Jobs
Benefits & Perks
•Remote work flexibility
•Health, dental, and vision coverage
•Wellness benefits
•Top Tier compensation with equity
•Annual team offsites
•Learning and development stipend
Required Skills
TensorFlow
Python
Apache Spark
Meta is seeking experienced Partner Engineers to join the Scaled Operations AI Accelerator Team. This team is responsible for rapidly designing, developing, and deploying AI-powered automation solutions that transform operational processes and drive efficiency at scale. As a Partner Engineer, you will play a pivotal role in building and implementing innovative solutions using AI technologies, collaborating across functions, and managing the work of contractor and/or vendor workers to deliver measurable impact across Scaled Operations.
Software Developer, Scaled Ops AI Acceleration Team Responsibilities:
- Design, develop, deploy, and maintain AI-powered automation solutions to optimize and automate key operational processes
- Rapidly prototype, iterate, and implement technical solutions that drive full-time employee efficiency using AI technologies
- Collaborate with process owners, architects, product managers, and cross-functional teams to identify high-impact automation opportunities and deliver solutions aligned with business needs
- Apply full-stack engineering skills, including backend, frontend, and data engineering, to build robust, scalable, and maintainable systems
- Manage and guide contractor workers and/or vendor workers in the development and delivery of technical solutions, ensuring quality, compliance, and alignment with team objectives
- Ensure all solutions adhere to Meta's security, privacy, and compliance requirements
- Communicate technical concepts, project status, and solution impact clearly to both technical and non-technical audiences
- Stay current with advancements in AI/ML and automation, and experiment with new tools and approaches to foster innovation and continuous improvement
- Contribute to the development of playbooks, reusable templates, and best practices to scale successful automations across Scaled Operations
- Track, analyze, and report on key metrics and business impact of automation initiatives
Minimum Qualifications:
- 8+ years of experience in software engineering, support engineering, reliability engineering or related
- 6+ years of experience in one or more of the following areas: machine learning, recommendation systems, natural language processing, data mining, artificial intelligence, AI-Infrastructure, or related technical field
- Bachelor's degree in Computer Science, Computer Engineering, related technical field, or equivalent experience
- Experience with the full web stack, REST API, Python, PHP/Hack, JavaScript/React development along with debugging and bug management support
- Knowledge on fine-tuning and optimizations of Py Torch models and with at least one LLM such as Llama, GPT, Claude, Falcon, etc
- Experience in communicating with technical and business audiences and creating technical documentation
- Experience assessing, analyzing, and resolving operational issues using data analysis (SQL)
- Experience overseeing and guiding contractor workers and/or vendor workers in technical solution delivery
- Demonstrated collaborate in cross-functional teams and deliver results in a demanding environment
Preferred Qualifications:
- Experience with Meta's internal tools and platforms
- Familiarity with Global Operations processes and workflows
- Advanced degree in Computer Science, Engineering, or related field
- Experience developing playbooks, reusable templates, and best practices for automation at scale that can be leveraged by less technical partners
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and Whats App further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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About Meta

Meta
PublicA social technology company that enables people to connect, find communities, and grow businesses.
10,001+
Employees
Menlo Park
Headquarters
$800B
Valuation
Reviews
3.4
26 reviews
Work Life Balance
2.3
Compensation
4.2
Culture
2.8
Career
3.1
Management
2.1
45%
Recommend to a Friend
Pros
Excellent compensation and benefits
Smart and talented colleagues
Fast-paced and challenging work environment
Cons
Frequent layoffs and job insecurity
Poor leadership and management accountability
High stress and competitive work environment
Salary Ranges
40,175 data points
Mid/L4
Mid/L4 · Data Scientist
3,113 reports
$284,667
total / year
Base
$179,458
Stock
$79,981
Bonus
$25,228
$193,897
$434,902
Interview Experience
6 interviews
Difficulty
4.2
/ 5
Duration
21-35 weeks
Offer Rate
17%
Experience
Positive 17%
Neutral 17%
Negative 66%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Coding Interviews
6
System Design Interview
7
Behavioral Interview
8
Final Loop/Hiring Manager Round
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Live Coding
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