• Participate in all phases of the AI development lifecycle, including problem framing, data analysis, solution design, model or agent development, evaluation and testing, deployment, monitoring, iterative improvement, support. • Own the technical execution of sprint deliverables from design through deployment. • Drive daily engineering momentum: run stand-ups from a technical lens, surface blockers early, and resolve them before they become delays. • Make implementation-level decisions confidently and quickly within the established architecture. • Review pull requests with a focus on correctness, performance, security, and long-term maintainability. • Ensure engineering work is aligned to acceptance criteria and Definition of Done including eval thresholds for AI features. • Design, build, and maintain reusable, scalable AI/ML systems, including model pipelines, feature engineering workflows, and inference services. • Partner with technical and business teams to translate complex business problems into effective AI/ML solutions. • Provide effort estimation, dependency analysis, and technical risk assessment for initiatives, epics, and complex features. • Act as a face of the AI Engineering team to the rest of the organization. • Provide technical leadership and engineering guidance for AI/ML solutions, ensuring alignment with enterprise standards, security requirements, and ethical AI principles. • Lead technical design reviews, influence architectural decisions, and set best practices for AI/ML development, deployment, and lifecycle management. • Mentor and guide engineers and data scientists on AI/ML design patterns, model evaluation, performance optimization, and responsible AI practices. • Communicate complex technical concepts, tradeoffs, and outcomes clearly to both technical and non-technical stakeholders. • Ensure solutions meet regulatory compliance, security, and data governance requirements, including privacy-by-design and model risk management. • Act as a trusted technical advisor to engineering leadership, technical, and business stakeholders. • Identify and resolve cross-team technical dependencies proactively, before they block sprint delivery. • Translate architecture decisions from the AI Architect into concrete, sprint-ready engineering tasks. • Partner with BSAs to pressure-test requirements for technical feasibility and surface AI-specific constraints early. • Represent the team in ARB reviews, technical design sessions, and cross-functional working groups when needed.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com. We’re looking for a Senior Staff Machine Learning Engineer to join our Feed Relevance team, which is responsible for the end-to-end systems that power personalization and ranking for the main Reddit feeds. This is a critical role that blends hands-on development with technical leadership, focusing on building scalable, extensible, and highly performant personalization systems. You will be instrumental in defining the technical direction for the team, collaborating closely with Product and Engineering leadership to set the strategy, and working with other individual contributors to execute and scale our systems to serve tens of millions of users. This work will directly enable our Machine Learning Engineers (MLEs) and engineers to quickly iterate and continuously improve the user experience. You will also partner with Infra and Platform teams to inform the direction of our core infrastructure, building for the future of ML at Reddit. Responsibilities: - Deliver on technical initiatives that have significant company-wide impact - Set technical direction for the broader Relevance and Feeds teams at Reddit, able to identify opportunities and influence strategy across multiple orgs - Work with management on goal setting, planning, and de-risking critical projects - Mentor and grow Senior and Staff engineers - Create a strong healthy engineering culture Qualifications: - 10+ years of industry experience building systems for relevance driven products - Subject matter expert in relevance, recommendation, and ML systems; able to solve complex problems in these domains that few others can - Deep understanding of how to build sustainable software systems at a large scale engineering organization - Experience in influencing organizations on technical direction/best practices - Experience working with cross-functional teams such as design, product, business & data teams to deliver great experiences. - Strong focus on user experience, usability, scalability, reliability and quality. You are an undying advocate for the user, and you have a deep intuition for how people & machines interact with software at scale. - High empathy, excellent communication skills, and the ability to find compromise working across the entire engineering org Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave #LI-remote, #LI-JS5 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $266,000—$372,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors. Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

• Diseñar, desarrollar y mantener soluciones de machine learning desde la concepción hasta su implementación en producción. • Colaborar con equipos de datos, producto e ingeniería para integrar modelos en productos reales. • Analizar grandes volúmenes de datos para resolver problemas complejos mediante modelos predictivos. • Optimizar modelos y sistemas existentes para mejorar eficiencia y rendimiento. • Implementar soluciones en la nube (AWS, GCP o Azure), maximizando su escalabilidad y costo-beneficio. • Documentar y presentar los desarrollos técnicos de manera clara y efectiva. • Impulsar mejoras continuas en prácticas de desarrollo y adopción de nuevas tecnologías.

Role Description This engagement is focused on building an internal AI platform that enables developers to ship AI-powered services efficiently. The scope includes: - Model connectivity - Prompt testing and evaluation - Monitoring/observability - The underlying AI infrastructure layer The objective is to improve DevEx and reduce time-to-market for AI features. Tasks include: - Build and operate the AI platform infrastructure enabling developers to ship LLM-based services faster. - Implement and maintain Kubernetes-based runtime environments (incl. AKS) for AI workloads. - Manage infrastructure as code with Terraform (modules, environments, CI/CD automation). - Support LLM workflows: RAG, agents, prompt experimentation, evaluations, and deployment patterns. - Integrate and operate tooling such as Azure AI Foundry, LiteLLM, Langfuse, MLflow. - Orchestrate pipelines using Kubeflow Pipelines and/or Argo Workflows (build, deploy, evaluate). - Improve platform reliability and observability (monitoring, logging, tracing, cost/perf signals). - Collaborate closely with developers to streamline DX (APIs, templates, docs, golden paths, automation). Qualifications - Strong hands-on experience with Kubernetes in production (preferably AKS). - Solid Terraform expertise (IaC best practices, multi-env setups). - Practical experience supporting ML/LLM workloads in a platform or DevOps/MLOps context. - Proficiency in Python for automation, scripting, and supporting APIs/evaluation tooling. - Understanding of CI/CD, release processes, and production-grade operations. - Ability to work under tight timelines and deliver pragmatically. Requirements - Experience building internal developer platforms or “paved roads” for engineering teams. - Familiarity with LLM evaluation frameworks, prompt testing workflows, and LLM observability. - Exposure to RAG architectures, vector databases, and agentic patterns. - Experience with Kubeflow, Argo, and ML lifecycle tooling. Benefits - Long-term B2B contract. - Join a team of 5, with 3 AI Platform Engineers being added. - Remote within Europe (preferred: Croatia, Poland, Portugal, Serbia). - European working hours. - Occasionally available for meetings up to 10:00 AM PST (US overlap).