. By submitting your application, you acknowledge that your personal information will be processed in accordance with our Applicant Privacy Notice. If you have any questions about the privacy of your personal information or your rights with regards to your personal information, please reach out to

About Quizlet At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. Our $1B+ learning platform serves tens of millions of students every month, including two thirds of U.S. high schoolers and half of U.S. college students, powering over 2 billion learning interactions monthly. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We're energized by the potential to power more learners through multiple approaches and various tools. Let's Build the Future of Learning Join us to design and deliver AI powered learning tools that scale across the world and unlock human potential. About The Team The Personalization & Recommendations ML Engineering team builds the core intelligence behind how Quizlet matches learners with content, activities and experiences that best fit their goals. We power recommendation and search systems across multiple surfaces, from home feed and search results to adaptive study modes. Our mission is to make Quizlet feel uniquely tailored for every learner by combining cutting edge machine learning, scalable infrastructure and insights from learning science. You'll collaborate closely with product managers, data scientists, platform engineers and fellow ML engineers to deliver personalized learning pathways that drive engagement, satisfaction and measurable learning outcomes. About The Role As a Senior or Staff Machine Learning Engineer on the Personalization & Recommendations team, you'll design and build large scale retrieval, ranking, and recommendation systems that directly shape how learners discover and engage with Quizlet. You'll bring deep expertise in modern recommender systems - from deep learning based retrieval and embeddings to multi task ranking and evaluation - and help evolve Quizlet's personalization stack to power adaptive, effective learning experiences. You'll work at the intersection of machine learning, product design, and scalable systems, ensuring our recommendations are performant, responsible, and aligned with learner outcomes, privacy, and fairness. This is an onsite position in our San Francisco office; employees are required to work in the office at least three days per week (Monday, Wednesday, and Thursday). In This Role, You Will Design and implement personalization models across candidate retrieval, ranking, and post ranking layers, leveraging user embeddings, contextual signals, and content features. Develop scalable retrieval and serving systems using architectures such as Two Tower, deep ranking, and ANN based vector search for real time personalization across surfaces. Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training serving consistency, and robust monitoring. Partner closely with Product and Data Science to translate learner objectives (engagement, retention, mastery) into measurable modeling goals and experimentation plans. Advance evaluation methodologies, refining offline metrics (e.g., NDCG, CTR, calibration) and supporting rigorous A/B testing to measure learner and business impact. Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost at scale. Contribute to the long term technical vision for personalization and recommendations, aligning modeling strategy with Quizlet's AI and product roadmaps. Stay current with RecSys research and industry trends, bringing relevant advances from top conferences (KDD, WSDM, SIGIR, RecSys, NeurIPS) into production. Mentor other engineers and applied scientists, fostering technical growth, experimentation rigor, and responsible ML practices. Champion collaboration, inclusion, and curiosity, helping build a team culture that values diverse perspectives and data driven problem solving. What You Bring To The Table 10+ years of experience in applied machine learning or ML heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems. Track record of measurable impact, improving key online metrics such as CTR, retention, or engagement through recommender or search systems in production. Strong hands on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices - including model registries, feature stores, monitoring, and drift detection. Deep understanding of retrieval and ranking architectures, including Two Tower models, deep cross networks, Transformers, or MMoE, and how to apply them in production contexts. Experience with large scale embedding models and vector search (e.g., FAISS, ScaNN), including training, serving, and optimization at scale. Proficiency in experiment design and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B test results to drive product decisions. Ability to communicate complex technical ideas clearly, collaborating effectively with product managers, data scientists, and engineers across teams. Growth and mentorship mindset, contributing to team learning and helping raise the bar for modeling quality, experimentation, and reliability. Commitment to responsible and inclusive personalization, ensuring our ML systems respect learner privacy, fairness, and diverse goals. Bonus Points If You Have Publications or open source contributions in RecSys, search, or ranking. Familiarity with reinforcement learning for recommendations or contextual bandits. Experience with hybrid RecSys systems blending collaborative filtering, content understanding, and LLM based reasoning. Prior work in consumer or EdTech applications with personalization at scale. Compensation, Benefits & Perks Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a starting base salary of $209,920 - $285,000, depending on location and experience, as well as company stock options. Collaborate with your manager and team to create a healthy work life balance. 20 vacation days that we expect you to take! Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice). Employer sponsored 401k plan with company match. Access to LinkedIn Learning and other resources to support professional growth. Paid Family Leave, FSA, HSA, commuter benefits, and wellness benefits. 40 hours of annual paid time off to participate in volunteer programs of choice. Why Join Quizlet • Massive reach: 60M+ users, 1B+ interactions per week • Cutting edge tech: Generative AI, adaptive learning, cognitive science • Strong momentum: Top tier investors, sustainable business, real traction • Mission first: Work that makes a difference in people's lives • Inclusive culture: Committed to equity, diversity, and belonging We strive to make everyone feel comfortable and welcome! We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are! In Closing At Quizlet, we're excited about passionate people joining our team-even if you don't check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together. Quizlet's success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us!

