Build a Safer World. TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all. The AI Engineering Team is chartered with enabling next-generation AI applications, with a special focus on Large Language Models (LLMs) and agentic systems. Our mission is to build robust pipelines, high-performance infrastructure, and operational tooling that allow AI systems to be deployed with speed, safety, and scale. We manage petabyte-scale pipelines, serve models with millisecond-level latency, and provide the observability and governance needed to make AI production-ready. We’re also deeply involved in evaluating and integrating cutting-edge tools in the LLM and agent space — including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that unlock TRM’s ability to innovate faster than the market. As a Senior MLOps Engineer with a focus in LLMOps, you’ll be at the core of building and scaling the technical infrastructure for AI/ML systems. You will: - Build reusable CI/CD workflows for model training, evaluation, and deployment — integrating Langfuse, GitHub Actions, and experiment tracking, etc. - Automate model versioning, approval workflows, and compliance checks across environments. - Build out a modular and scalable AI infrastructure stack — including vector databases, feature stores, model registries, and observability tooling. - Partner with engineering and data science to embed AI models and agents into real-time applications and workflows. - Continuously evaluate and integrate state-of-the-art AI tools (e.g. LangChain, LlamaIndex, vLLM, MLflow, BentoML, etc.). - Drive AI reliability and governance, enabling experimentation while ensuring compliance, security, and uptime. - Build and enhance AI/ML Model Performance - Ensure data accuracy, consistency and reliability, leading to better model training and inferencing - Deploy infrastructure to support offline and online evaluation of LLMs and agents — including regression testing, cost monitoring, and human-in-the-loop workflows. - Enable researchers to iterate quickly by providing sandboxes, dashboards, and reproducible environments. What We’re Looking For - Write high-quality, maintainable software — primarily in Python, but we value engineering ability over language familiarity. - Have a strong background in scalable infrastructure, including: - Containerization and orchestration (e.g. Docker, Kubernetes) - Infrastructure-as-code and deployment (e.g. Terraform, CI/CD pipelines) - Monitoring and logging frameworks (e.g. Datadog, Prometheus, OpenTelemetry) - Understand and implement ML Ops best practices, including: - Model versioning and rollback strategies - Automated evaluation and drift detection - Scalable model and agent serving infrastructure (e.g. vLLM, Triton, BentoML) - Deploy and maintain LLM and agentic workflows in production, including: - Monitoring cost, latency, and performance - Capturing traces for analysis and debugging - Optimizing prompt/response flows with real-time data access - Demonstrate strong ownership and pragmatism, balancing infrastructure elegance with iterative delivery and measurable impact. Learn about TRM Speed in this position: - Rapid Issue Resolution. TRM Engineers identify and resolve critical onsite issues in minutes to hours, not weeks. We create virtual war rooms, implement fixes, and share lessons with both customer stakeholders and internal teams within 48 hours. - Navigating Bureaucracy. We anticipate and address procedural hurdles, build trust with key stakeholders, and find alternative pathways to approvals. This keeps projects moving even in complex environments. - Efficient Knowledge Transfer. Engineers document and share updates in real time, ensuring the entire team—onsite and remote—has full visibility into plans, blockers, and resolutions. Knowledge sharing sessions and clear documentation reduce friction and accelerate delivery. About TRM's Engineering Levels: Engineer: Responsible for helping to define project milestones and executing small decision decisions independently with the appropriate tradeoffs between simplicity, readability, and performance. Provides mentorship to junior engineers, and enhances operational excellence through tech debt reduction and knowledge sharing. Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing. Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor. The following represents the expected range of compensation for this role: - Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only. - The estimated base salary range for this role is $200,000 - $275,000. - Additionally, this role may be eligible to participate in TRM’s equity plan. - Please note – we factor in the different costs for geographies outside the United States. Life at TRM We are building a safer world. That promise shows up in how we work every day. TRM moves quickly. We are a high velocity, high ownership team that expects clarity, follow-through, and impact. People who thrive here are energized by hard problems, experimentation, and continuous feedback. If something takes months elsewhere, it will ship here in days. Our work sits at the intersection of AI, national security, and fighting financial crime. The problems are complex, the stakes are real, and the environment evolves quickly. The pace and intensity of the work reflect the importance of the mission. As a result, the way we operate requires a high level of ownership, adaptability, collaboration, and creative problem-solving. At TRM, you should expect: - Priorities and targets to change quickly as we experiment and iterate - Work that often