Responsibilitie

About The Team The Applied Machine Learning (AML) team combines system engineering and the art of machine learning to develop and run massively distributed recommendation systems around the world. The efficiency tools team provides a high-quality tool platform and technical outputs for the efficiency and training of online models and the management of the team's massive hardware resources. Responsibilities: - Research, design, and develop computer and network software or specialised utility programs. - Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. - Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures. - Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements. - Research, design, and develop computer and network software or specialised utility programs. - Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis. - Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures.

Qualification

Minimum Qualifications: - Bachelor's degree in Computer Science or equivalent with 1+ years of relevant experience - Proven experience in analyzing and troubleshooting distributed systems. - Prior experience designing and maintaining large-scale systems. - Experience programming in at least one of the following languages: Python or Golang. - Familiar with components, such as Mysql, Redis, Kafka, Clickhouse, Terraform and K8S, etc. - Expertise in DevOps technologies like Monitor, Alarm, Tracing, CMDB etc. - Experience in building solutions with AWS, Azures, AliCloud or other cloud services. Preferred Qualifications: - Familiar with Unix/Linux operating systems. - Ability to thrive in a fast-paced environment. - Strong understanding of code optimizing and routine tasks automation. - Extra points will be given for proficiency in at least one machine learning framework: TensorFlow, PyTorch, MXNet or PaddlePaddle. - Solid background of algorithms and data structures.

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $128000 - $316800 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.