Get AI-powered advice on this job and more exclusive features. Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer's B2B risk solutions & identity graph network leverage state & federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses. About You: You want to learn from the best of the best, get your hands dirty, and put in the work to hit your full potential. You're not just doing it for the win-you're doing it because you have something to prove and want to be great. You are looking to be an impeccable machine learning engineer working on cutting-edge AI solutions. You have 1-3 years of experience in machine learning development, working with Python and building ML models You're comfortable working with large-scale data and enjoy optimizing performance for computationally intensive ML systems You have a strong foundation in AI/ML fundamentals, particularly with LLMs, and are eager to experiment with emerging techniques You prioritize responsible AI practices and model governance, especially in regulated environments like KYC/KYB You have a keen eye for detail and take pride in writing clean, maintainable code while optimizing for model performance You thrive in a high-trust, ownership-focused environment and are comfortable working across different levels of abstraction Problem-solver who navigates the unknown confidently Proactive self-starter who thrives in dynamic settings Incredibly intelligent and clever. You take pride in your models Highly feedback-oriented. We believe in radical candor and using feedback to get to the next level Responsibilities Model Development & Integration: Build and maintain ML models and integrate them with various data sources, ensuring scalability, high performance, and adaptability for autonomous agents in the GTM space ML System Design: Architect and design core ML services that support KYC/KYB processes, leveraging knowledge graphs and LLMs for dynamic use cases Data Processing & Feature Engineering: Develop and maintain robust data pipelines for feature extraction and transformation, focusing on scalability and performance when handling large-scale, high-dimensional data Advanced ML Techniques: Implement and experiment with state-of-the-art techniques including reinforcement learning from human feedback (RLHF) and parameter-efficient fine-tuning methods (e.g., LoRA) to improve LLMs for specific use cases within the identity space ML Infrastructure: Build and maintain infrastructure for model training, evaluation, and deployment, creating a scalable platform foundation for continued innovation Model Governance & Compliance: Ensure ML systems meet industry standards for fairness, explainability, and compliance, particularly around KYC/KYB regulations Performance Optimization: Implement optimizations for model inference and training, ensuring ML services can efficiently process identity data while maintaining reliability Experimentation & Evaluation: Design and conduct experiments to evaluate model performance, debug issues, and monitor ML services, while continuously improving architectures to handle diverse data and use cases Hybrid in SF. In office 3 days/week Flexible PTO Smart, genuine, ambitious team Salary Range: $150k - $225k + Equity - 0.05% - 0.25% Seniority level Entry level Employment type Full-time Job function Engineering and Information Technology Industries Technology, Information and Internet Referrals increase your chances of interviewing at Baselayer by 2x.

Overview At Scale AI, our mission is to accelerate the development of AI applications. Scale is a leading AI data foundry, enabling data capabilities for generative AI, defense applications, and autonomous vehicles. We are building on our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world's most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce supports how humanity will interact with AI. Our Approach As part of the interview process, you'll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. These teams power Scale's AI data operations-from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through trusted safety and security measures. Responsibilities Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your users are your neighbors) to identify bottlenecks and ship fast, pragmatic solutions Own core systems critical to our contributor platform, with direct impact on Scale's GenAI data pipeline and business outcomes Architect and scale infrastructure capable of handling millions of tasks per week with high reliability and low latency Partner cross-functionally with ML teams, Forward Deployed Engineers, and Product to ensure data quality and operational excellence Contribute to a strong engineering culture while setting best practices for teammates through mentorship, code reviews, and process improvements Requirements 5+ years of software engineering experience, ideally in high-growth, product-focused environments Proven track record of shipping production systems at scale Drive reliability and performance across critical infrastructure systems, ensuring our platforms scale predictably and operate with high availability Strong technical depth in one or more areas: front-end frameworks, distributed systems, data infrastructure, or developer tooling Experience working across the stack, ideally with React, TypeScript, Node.js, Python, MongoDB, Elasticsearch, and/or Temporal Strong product sense and ability to translate ambiguous problems into technical solutions Comfortable working in a fast-paced, high-ownership environment with a bias toward execution Excited to join a dynamic hybrid team based in San Francisco or New York City Compensation and Benefits Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The salary range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and other factors, including job-related skills, experience, interview performance, and education or training. Eligible employees are granted equity-based compensation, subject to Board approval. Recruiters can share the specific salary range for your location during the hiring process, and confirm whether the role is eligible for equity. Benefits include comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may be eligible for additional benefits such as a commuter stipend. Location and Notice Please reference the job posting's subtitle for the location. For pay transparency, the base salary range for this full-time position in San Francisco, New York, and Seattle is: $216,200 - $270,250 USD. Equal Opportunity and Accessibility Scale AI is an equal opportunity employer. We provide reasonable accommodations to qualified applicants and employees. If you need assistance during the application or recruiting process, please contact . We comply with applicable equal employment opportunity laws and disclosure requirements where applicable.

