Role Description The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. As a Staff ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit. - Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more. - Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration. - Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment. - Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more. - Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges. Qualifications - 8+ years of experience in ML infrastructure, including model training and model deployments. - Hands-on experience with ML optimization, including memory and GPU profiling. - Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more. - Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb). - Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc. - Deep experience working with distributed training frameworks, including Ray and Kubernetes. - Strong focus on scalability, reliability, performance, and ease of use. - Strong organizational & communication skills. - Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus. - Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus. Requirements - 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. - 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. - The base salary range for this position is: $230,000 - $322,000 USD. Benefits - Medical, dental, and vision insurance. - 401(k) program with employer match. - Generous time off for vacation. - Parental leave.

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What Is The Role : We are on the lookout for a Principal Software Engineer II to join our Elasticsearch - Machine Learning team and help build and maintain the platform and components used for machine learning in Elasticsearch. On the Java side this will involve maintaining and extending ML support in Elasticsearch, on the C++ side this will involve working on model performance optimizations. You will help us to build the platform and components that enable customers to gain insight from their data. This team builds and maintains the infrastructure that integrates advanced analytics and machine learning components into the distributed Elastic platform - making these available for our Search, Observability and Security Solutions. This work will involve close collaboration with elasticsearch and enterprise search engineers. What You Will Be Doing : - Build and maintain Machine Learning and advanced analytical platform components. - Implement scalable, high quality, well-architected code. - Collaborate with other engineering teams within Elastic that build on our platform. - Assist our support engineers and community. - Promote knowledge sharing and collaboration in a distributed team. What You Bring : - You have strong skills in core Java and C++ and are conversant in the standard library of data structures and concurrency constructs, as well as newer language features. - You have a deep technical proficiency in algorithms. - You have professional experience in leading the development of Machine Learning components. - You have shown your ability to understand and work on complex systems. - You demonstrate the ability to build and debug features with a broad impact, running on multiple machines. - You are able to own projects from beginning to end. This covers both technical design and working with others to develop needed components. - You have experience communicating with a variety of stakeholders. Bonus Points : - Experience with the Elastic Stack. - Experience with Python / Go. - Open source experience. Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $199,700—$315,900 USD The typical starting salary range for this role in the select locations listed above is: $239,800—$379,300 USD Additional Information - We Take Care of Our People As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do. We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do. - Competitive pay based on the work you do here and not your previous salary - Health coverage for you and your family in many locations - Ability to craft your calendar with flexible locations and schedules for many roles - Generous number of vacation days each year - Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service - Up to 40 hours each year to use toward volunteer projects you love - Embracing parenthood with minimum of 16 weeks of parental leave Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email candidate_accessibility@elastic.co. We will reply to your request within 24 business hours of submission. Applicants have rights under Federal Employment Laws, view posters linked below: Family and Medical Leave Act (FMLA) Poster; Pay Transparency Nondiscrimination Provision Poster; Employee Polygraph Protection Act (EPPA) Poster and Know Your Rights (Poster) Elasticsearch develops and distributes technology and information that is subject to U.S. and other countries’ export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic. Please see here for our Privacy Statement.

Please submit your resume in English and indicate your level of English. At Toloka, we connect smart, curious people from around the world with freelance online tasks that train and improve artificial intelligence. What we do The Toloka Annotators connects individuals with Generative AI projects from leading tech innovators. Our mission is to unlock the full potential of AI by involving real people from around the world in the development process. About the Role Annotation is what helps AI make sense of the world. As an annotator, you may be invited to take part in online projects such as rating AI-generated content, evaluating factual accuracy, or comparing responses - when projects are available. Responsibilities: - Carefully review provided data (text, images, or videos) - Label or classify content based on project guidelines - Identify and flag factually incorrect, sensitive, inappropriate, or unclear material Important note: This is project-based work. Tasks are available only when projects are active. You may be invited to one or more projects depending on your profile and current opportunities. Each project has its own compensation level based on scope and expertise required. On this project, AI trainers earn up to $23 per hour equivalent.

• Design, implement and validate high-reliability, distributed platforms for machine learning, natural language processing, and LLMs. • Create, debug, interpret and improve production machine learning and natural language processing models. • Build the tools and validation processes that help Clover translate insights into action at scale. • Use existing commercial and open-source tools to create a robust production platform. • Work closely with Clover's Data Science and Engineering teams to ensure that the ML/NLP/LLM Platform is providing real value. • Document, iterate, and provide tutorials to ensure Data Scientists are able to use your tools easily.