requires operating with a high degree of ambiguity - A high level of personal ownership and accountability - Close collaboration across teams and functions - Frequent, high-touch communication - Creative problem solving and out-of-the-box thinking - A pace that rewards urgency, adaptability, and outcomes This environment is energizing for people who enjoy building, solving hard problems, and making progress in situations that are not always fully defined. It also requires comfort navigating ambiguity, adjusting course as new information emerges, and maintaining focus and positivity in a fast-moving and intense environment. We also recognize that this style of operating is not for everyone. If you are primarily optimizing for predictability or a consistently balanced workload, we encourage you to use the interview process to pressure test whether this environment is truly the right fit. We want teammates who thrive here, not just survive here. At the same time, many people find this work deeply rewarding. If you are excited by meaningful problems, motivated by ambitious goals, and energized by working alongside mission-driven colleagues, there is a good chance you will find TRM to be an exceptional place to grow and contribute. Learn more: Interviewing at TRM: How We Hire and What Success Looks Like AI Fluency at TRM AI fluency is a baseline expectation at TRM. We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks. At TRM, AI fluency means you are among the top 10 percent of operators in your function in how you apply AI to: - Accelerate repeatable workflows - Structure and solve problems - Improve output quality - Increase speed and leverage You will be evaluated on applied AI fluency during the interview process. Leadership Principles We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions. - Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly. - Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end‑to‑end, and invest in getting better everyday. - Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one‑team mindset — giving and receiving feedback to make the team stronger. Join our Mission At TRM we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast. TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore. Privacy Policy and Additional Information By submitting your application, you are agreeing to allow TRM to process your personal information in accordance with the TRM Privacy Policy. Our typical hiring cycles for specialized roles span 24 to 36 months. Accordingly, we retain your personal information for up to 36 months to evaluate your application and to consider you for current and future employment opportunities, unless you request earlier deletion or a different retention period is required or permitted by law. To notify TRM Labs that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. The use of AI tools of any kind (including but not limited to notetakers, interview assistants, and real-time coaching tools such as Otter.ai, Fireflies, Fathom, Cluey, or similar) during TRM interviews is not permitted without prior approval from TRM. TRM uses its own internal tools for note-taking to ensure a consistent and confidential experience for all candidates. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this form. Recruitment agencies TRM Labs does not accept unsolicited agency resumes. Please do not forward resumes to TRM employees. TRM Labs is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company without a signed agreement. Learn More: Company Values | Interviewing | FAQs

Build a Safer World. TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all. The AI Engineering Team is chartered with enabling next-generation AI applications, with a special focus on Large Language Models (LLMs) and agentic systems. Our mission is to build robust pipelines, high-performance infrastructure, and operational tooling that allow AI systems to be deployed with speed, safety, and scale. We manage petabyte-scale pipelines, serve models with millisecond-level latency, and provide the observability and governance needed to make AI production-ready. We’re also deeply involved in evaluating and integrating cutting-edge tools in the LLM and agent space — including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that unlock TRM’s ability to innovate faster than the market. As a Staff MLOps Engineer with a focus in LLMOps, you’ll be at the core of building and scaling the technical infrastructure for AI/ML systems. You will: - Build reusable CI/CD workflows for model training, evaluation, and deployment — integrating Langfuse, GitHub Actions, and experiment tracking, etc. - Automate model versioning, approval workflows, and compliance checks across environments. - Build out a modular and scalable AI infrastructure stack — including vector databases, feature stores, model registries, and observability tooling. - Partner with engineering and data science to embed AI models and agents into real-time applications and workflows. - Continuously evaluate and integrate state-of-the-art AI tools (e.g. LangChain, LlamaIndex, vLLM, MLflow, BentoML, etc.). - Drive AI reliability and governance, enabling experimentation while ensuring compliance, security, and uptime. - Build and enhance AI/ML Model Performance - Ensure data accuracy, consistency and reliability, leading to better model training and inferencing - Deploy infrastructure to support offline and online evaluation of LLMs and agents — including regression testing, cost monitoring, and human-in-the-loop workflows. - Enable researchers