Overview At Scale AI, our mission is to accelerate the development of AI applications. Scale is a leading AI data foundry, enabling data capabilities for generative AI, defense applications, and autonomous vehicles. We are building on our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world's most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce supports how humanity will interact with AI. Our Approach As part of the interview process, you'll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. These teams power Scale's AI data operations-from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through trusted safety and security measures. Responsibilities Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your users are your neighbors) to identify bottlenecks and ship fast, pragmatic solutions Own core systems critical to our contributor platform, with direct impact on Scale's GenAI data pipeline and business outcomes Architect and scale infrastructure capable of handling millions of tasks per week with high reliability and low latency Partner cross-functionally with ML teams, Forward Deployed Engineers, and Product to ensure data quality and operational excellence Contribute to a strong engineering culture while setting best practices for teammates through mentorship, code reviews, and process improvements Requirements 5+ years of software engineering experience, ideally in high-growth, product-focused environments Proven track record of shipping production systems at scale Drive reliability and performance across critical infrastructure systems, ensuring our platforms scale predictably and operate with high availability Strong technical depth in one or more areas: front-end frameworks, distributed systems, data infrastructure, or developer tooling Experience working across the stack, ideally with React, TypeScript, Node.js, Python, MongoDB, Elasticsearch, and/or Temporal Strong product sense and ability to translate ambiguous problems into technical solutions Comfortable working in a fast-paced, high-ownership environment with a bias toward execution Excited to join a dynamic hybrid team based in San Francisco or New York City Compensation and Benefits Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The salary range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and other factors, including job-related skills, experience, interview performance, and education or training. Eligible employees are granted equity-based compensation, subject to Board approval. Recruiters can share the specific salary range for your location during the hiring process, and confirm whether the role is eligible for equity. Benefits include comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may be eligible for additional benefits such as a commuter stipend. Location and Notice Please reference the job posting's subtitle for the location. For pay transparency, the base salary range for this full-time position in San Francisco, New York, and Seattle is: $216,200 - $270,250 USD. Equal Opportunity and Accessibility Scale AI is an equal opportunity employer. We provide reasonable accommodations to qualified applicants and employees. If you need assistance during the application or recruiting process, please contact . We comply with applicable equal employment opportunity laws and disclosure requirements where applicable.

Genies is an avatar technology company powering the next era of interactive digital identity through Smart Avatars. With the Avatar Framework and intuitive creation tools, Genies enables developers, talent, and creators to generate and deploy game-ready Smart AI companions. The company's technology stack supports full customization, AI-generated fashion and props, and seamless integration of user-generated content (UGC). Backed by investors including Bob Iger, Silver Lake, BOND, and NEA, Genies' mission is to become the visual and interactive layer for the LLM-powered internet. Genies is seeking a Lead Full Stack Engineer to guide the technical direction, architecture, and execution of our avatar-driven digital products. You'll be a player-coach, leading by example as a hands-on contributor while mentoring a team of talented engineers. Reporting directly to the Developer Platform Engineering Manager, you'll drive technical excellence, promote engineering best practices, and ensure scalable, performant solutions across the stack. This is a high-impact role for an engineer who thrives on mentorship, system design, and building cohesive teams that deliver complex, user-facing systems blending AI, game technology, and UGC creation tools. What You'll be Doing: Technical Leadership: Define and own the architectural vision and implementation strategy for full-stack systems supporting Genies' Smart Avatar ecosystem. Establish technical standards, patterns, and scalable frameworks for both frontend and backend components. Mentorship & Team Development: Act as a player-coach for a growing team. Provide structured mentorship, code review guidance, and ongoing feedback to foster career growth and engineering excellence. Hands-on Contribution: Contribute directly to the codebase with a focus on maintainability, reliability, and performance. Prototype, iterate, and deliver features across our stack using technologies such as React, Next.js, Node, and Go. Cross-Functional Collaboration: Partner closely with product managers, designers, and other engineering teams to translate high-level goals into technical deliverables that delight users and scale gracefully. Strategic Impact: Drive initiatives that improve developer velocity, operational efficiency, and code quality across the organization. Proactively identify technical risks, scalability challenges, and long-term architectural needs. Process and Culture Building: Champion best practices in code quality, security, and performance. Help shape a culture of learning, accountability, and collaboration within the engineering org. What You Should Have: 7+ years of professional full stack development experience, including at least 2 years in a technical leadership or mentorship role. Bachelor's degree in Computer Science, related field, or equivalent practical experience. Proven ability to design and scale