Responsibilitie

The Applied Machine Learning (AML) team is seeking a Machine Learning Platform Engineer to develop and maintain our machine learning platform. The platform supports deep learning models for code development, testing, training, model deployment, and other core business functions. The team oversees the company's critical machine learning platform and serves as a foundation for recommendation, advertising and search. Here, you can work on recommended systems and distributed training of large-scale deep learning models. We welcome candidates interested in machine learning platform engineering and with excellent engineering capabilities to join our team. If you love challenges and want to develop in the innovation field, please submit your application as soon as possible. What you'll do - Design, develop, and maintain core functions of the machine learning platform, including data processing, feature engineering, model training, model insights, and model deployment. - Build efficient, scalable data processing and computing processes to ensure platform stability and performance. - Collaborate with data scientists and machine learning engineers to understand their requirements and provide tool and technical support. - Work closely with system administrators and software engineers to ensure smooth platform integration with other systems. - Responsible for managing and monitoring the operation of the machine learning platform and troubleshooting any platform-related issues. - Continuously track and evaluate emerging technologies and tools and provide suggestions for platform improvements and development.

Qualification

Minimum Qualifications - A bachelor's or above degree in computer science, software engineering, or a related field. - At least 3 years of experience in software engineering and be proficient in developing using common programming languages (such as Python and Golang). - In-depth understanding of distributed computing and principles and technologies of large-scale data processing, familiar with related open source tools and frameworks (such as Hadoop, Spark, etc.). - Possess good communication and teamwork skills, effective collaboration with team members from different technical backgrounds. - Enthusiastic about learning new technologies and solving complex problems, passionate about engineering challenges. - Strong analytical and problem-solving skills, ability to quickly understand and solve engineering problems.

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $162000 - $387600 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:

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; and

3. Exercising sound judgment.