Machine Learning Engineer, Ads Creative
Job Description
Responsibilities
- Contribute to the development of a large scale ads platform.
- Lead the development of state of the art applied machine learning projects within ads.
- Own critical targeting components and strategies in the ads monetization ecosystem.
- Collaborate with product and business teams to shape product vision and roadmap.
Requirements
- BS or MS degree in Computer Science, Computer Engineering, or related fields.
- Strong theoretical grounding in machine learning with practical experience in ML concepts and techniques.
- Excellent programming, debugging, and optimization skills in Go, C/C++, Python or similar languages.
- Experience with ML frameworks such as TensorFlow, PyTorch, MXNet, or equivalent.
- Ability to think critically and articulate solutions clearly and concisely.
Technologies
- Go
- C
- C++
- Python
- TensorFlow
- PyTorch
- MXNet
Compensation
- Base salary range: $156,000 - $316,800 annually.
- Pay transparency description: The base salary range for this position in the selected city is $156000 - $316800 annually.
Location
San Jose, CA (onsite)
Employment Type
Regular
Job Code
A56375
Benefits
- Medical, dental, and vision insurance
- 401(k) savings plan with company match
- Paid parental leave
- Short-term and long-term disability coverage
- Life insurance
- Wellbeing benefits
- 10 paid holidays per year
- 10 paid sick days per year
- 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)
- Potential discretionary bonuses/incentives
- Restricted stock units
Los Angeles County 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
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