distributed, high-performance web applications. Expertise with modern web technologies: React, JavaScript (ES6+), TypeScript, Node.js, Next.js. Strong backend development experience with Go, Python, or similar languages. Experience building and consuming RESTful and GraphQL APIs, and familiarity with event-driven architectures. Solid understanding of cloud infrastructure (AWS) and CI/CD pipelines. Strong communication skills, with the ability to guide both technical and non-technical discussions. Demonstrated ability to balance hands-on engineering with people leadership. Bonus: Experience with real-time systems, web sockets, or multiplayer architectures. Exposure to AI/ML systems, LLM integration, or digital identity platforms. Passion for mentoring, technical strategy, and cultivating a high-performing team culture. How Genies will support you Competitive salary and equity packages Comprehensive health, dental, and vision insurance Unlimited PTO and parental leave Hybrid work structure (minimum 4 days in office weekly) Monthly wellness reimbursement Genies is a well-funded, fast-growing start-up that values innovation, creativity, and ownership. Our roles and their responsibilities are created with a breadth of scope that introduces each employee to exciting new challenges and opportunities that a growing start-up encounters. The actual base pay is dependent upon a number of factors, including: professional background, training, transferable skills, work experience, education, location, business and product needs, and market demand. The base pay range is subject to change and may be modified in the future. Starting Salary Range: $210,000 - $260,000 if annualized Here's why you'll love working at Genies: You'll lead and mentor a talented, mission-driven team while still shipping impactful code. You'll shape the technical foundation of next-gen avatar systems built for the LLM-powered internet. You'll join a startup with enterprise-level stability and visionary leadership, including seasoned operators and industry pioneers.

Genies is an avatar technology company powering the next era of interactive digital identity through Smart Avatars. With the Avatar Framework and intuitive creation tools, Genies enables developers, talent, and creators to generate and deploy game-ready Smart AI companions. The company's technology stack supports full customization, AI-generated fashion and props, and seamless integration of user-generated content (UGC). Backed by investors including Bob Iger, Silver Lake, BOND, and NEA, Genies' mission is to become the visual and interactive layer for the LLM-powered internet. Genies is seeking a Lead Full Stack Engineer to guide the technical direction, architecture, and execution of our avatar-driven digital products. You'll be a player-coach, leading by example as a hands-on contributor while mentoring a team of talented engineers. Reporting directly to the Developer Platform Engineering Manager, you'll drive technical excellence, promote engineering best practices, and ensure scalable, performant solutions across the stack. This is a high-impact role for an engineer who thrives on mentorship, system design, and building cohesive teams that deliver complex, user-facing systems blending AI, game technology, and UGC creation tools. What You'll be Doing: Technical Leadership: Define and own the architectural vision and implementation strategy for full-stack systems supporting Genies' Smart Avatar ecosystem. Establish technical standards, patterns, and scalable frameworks for both frontend and backend components. Mentorship & Team Development: Act as a player-coach for a growing team. Provide structured mentorship, code review guidance, and ongoing feedback to foster career growth and engineering excellence. Hands-on Contribution: Contribute directly to the codebase with a focus on maintainability, reliability, and performance. Prototype, iterate, and deliver features across our stack using technologies such as React, Next.js, Node, and Go. Cross-Functional Collaboration: Partner closely with product managers, designers, and other engineering teams to translate high-level goals into technical deliverables that delight users and scale gracefully. Strategic Impact: Drive initiatives that improve developer velocity, operational efficiency, and code quality across the organization. Proactively identify technical risks, scalability challenges, and long-term architectural needs. Process and Culture Building: Champion best practices in code quality, security, and performance. Help shape a culture of learning, accountability, and collaboration within the engineering org. What You Should Have: 7+ years of professional full stack development experience, including at least 2 years in a technical leadership or mentorship role. Bachelor's degree in Computer Science, related field, or equivalent practical experience. Proven ability to design and scale distributed, high-performance web applications. Expertise with modern web technologies: React, JavaScript (ES6+), TypeScript, Node.js, Next.js. Strong backend development experience with Go, Python, or similar languages. Experience building and consuming RESTful and GraphQL APIs, and familiarity with event-driven architectures. Solid understanding of cloud infrastructure (AWS) and CI/CD pipelines. Strong communication skills, with the ability to guide both technical and non-technical discussions. Demonstrated ability to balance hands-on engineering with people leadership. Bonus: Experience with real-time systems, web sockets, or multiplayer architectures. Exposure to AI/ML systems, LLM integration, or digital identity platforms. Passion for mentoring, technical strategy, and cultivating a high-performing team culture. How Genies will support you Competitive salary and equity packages Comprehensive health, dental, and vision insurance Unlimited PTO and parental leave Hybrid work structure (minimum 4 days in office weekly) Monthly wellness reimbursement Genies is a well-funded, fast-growing start-up that values innovation, creativity, and ownership. Our roles and their responsibilities are created with a breadth of scope that introduces each employee to exciting new challenges and opportunities that a growing start-up encounters. The actual base pay is dependent upon a number of factors, including: professional background, training, transferable skills, work experience, education, location, business and product needs, and market demand. The base pay range is subject to change and may be modified in the future. Starting Salary Range: $210,000 - $260,000 if annualized Here's why you'll love working at Genies: You'll lead and mentor a talented, mission-driven team while still shipping impactful code. You'll shape the technical foundation of next-gen avatar systems built for the LLM-powered internet. You'll join a startup with enterprise-level stability and visionary leadership, including seasoned operators and industry pioneers.

