This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role offers an exciting opportunity for an experienced Machine Learning Engineer to contribute to a cutting-edge platform that drives intelligent solutions for financial services. You will design, develop, and scale backend systems for predictive modeling and generative AI, collaborating closely with cross-functional teams such as LLM Engineers, Product Owners, and Data Scientists. The position involves ownership of end-to-end software development, from architecture and coding to deployment and ongoing operations. You will help define and implement robust data strategies, enhance AI capabilities, and maintain high-performance, secure production systems. This role is ideal for a hands-on engineer who thrives in a collaborative, fast-paced environment and is eager to work on technologies that directly impact user experience and business outcomes. - Design, implement, and maintain scalable, high-performance backend services, primarily in Python and frameworks like FastAPI. - Translate business and technical requirements into actionable software designs and tasks. - Develop and optimize databases, manage schema changes, and improve query performance. - Integrate internal and external services, including APIs and AWS infrastructure, ensuring secure data flow. - Operate, monitor, and maintain production systems, ensuring high availability and reliability. - Contribute to CI/CD pipelines, automation, and infrastructure improvements. - Design data collection pipelines and support LLM-based applications, including RAG systems and agentic technologies. - Collaborate with cross-functional teams to prototype internal tools and data exploration interfaces. Qualifications - Proven experience as a Machine Learning or Backend Engineer with strong Python development skills. - Hands-on experience with cloud platforms, particularly AWS (IAM, EKS/ECS, and core services). - Experience building and scaling production applications. - Knowledge of integrating internal and external services. - Familiarity with LLMs, RAG systems, embedding vector databases, and agentic technologies preferred. - Experience with data governance, structured data principles, and Feature Stores or ELT processes preferred. - Strong problem-solving, communication, and collaboration skills. - Ability to thrive in a fast-paced, remote-first work environment. Benefits - Fully remote role with flexibility to work from anywhere in the contiguous U.S. - Competitive salary with equity/RSU opportunities. - Medical, dental, and vision coverage with multiple plan options. - Life and AD&D insurance, short-term and long-term disability coverage. - 401(k) retirement plan. - Paid time off including vacation, sick leave, and parental leave. - Employee Assistance Program (EAP) and financial literacy mentoring. - Home office stipend and pet insurance. - Supportive, inclusive, and innovative work culture.

• Build and improve inventory demand forecasting models using ML and statistical methods. • Own ML models end-to-end: data collection → feature engineering → training → deployment → monitoring → iteration. • Develop decision systems that support inventory planning, pricing, and demand decisions. • Build and maintain data pipelines and API integrations for external and internal data sources. • Work with messy real-world data to ensure model reliability through rigorous validation and testing. • Implement LLM/AI-agent workflows to translate domain logic into automated processes. • Operate independently in a small team, setting priorities, unblocking challenges, and communicating tradeoffs clearly.

• Design, implement, and optimize agentic AI components, including tools, memory management, and prompts. • Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale. • Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability. • Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights. • Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes. • Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement. • Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role is a senior technical position within a high-impact Ads Marketplace team, responsible for shaping and optimizing the auction and pricing mechanisms that drive ad performance and revenue. You will apply machine learning expertise to improve marketplace efficiency, enhance user experience, and maximize advertiser value. The position requires deep knowledge of ad-tech, large-scale data systems, and end-to-end ML workflows, from feature engineering to model deployment. You will influence technical strategy, lead cross-functional initiatives, and mentor engineers while driving measurable impact across the ad ecosystem. This role offers the opportunity to innovate on high-visibility projects and help define the future of a sophisticated advertising platform. - Lead the strategy, planning, and execution of initiatives focused on ads marketplace, auction, and pricing optimization. - Analyze marketplace dynamics and design algorithms to improve efficiency, relevance, and fairness for all participants. - Oversee end-to-end machine learning workflows, including data ingestion, feature engineering, model training, evaluation, and deployment. - Provide technical leadership and mentorship to both junior and senior engineers, fostering innovation and knowledge sharing. - Collaborate with cross-functional teams such as product, data science, and business stakeholders to align on long-term vision and deliver impactful solutions. - Drive architectural decisions and maintain high standards for code quality, scalability, and performance. Qualifications - 8+ years of experience in industry-level product development, with at least 5+ years focused on large-scale, data-driven marketplace optimization. - Strong expertise in ad marketplace dynamics, auction design, and pricing mechanism optimization. - Proficiency with machine learning frameworks (TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference. - Experience with large-scale data processing and distributed computing systems (e.g., Spark, Kafka, Beam, Flink). - Solid programming skills in Java, Python, Golang, C++, or similar languages. - Demonstrated technical leadership in cross-functional settings, with strong communication, mentoring, and collaboration abilities. - Ability to influence stakeholders and execute on long-term technical and business strategies. Benefits - Competitive base salary ($230,000–$322,000 USD) plus eligibility for equity and potential commission. - Comprehensive medical, dental, and vision insurance. - 401(k) program with employer match. - Flexible vacation, paid parental leave, and global wellness days. - Home office support and personal/professional development funds. - Paid volunteer time off and family planning support.