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Software Engineer - Recommendation Infrastructure, Performance Efficiency

$156k - $387.6k

Ellis Technologies, Inc.

Software Engineer - Recommendation Infrastructure, Performance Efficiency Location: San Jose Employment Type: Regular Job Code: A27298 Responsibilities The Recommendation System Infrastructure team is responsible for building and evolving the large-scale online serving and data infrastructure that powers TikTok’s recommendation products globally. Our mission is to deliver highly efficient, reliable, observable, and scalable infrastructure for recommendation systems. The team works closely with recommendation algorithm teams to accelerate strategy iteration, improve compute efficiency, optimize serving cost, and enable the next generation of AI-native and agentic engineering workflows. We focus on core infrastructure challenges across online/nearline/offline modules on GPU/CPU, high-performance computing, data pipelines, observability, automation, system reliability, and cost optimization. Our systems are primarily built in C++, while broader infrastructure and automation work may also involve offline data processing frameworks such as Flink, Spark, or other large-scale data systems. A key direction of the team is to build 24/7 closed-loop agentic systems that can observe, diagnose, plan, execute, verify, and continuously improve recommendation infrastructure and iteration workflows. Design, build, and optimize high-performance online serving systems for large-scale global recommendation systems, improving business ROI, system efficiency, and serving quality. Improve the efficiency, reliability, scalability, and cross-regional consistency of recommendation system infrastructure. Identify and resolve system performance bottlenecks across CPU, memory, bandwidth, GPU compute efficiency, serving latency, throughput, and resource allocation efficiency. Drive cost optimization for large-scale recommendation serving, including business-impacted cost efficiency, compute resource utilization, and infrastructure or strategy level performance improvements. Build reliable and efficient workflows and pipelines for automation on candidate generation, profile generation, feature processing, training data generation, and online development. Qualifications Minimum: Bachelor's degree or above in Computer Science, Software Engineering, or a related technical field. Experience in building scalable backend systems, distributed systems, infrastructure systems, or high-performance online services. Strong programming skills in at least one systems programming language, such as C++, C, Go, or Java. Solid understanding of data structures, algorithms, operating systems, networking, and distributed system fundamentals. Experience with performance analysis, system debugging, reliability improvement, or large-scale service optimization. Strong ownership, problem-solving ability, and communication skills. Ability to work effectively with cross-functional teams, including infrastructure teams, recommendation algorithm teams, and product/business-facing engineering teams. Preferred: Experience with infrastructure for recommendation systems, search engines, advertising systems, machine learning systems, or large-scale online serving systems. Experience optimizing high-throughput, low-latency C++ services in production environments. Familiarity with profiling, benchmarking, performance tuning, capacity planning, resource efficiency improvement, and cost optimization. Experience with large-scale data processing systems such as Flink, Spark, Kafka, or similar frameworks. Experience building end-to-end automation systems based on AI agents, LLMs, workflow orchestration, or closed-loop engineering automation. Experience designing agentic workflows for system diagnosis, performance optimization, reliability improvement, change validation, or automatic execution. Experience with real-time data pipelines, online training, feature engineering, candidate generation, or recommendation system iteration workflows. Job Information The base salary range for this position in the selected city is $156,000 - $387,600 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units. Benefits Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure). The Company reserves the right to modify or change these benefits programs at any time, with or without notice. Fair Chance Eligibility For Los Angeles County (unincorporated) Candidates: Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in withdrawal of the conditional offer of employment: 1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; 2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; 3. Exercising sound judgment. #J-18808-Ljbffr

Vacancy posted 14 hours ago
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