Discord is used by over 200 million people every month for many different reasons, but there's one thing that nearly everyone does on our platform: play video games. Over 90% of our users play games, spending a combined 1.5 billion hours playing thousands of unique titles on Discord each month. Discord plays a uniquely important role in the future of gaming. We are focused on making it easier and more fun for people to talk and hang out before, during, and after playing games. The Safety Processing team is responsible for the systems that power Discord's ability to detect, review, and enforce against harmful content at scale. We build the infrastructure and decision systems that enable accurate, efficient, and fair content moderation across all of Discord. We're looking for a Senior Software Engineer who can handle complex, multi-milestone projects and deliver high-quality systems that protect millions of users daily. As a Senior Engineer on Safety Processing, you'll take full ownership of projects from initial design through post-launch monitoring and iteration. You'll work on challenging problems at the intersection of automation, large-scale distributed systems, and content safety. You'll help build automated decision systems that scale our review capacity by 10x, develop enforcement infrastructure that handles millions of decisions per day, or architect systems that centralize and simplify safety signal processing. You'll collaborate closely with Trust & Safety operations, ML teams, Policy, and product partners to deliver solutions that make Discord safer while maintaining our commitment to user experience. You'll deliver lovable products while maintaining Discord's high quality bar, utilizing 80/20 thinking and a user centric approach. You'll embody a growth mindset, diving into new code and technologies to deliver safety solutions that protect millions of users daily. This person reports to the Engineering Manager of Safety Processing. This role offers the opportunity to work on systems that directly impact user safety, tackle novel technical challenges in content moderation at scale, and help shape the future of how Discord keeps communities safe. What You'll Be Doing: Own complex safety infrastructure projects end-to-end, from initial design through post-launch monitoring and iteration Build and maintain critical systems for automated content review, enforcement, and safety signal processing at massive scale Apply an adversarial mindset to your work, thinking through security, abuse scenarios, edge cases, and scalability concerns to protect Discord's users Collaborate with Trust & Safety, ML, Policy, and product teams to understand requirements and deliver effective safety solutions Break down complex, multi milestone projects into smaller work streams while managing stakeholders and dependencies across teams Debug and resolve issues within the team's codebase and adjacent systems, participating in on call rotations Contribute to technical design discussions and documentation, writing RFCs Help establish best practices and maintain the team's quality bar through code reviews and mentorship What You Should Have: 4+ years of professional software engineering experience with a focus on backend services and infrastructure Strong programming skills in Python Experience building and operating distributed systems and production services at scale Demonstrated ability to own projects end to end and deliver results on time Strong debugging skills and ability to navigate complex codebases Excellent collaboration skills and ability to work effectively with cross functional partners Experience working in larger engineering organizations with multiple teams and stakeholders A quality centered mindset with attention to the right details at every stage of development Demonstrated adversarial thinking - ability to anticipate misuse, edge cases, and system vulnerabilities Experience with distributed systems concepts and cloud platforms (GCP/AWS) Experience being in 24/7 on call rotations Strong collaboration and communication skills Bonus Points: Experience with content moderation, trust & safety, or related problem domains Experience with workflow automation or decision systems Experience with ML/LLM integration and prompt engineering Experience with observability tools, metrics, and monitoring systems at scale Experience with cloud platforms (GCP/AWS) A strong passion for Discord and making online communities safer Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available. The US base salary range for this full time position is $196,000 to $220,500 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits. Why Discord? Discord plays a uniquely important role in the future of gaming. We're a multiplatform, multigenerational and multiplayer platform that helps people deepen their friendships around games and shared interests. We believe games give us a way to have fun with our favorite people, whether listening to music together or grinding in competitive matches for diamond rank. Join us in our mission! Your future is just a click away! Discord is committed to inclusion and providing reasonable accommodations during the interview process. We want you to feel set up for success, so if you are in need of reasonable accommodations, please let your recruiter know. Please see our Applicant and Candidate Privacy Policy for details regarding Discord's collection and usage of personal information relating to the application and recruitment process by clicking HERE.

