Machine Learning Engineer Graduate

Machine Learning Engineer Graduate (E-Commerce Knowledge Graph - CV/Multimodal/NLP) -2026 Start (BS/MS) Location: San Jose Team: Technology Employment Type: Regular Job Code: A B Responsibilities Team Introduction: The Knowledge Graph team is responsible for the neural network of e-commerce, which includes tasks such as categorizing products, influencers, and merchants, mining product information, and providing this data to the recommendation team. Additionally, they manage operations related to product tags and category attributes. When we come across a product, they determine whether it belongs to the clothing or sports category, who it will be suitable for, etc. The team also conducts competitive research, identifies top-performing items on the platform, and analyzes why a similar product outperforms others. They are involved in brand recognition and collaborate closely with other teams. Dive deep into the construction and development of vast knowledge graphs that encapsulate real‑world products, aiding in feed ranking, recommendations, and ads. Collaborate closely with product managers, data scientists, and the strategic product & operation team to craft forward‑thinking product strategies and features. Craft intricate knowledge graphs, encompassing areas like product/content insights and category/brand/SPU development. Architect knowledge maps detailing buyer and product connections. Qualifications Minimum Qualifications: Bachelor's degree or above, final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline. Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment. Passion or exposure to areas like machine learning, NLP (Natural Language Processing), multimodal systems, and computer vision. Familiarity with or coursework related to programming languages like C++, Python, Go, or Java. Strong teamwork and communication skills. Any hands‑on experience or group projects in relevant technical scenarios will be a plus. Preferred Qualifications: Familiarity with deep learning frameworks like TensorFlow/PyTorch. Coursework or projects related to text classification, text matching, sequence labeling, and knowledge graphs. Knowledge of domain adaptation, text mining, and unsupervised/semi‑supervised methodologies. Experience with machine learning and deep learning algorithms, and text representation methods. Exposure to large‑scale text data processing or tools like Hadoop/Spark/Hive/Flink. Job Information The base salary range for this position in the selected city is $118,658 - $177,000 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 may vary depending on the nature of employment and the country work location. 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. 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 the withdrawal of the conditional offer of employment: Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; Exercising sound judgment. #J-18808-Ljbffr