to iterate quickly by providing sandboxes, dashboards, and reproducible environments. What We’re Looking For - Write high-quality, maintainable software — primarily in Python, but we value engineering ability over language familiarity. - Have a strong background in scalable infrastructure, including: - Containerization and orchestration (e.g. Docker, Kubernetes) - Infrastructure-as-code and deployment (e.g. Terraform, CI/CD pipelines) - Monitoring and logging frameworks (e.g. Datadog, Prometheus, OpenTelemetry) - Understand and implement ML Ops best practices, including: - Model versioning and rollback strategies - Automated evaluation and drift detection - Scalable model and agent serving infrastructure (e.g. vLLM, Triton, BentoML) - Deploy and maintain LLM and agentic workflows in production, including: - Monitoring cost, latency, and performance - Capturing traces for analysis and debugging - Optimizing prompt/response flows with real-time data access - Demonstrate strong ownership and pragmatism, balancing infrastructure elegance with iterative delivery and measurable impact. Learn about TRM Speed in this position: - Rapid Issue Resolution. TRM Engineers identify and resolve critical onsite issues in minutes to hours, not weeks. We create virtual war rooms, implement fixes, and share lessons with both customer stakeholders and internal teams within 48 hours. - Navigating Bureaucracy. We anticipate and address procedural hurdles, build trust with key stakeholders, and find alternative pathways to approvals. This keeps projects moving even in complex environments. - Efficient Knowledge Transfer. Engineers document and share updates in real time, ensuring the entire team—onsite and remote—has full visibility into plans, blockers, and resolutions. Knowledge sharing sessions and clear documentation reduce friction and accelerate delivery. About TRM's Engineering Levels: Engineer: Responsible for helping to define project milestones and executing small decision decisions independently with the appropriate tradeoffs between simplicity, readability, and performance. Provides mentorship to junior engineers, and enhances operational excellence through tech debt reduction and knowledge sharing. Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing. Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor. The following represents the expected range of compensation for this role: - Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only. - The estimated base salary range for this role is $200,000 - $275,000. - Additionally, this role may be eligible to participate in TRM’s equity plan. - Please note – we factor in the different costs for geographies outside the United States. Life at TRM We are building a safer world. That promise shows up in how we work every day. TRM moves quickly. We are a high velocity, high ownership team that expects clarity, follow-through, and impact. People who thrive here are energized by hard problems, experimentation, and continuous feedback. If something takes months elsewhere, it will ship here in days. Our work sits at the intersection of AI, national security, and fighting financial crime. The problems are complex, the stakes are real, and the environment evolves quickly. The pace and intensity of the work reflect the importance of the mission. As a result, the way we operate requires a high level of ownership, adaptability, collaboration, and creative problem-solving. At TRM, you should expect: - Priorities and targets to change quickly as we experiment and iterate - Work that often requires operating with a high degree of ambiguity - A high level of personal ownership and accountability - Close collaboration across teams and functions - Frequent, high-touch communication - Creative problem solving and out-of-the-box thinking - A pace that rewards urgency, adaptability, and outcomes This environment is energizing for people who enjoy building, solving hard problems, and making progress in situations that are not always fully defined. It also requires comfort navigating ambiguity, adjusting course as new information emerges, and maintaining focus and positivity in a fast-moving and intense environment. We also recognize that this style of operating is not for everyone. If you are primarily optimizing for predictability or a consistently balanced workload, we encourage you to use the interview process to pressure test whether this environment is truly the right fit. We want teammates who thrive here, not just survive here. At the same time, many people find this work deeply rewarding. If you are excited by meaningful problems, motivated by ambitious goals, and energized by working alongside mission-driven colleagues, there is a good chance you will find TRM to be an exceptional place to grow and contribute. Learn more: Interviewing at TRM: How We Hire and What Success Looks Like AI Fluency at TRM AI fluency is a baseline expectation at TRM. We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks. At TRM, AI fluency means you are among the top 10 percent of operators in your function in how you apply AI to: - Accelerate repeatable workflows - Structure and solve problems - Improve output quality - Increase speed and leverage You will be evaluated on applied AI fluency during the interview process. Leadership Principles We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions. - Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly. - Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end‑to‑end, and invest in getting better everyday. - Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one‑team