Machine Learning Engineer - Perception Offline Driving Intelligence at Zoox Overview The Offline Driving Intelligence (ODIN) team at Zoox is leveraging the latest in AI to craft algorithms that understand the world. We leverage large models first offline and devise a path of impact into our self driving robot, enabling safe and efficient navigation in complex environments. As an engineer in the ODIN team, you will develop advanced multimodal large language models that enhance environmental understanding. You'll develop and fine tune these models for off vehicle analysis while working with the onboard team to deliver impact in our robotaxi platform, ensuring they can efficiently identify hazards and interpret driving restrictions with minimal latency. Working alongside world class engineers and researchers, you'll leverage premium sensor data and cutting edge infrastructure to validate your algorithms in real world conditions, directly impacting productivity, safety and the capability of Zoox's autonomous system. Responsibilities Develop multimodal large language models that enhance our robotaxis' understanding of complex urban environments Implement model architectures and sophisticated training techniques Build large, high quality datasets leveraging all inputs from our sensor stack and the overall large scale data we have at Zoox Drive end to end ML solutions from research to production, utilizing Zoox's extensive data pipelines and infrastructure to improve autonomous driving capabilities Collaborate with perception, planning, safety, and systems teams to integrate your models into the vehicle's decision making pipeline Validate and optimize your solutions using real world driving scenarios, directly contributing to the safety and reliability of Zoox's autonomous system Qualifications MS or PhD in Computer Science, Machine Learning, or related technical field Demonstrated experience training and deploying large language models (LLMs) Experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluation Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects Experience training models with large scale data Bonus Qualifications Publications in top tier conferences (CVPR, ICCV, RSS, ICRA) Experience with autonomous robotics systems Compensation $179,000 - $245,000 a year Base Salary Range: There are three major components to compensation for this position-salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Benefits Zoox also offers a comprehensive package of benefits, including paid time off (e.g., sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long term care insurance, long term and short term disability insurance, and life insurance. About Zoox Zoox is developing the first ground up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility as a service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast moving and highly execution oriented team. Accommodations If you need an accommodation to participate in the application or interview process please reach out to or your assigned recruiter. A Final Note You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Join to apply for the Machine Learning Engineer role at Poesis AI. About Poesis Poesis is the AI-native investment manager pioneering a new foundation model for investing in U.S. equities. We're building modular AI systems to predict market movements and outperform legacy managers. This is frontier research with immediate real world validation. Your work will directly shape investment decisions and portfolio performance. Location & Workstyle San Francisco Bay Area (near Stanford). Hybrid: several days on site per week. Relocation available. About The Role Poesis is building an AI driven hedge fund focused on reshaping how trading decisions are made. We're hiring our Founding ML Engineer, the first full time machine learning hire who will turn research and data into production models. You'll build the first ML pipelines end to end - from ingesting and cleaning data, to model training, validation, and signal generation. This is a deeply hands on, execution oriented role for someone who can write code, design experiments, and deliver validated results quickly. You'll work directly with the CEO, CFO, and Chief Scientist, owning both implementation and iteration. Over time, you'll help scale the system into a full production platform and define best practices for future hires. Responsibilities Architect, build, and maintain the core ML infrastructure for Poesis' investment platform. Develop reproducible pipelines for data ingestion, feature generation, and model training. Implement backtesting and evaluation frameworks with clear performance metrics. Deliver regular, documented reports on model accuracy, feature importance, and portfolio level impact. Collaborate closely with the Chief Scientist to refine model hypotheses and production readiness. Maintain code quality: version control, testing, reproducibility, and documentation. Build robust backtesting frameworks and model validation tools with walk forward evaluation and risk controls. Integrate with professional financial data providers (Bloomberg, FactSet, Refinitiv, CapIQ). Establish foundational MLOps practices: model versioning, CI/CD, monitoring, and documentation. Define and iterate on "demo able" workflows that connect model outputs to investment decision makers. Required Competencies 5-10+ years of experience as an ML Engineer, Quant Engineer, or similar role. Proven track record deploying production ML systems (ideally in finance or other high stakes domains). Deep expertise in Python and ML frameworks (PyTorch, TensorFlow, scikit learn, JAX, XGBoost). Experience designing large scale, reliable data or MLOps systems. Strong software