We create honest financial products that improve lives.
Senior Staff Machine Learning Engineer, (ML Underwriting)
Location
United States
Posted
121 days ago
Salary
$232K - $310K / year
Seniority
Senior
Job Description
Senior Staff Machine Learning Engineer, (ML Underwriting)
Affirm
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to Affirm's mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques ensuring responsible and accessible financial products. In this role, you will help shape the future of machine learning at Affirm. You’ll partner with ML Platform, engineering, product, and risk leaders to design, implement, and scale advanced modeling approaches that drive critical decisions across the company. You will elevate our modeling capabilities, influence architectural direction, and ensure our systems can support increasingly sophisticated workloads. You will mentor senior engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy. If you are passionate about modern machine learning and excited to drive high-impact innovation across a growing organization, Affirm is the place for you. What you’ll do - You will define and drive multi-year, multi-team technical strategy for machine learning across Affirm, ensuring alignment with company-wide priorities and influencing the roadmaps of partner teams and platforms. - You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads. - You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next-generation ML methods. - You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross-org guidance. - You will drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization. - You will champion operational and system excellence at the area level, owning the long-term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams. What we look for - You have 10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE. - You have experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. You use distributed frameworks such as Spark, Ray, or similar large-scale data processing systems. - You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms. - You have a strong understanding of representation learning and embedding-based modeling. You possess deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale. - You have deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining. - You provide strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces. - You demonstrate exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning. - You have strong verbal and written communication skills that support effective collaboration across our global engineering organization. - This position requires equivalent practical experience or a Bachelor’s degree in a related field. Pay Grade - R Equity Grade - 15 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT) per year: $260,000 - $310,000 USA base pay range (all other U.S. states) per year: $232,000 - $282,000 #LI Remote Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities. We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include: - Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents - Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses - Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge - ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. [For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
Benefits
- 401(K), 401(K) matching, Adoption Assistance, Childcare benefits, Commuter benefits, Company equity, Company-sponsored outings, Company sponsored family events, Continuing education stipend, Dedicated diversity and inclusion staff, Dental insurance, Disability insurance, Diversity manifesto, Volunteer in local community, Employee stock purchase plan, Family medical leave, Fitness stipend, Flexible Spending Account (FSA), Flexible work schedule, Generous parental leave, Generous PTO, Company-sponsored happy hours, Health insurance, Job training & conferences, Open door policy, Life insurance, Mentorship program, Paid volunteer time, Online course subscriptions available, Onsite gym, Open office floor plan, Paid holidays, Paid sick days, Partners with nonprofits, Performance bonus, Promote from within, Lunch and learns, Relocation assistance, Remote work program, Return-to-work program post parental leave, Free snacks and drinks, Team based strategic planning, OKR operational model, Continuing education available during work hours, Tuition reimbursement, Mandated unconscious bias training, Vision insurance, Wellness programs, Some meals provided, Mental health benefits, Home-office stipend for remote employees, Diversity employee resource groups, Hiring practices that promote diversity, Fertility benefits, Employee resource groups, Employee-led culture committees, Quarterly engagement surveys, In-person all-hands meetings, President's club, Employee awards, Diversity recruitment program, Pension, Pay transparency, Transgender health care benefits, Abortion travel benefits, Mother's room, Personal development training, Apprenticeship programs, Flexible time off, Bereavement leave benefits
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Staff Software Engineer - Machine Learning
General MotorsGeneral Motors (GM), founded in 1908 by William "Billy" Durant in Flint, Michigan, began with the Buick Motor Company and later acquired brands like Oldsmobile
Description Role: The Smart Agents group is responsible for building the ML models and system to simulate road users in a variety of situations and generate the scenarios used for testing and training AV driving policies. If you think of Simulation as a video game our autonomous vehicles train on to learn to drive, the Smart Agents team develops the ML/AI models that control the other characters in the video game to interact in realistic ways as the av drives-eg, the other vehicles, bikers, and pedestrians. Our technology stack includes Generative AI models (GPT) and Reinforcement Learning (RL) policies. The Smart Agents group work closely with the rest of the Simulation, and our partners Behaviors, Perception, and Safety Engineers. The specific duties may include ML/RL model development as well as training loop development, streamlining optimization, integration, creating ML infrastructure, metrics, and data pipelines for production model deployment as well as for fast experimentation cycles. What You'll Do: - Support the team in developing machine learning (ML) and reinforcement learning (RL) models, including training loop development and optimization. - Streamline integration and create ML infrastructure, metrics, and data pipelines for production model deployment and rapid experimentation. - Work as part of an ML team and contribute strong software engineering (SWE) expertise. - Support the ML team in accelerating project timelines, particularly in areas related to Autopilot, Lane Keep, and autonomous vehicle (AV) technologies. - Experience in simulation and robotics is highly desirable, with a preference for candidates from AV or robotics backgrounds rather than solely cloud-focused companies. Your Skills & Abilities: - 4+ years of experience in the field of robotics or latency-sensitive backend services - Background working with machine learning teams, algorithms, and models - Bonus: Experience building highly performant ML and system pipelines - Strong programming skills in modern C++ or Python Bonus: - Experience with profiling CPU and/or GPU software, process scheduling, and prioritization - Passionate about self-driving car technology and its impact on the world - Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions. - Ability to design across multiple systems. Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain. - Ability to wear several hats shifting between coding, design, technical strategy, and mentorship combined with excellent judgment on when to switch contexts to meet the greatest need. - Track record in deploying perception/prediction/av models into real world environments Your Skills & Abilities: - 4+ years of experience in the field of robotics or latency-sensitive backend services - Proven experience in machine learning and classification. Familiar with ML frameworks such as Tensorflow or PyTorch - Experience building highly performant ML and system pipelines - Strong programming skills in modern C++ or Python - Experience with profiling CPU and/or GPU software, process scheduling, and prioritization - Passionate about self-driving car technology and its impact on the world - Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions. - Ability to design across multiple systems. Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain. - Ability to wear several hats shifting between coding, design, technical strategy, and mentorship combined with excellent judgment on when to switch contexts to meet the greatest need. - Track record in deploying perception/prediction/av models into real world environments - Experience working with RL and sequence prediction (ML) models Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington. - The salary range for this role is $134,000 to $235,900. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. - Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. - Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times a week, at minimum. Relocation: This job may be eligible for relocation benefits. #GM-AV-1 GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.) This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Total Rewards | Benefits Overview From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us [email protected] or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
• Lead the design and development of ML applications across the product portfolio • Provide architecture and shape coding standards • Evangelize best practices for software engineering including design, development, and lifecycle maintenance • Partner with multiple software engineering teams to encourage practices like code reusability, shared libraries, UX-driven design • Guide the transformation of machine learning research domain expertise into viable prototypes • Enable Machine Learning Engineers to build and train new production-grade algorithms • Research and share current and emerging industry tools, techniques, and algorithms • Collaborate with stakeholders, product managers, engineering managers, data scientists, and other engineers • Understand and distill technical and business impacting variables into strategic and tactical choices • Support multiple scrum teams across the product portfolio • Work with external customers either as a consultant or as a solution Machine Learning Engineer • Prepare and submit conference and journal articles
• Design and implement ML pipelines (training, validation, deployment, and inference) with a focus on scalability and cost. • Put models into production using MLOps practices (versioning, reproducibility, automation, and performance/drift monitoring). • Build and maintain inference services (batch and/or real-time), APIs, and integrations with internal systems. • Collaborate with data scientists, analysts, and product teams to translate business needs into solutions. • Ensure quality (testing, code review, documentation), security, and engineering best practices. • Monitor operational metrics and outcomes (SLA, latency, cost, accuracy, business impact).
Afresh is the leading AI company in fresh food—partnering with grocers like Albertsons, Wakefern, Meijer, and Stater Bros to order billions of dollars of fresh food in over 12,000 grocery departments nationwide. Following record-breaking 70% growth in 2025, we’ve expanded our platform to cover all fresh departments, launched our full store suite, and debuted DC Fresh Buying. We’re on a mission to eliminate food waste and make fresh food accessible to all. In 2025 alone our software helped save 200M lbs of food waste. If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines the future of fresh, there is no better time to join us. The ML Platform Engineering team at Afresh is responsible for building and maintaining the foundational infrastructure and tooling that powers all of our machine learning and applied science solutions. We provide the shared components and services that enable our teams to develop, deploy, and scale robust ML models. This includes a performant data API, configurable featurization, reliable forecasting systems, highly parallel optimization engines, and scalable training pipelines, and deep experimentation capabilities. As our product suite and customer base grow, so does the scale and complexity of what our platform needs to support, gracefully accommodating predictions and simulations across various time scales (hours, days, weeks), complex data hierarchies (pallets on a truck, shelves of mangos in a store, chunks of fruit in a bowl), and endless configuration possibilities (average shelf fullness, backroom loads, truck capacities). About the Role As an ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability. You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact. Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States. What you will do: - In your first 3 months, you might deliver a project that helps generalize model configuration, enables no-code model deploys for our various ML solutions, or vastly improves integration testing across our ML systems. - By the end of your first 6 months, you will have owned the design and implementation of significant scalability improvements and additions to our ML platform. This might include new feature pipelines that power our recommendation engine, or work to stand up the first instance of real-time inference at Afresh. Skills and Experience - BS in Computer Science or a relevant technical field. - 4+ years of professional software development experience with a proven track record of shipping high-quality applications and services. - Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models. - Technical leadership experience and a demonstrated ability to mentor junior engineers. - Deep expertise in library design, API design, data structures, and algorithms. - Strong familiarity with Python. Salary Range in U.S. $156,000 - $211,000 Salary Range for Canada in CAD: $137,000 - $185,000 About Afresh Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices. Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals including ICML, and we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors. Fresh is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility. Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law. Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