mindset — giving and receiving feedback to make the team stronger. Join our Mission At TRM we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast. TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore. Privacy Policy and Additional Information By submitting your application, you are agreeing to allow TRM to process your personal information in accordance with the TRM Privacy Policy. Our typical hiring cycles for specialized roles span 24 to 36 months. Accordingly, we retain your personal information for up to 36 months to evaluate your application and to consider you for current and future employment opportunities, unless you request earlier deletion or a different retention period is required or permitted by law. To notify TRM Labs that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. The use of AI tools of any kind (including but not limited to notetakers, interview assistants, and real-time coaching tools such as Otter.ai, Fireflies, Fathom, Cluey, or similar) during TRM interviews is not permitted without prior approval from TRM. TRM uses its own internal tools for note-taking to ensure a consistent and confidential experience for all candidates. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this form. Recruitment agencies TRM Labs does not accept unsolicited agency resumes. Please do not forward resumes to TRM employees. TRM Labs is not responsible for any fees related to unsolicited resumes and will not pay fees to any third-party agency or company without a signed agreement. Learn More: Company Values | Interviewing | FAQs

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. Data Science and Engineering (‘DSE’) at Netflix is aimed at using data, analytics, causal inference, machine learning (ML), and sciences to improve various aspects of our business. The AI initiative at Netflix Games is dedicated to pioneering the next generation of interactive entertainment. We have the ambition to transform how players interact with stories, characters, and worlds by empowering gameplay experience with AI. We work at the intersection of creative game design and cutting-edge machine learning, ensuring that dynamic storytelling is not only novel but also coherent, immersive, and safe for our players. We are seeking an experienced L5 ML Scientist specialized in forecasting and audience research. In this role, you will: - Build Foundational ML Building Blocks: Develop sophisticated embeddings and models that incorporate deep game-specific signals to solve high-impact business problems, including audience insights, opportunity sizing, and forecasting. - Accelerate Product Development: Build the tools, models, and pipelines required to accelerate DSE workflows across games portfolio, studios, product, and platform. - Bridge the Netflix Ecosystem: Act as a key liaison with the broader Netflix DSE and AI teams to adopt, adapt, and tailor global Netflix capabilities for the unique requirements of the gaming space. - Design Scalable Pipelines: Create end-to-end ML pipelines that accelerate and enable DSE members across games to uncover actionable insights and build data-intensive game features. - Elevate ML Practices: Establish the technical standards for how ML capabilities are applied across game domains. Who Will Succeed in This Role: - Ph.D. in Computer Science, Machine Learning, or a related quantitative field. - 5+ years of experience leading complex, end-to-end ML projects that impact end-customer experiences. - 3+ years of experience navigating large-scale technical organizations to align roadmap priorities and share infrastructure - You can digest the latest research paper in the morning and ship a functional prototype or foundational model by the afternoon. - You can bridge the gap between technical ML architecture and business objectives, translating product needs into rigorous technical specifications. - You thrive in zero-to-one environments, enjoying the freedom to choose your stack and define the engineering standards for a new domain. - You have a foundational understanding of causal inference principles, allowing you to discern when a predictive model is sufficient vs. when a causal approach is required. - You have a passion for developing reusable ML capabilities to unlock and accelerate development work broadly. Nice to Have: - Experience working with game development teams, particularly in game design and engineering. - Experience with building production-grade ML systems, including MLOps best practices. - Have strong engineering skills, particularly in designing and optimizing evaluation frameworks (e.g., Python, PyTorch, LangChain). Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is . This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

• Lead the design and development of personalization in the P+ sign-up flow and Pluto TV registration flows. • Own end-to-end machine learning pipelines—from data and feature engineering to training, deployment, serving, and monitoring. • Partner closely with product, design, content, platform engineering, and data science to define roadmaps and deliver measurable user outcomes. • Advance our semantic search and browse experience through state-of-the-art embeddings, query understanding, and domain-specific model architectures. • Establish high-integrity experimentation practices, improve offline→online correlation, and guide feature rollouts with strong scientific rigor. • Mentor engineers and scientists, develop technical talent, and help shape the culture of our growing Applied ML organization.