engineering fundamentals: testing, versioning, CI/CD, and code review discipline. Experience with financial data APIs and real time data handling. Comfortable working directly with executives and acting as both IC and product owner. Willingness to work in person in the Bay Area; relocation support available. Preferred Competencies Prior experience at a hedge fund, quant research lab, or fintech startup. Familiarity with quantitative finance, portfolio optimization, or risk management. Exposure to time series modeling, forecasting, or reinforcement learning. Understanding of financial market microstructure and execution systems. Experience with LLM/RAG workflows for parsing financial documents (filings, transcripts). Comfort with multi language engineering environments (C++, Rust, Go, etc.). Profile You're a founder type engineer - equally comfortable writing code, setting strategy, and defining requirements. You thrive in high autonomy, low process environments and like being close to decision makers. You think like both a researcher and a builder, able to turn models into production systems quickly. You're pragmatic: you deliver something useful fast, then refine it as data and users evolve. You want to build the technical backbone of a next generation hedge fund from day one. Current legal authorization to work in the US required; visa sponsorship considered later for full time employees.

Machine Learning Engineer (LLM) Compensation: $170,000 - $200,000+ (DOE) Location: Boston or Berkeley, flexible 2-3 days per week in office We're working a fast growing AI company on a mission to automate complex workflows in the financial services sector, starting with insurance. Their technology leverages cutting edge AI to simplify high value processes, from multi turn conversations to full workflow automation. As an ML Engineer within LLMs, you'll be building and scaling advanced AI systems that power intelligent, multi agent workflows. You'll take ownership of designing, fine tuning, and productionizing large language models, integrating them with backend systems, and optimizing their performance. You'll collaborate closely with data science, DevOps, and leadership to shape the AI infrastructure that drives the company's automation solutions. What You'll Do Build, fine tune, and productionize large language model (LLM) pipelines, including PEFT, RLHF, and DPO workflows. Develop APIs, data pipelines, and orchestration systems for multi agent, multi turn AI conversations. Integrate models with backend services, including voice orchestration platforms and transcript generation. Optimize model usage and efficiency, transitioning from external APIs to in house solutions. Collaborate cross functionally with data scientists, DevOps, and leadership to deliver scalable machine learning solutions. What We're Looking For Essential Skills & Experience Strong proficiency in Python and ML frameworks (e.g., scikit learn, TensorFlow, PyTorch). Hands on experience fine tuning and training LLMs. Experience with PEFT, DPO, Prefence Optimization, post training, supervised fine tuning, RLHF. Familiarity with AWS suite and deploying ML models to production. Ability to reason deeply about ML principles, architectures, and design choices. Knowledge of multi agent orchestration and conversational AI systems. Desirable Skills & Experience Background in voice AI, speech to text, or text to speech systems. Exposure to financial services or insurance applications. Familiarity with optimizing models for long context scenarios. For additional information or to apply, please get in touch or apply directly. Seniority level Not Applicable Employment type Full time Job function Information Technology

Overview WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence, proving it's possible with powerful, trustworthy AI that unites IT and business teams to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents grounded in their data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as a leader in enterprise generative AI. About The Role We're looking for an exceptional software engineer, generative AI to join our rapidly evolving team at WRITER. In this pivotal role, you'll be at the forefront of expanding human capacity by building the next generation of AI-powered solutions that transform how leading enterprises operate. You will develop a state-of-the-art platform that leverages cutting-edge generative AI technologies, from large language models to sophisticated agentic workflows, delivering seamless, scalable, and secure applications that redefine enterprise productivity. This is an opportunity to shape the future of AI and contribute to a product that's changing how the world works. This role is hybrid, based out of our San Francisco, New York City, or London hubs. You'll report to an engineering director or a senior engineering manager. What You'll Do Design and develop robust, scalable, and secure generative AI services and applications using Python and modern frameworks to drive enterprise-wide transformation Build and optimize high-performance, low-latency APIs and microservices for integrating advanced AI models and agentic workflows into our platform Collaborate closely with product managers, data scientists, and cross-functional engineering teams to translate complex business needs into innovative AI solutions, from concept to production Implement and maintain responsive user interfaces (primarily focused on backend enablement though some frontend interaction is expected) using technologies like React and TypeScript to deliver intuitive user experiences Partner with DevOps teams building continuous deployment, logging and monitoring; ensuring top-tier performance and reliability Own key architectural components, ensuring best practices in code quality, security, and maintainability through rigorous testing and peer reviews What You Need 3+ years of hands-on experience as a software engineer, with a strong emphasis on Python development in production environments. We are open to discussing seniority levels from Senior to Staff. Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases (e.g., Pinecone, Weaviate, pgvector), and modern open source agentic Frameworks. Deep understanding and practical experience with microservices architecture, RESTful APIs, and cloud platforms such as AWS, GCP, or Azure, including containerization with Docker and Kubernetes Solid grasp of modern web technologies including FastAPI, Asyncio, and database systems like PostgreSQL A "Connect" mindset, thriving in collaborative settings where you actively engage with cross-functional teams and mentor junior engineers to achieve shared goals A "Challenge" spirit, demonstrating exceptional problem-solving skills to tackle complex technical hurdles and proactively suggest innovative improvements to our systems and processes An "Own" attitude, taking full accountability for delivering high-quality, resilient, and scalable code from conception through to production, continuously driving performance and maintainability Benefits & Perks Generous PTO, plus company holidays Medical, dental, and vision coverage for you and your family Paid parental leave for all parents (12 weeks) Fertility and family planning support Early-detection cancer testing through Galleri Flexible spending account and dependent FSA options Health savings account for eligible plans with company contribution Annual work-life stipends for: Wellness stipend for gym, massage/chiropractor, personal training, etc. Learning and development stipend Company-wide off-sites and team off-sites Competitive compensation, company stock options and 401k WRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. By submitting your application on the application page, you acknowledge and agree to WRITER's Global Candidate Privacy Notice. Compensation Range: $119.3K - $292.4K

Machine Learning Engineer PhD (Full Time) - United States Get AI-powered advice on this job and more exclusive features. Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. Applications are accepted until further notice. Meet the Team Join our innovative engineering team focused on building next generation AI/ML solutions. You'll collaborate with skilled colleagues across platform, security, release engineering, and support teams to deliver high impact products and ensure their perfect operation. Your Impact Dive into the development and implementation of cutting edge generative AI applications using the latest large language models-think GPT 4, Claude, Llama, and beyond! Take on the challenge of optimizing neural networks for natural language processing and machine perception, drawing on a toolkit that includes convolutional and transformer based models, student teacher frameworks, distillation, and generative adversarial networks (GANs). Performance, scalability, and reliability are front and center as models are trained, fine tuned, and put through their paces for real world deployment. Collaboration is at the heart of this role-work alongside talented engineers and cross functional teams to gather and prep data, design custom layers, and automate model deployment. Experimentation with new technologies and ongoing learning are always encouraged. Production ready code, robust testing, and creative problem solving all play a part in bringing innovative AI solutions to life. What an exciting place to grow and make an impact! Minimum Qualifications Recent graduate or in your final year of studies toward a PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or a related field. 3+ years of experience in backend development using Go or Python. Understanding of LLM infrastructure and optimization, validated by technical interview responses, project documentation, or relevant publications. Hands on experience with model building and AI/LLM research, demonstrated through portfolio work, code samples, technical assessments, or documented academic or professional projects. Preferred Qualifications Experience working with inference engines (e.g., vLLM, Triton, TorchServe). Knowledge of GPU architecture and optimization. Familiarity with agent frameworks. Exposure to cloud native solutions and platforms. Experience with cybersecurity principles and Python programming, including common AI libraries. Familiarity with distributed systems and asynchronous programming models. Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. Message to applicants applying to work in the U.S. and/or Canada: Individual pay is determined by the candidate's hiring location, market conditions, job related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process. U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time. 10 paid holidays per full calendar year, plus 1 floating holiday for non exempt employees 1 paid day off for employee's birthday, paid year end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco Non exempt employees receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full time employees Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations) 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next Additional paid time away may be requested to deal with critical or emergency issues for family members Optional 10 paid days per full calendar year to volunteer Seniority Level Internship Employment Type Full time Job Function Engineering and Information Technology Industry Software Development Referrals increase your chances of interviewing at Cisco by 2x.