Updated Jan 20, 2026 using last 90 days postings.
Meta Hiring Trends – January 2026
Meta is scaling extensively in machine learning and AI engineering, particularly focusing on advancing personalization of AI and generative AI programs. They are also expanding infrastructure-related operations, including global data annotation workflows, infrastructure investments, and hardware accelerator design for data centers. Additionally, Meta is growing teams in product risk management, growth marketing across their core apps, and game development, all concentrated mainly in California and Texas with limited remote options.
Note: These dashboards are not the source of truth. Job posting data can include duplicates and may double count roles. Treat the results as a sample that helps explain what the postings suggest about hiring focus. Summaries are generated with an LLM and may contain errors or omissions. For the most accurate and complete information, research the company directly.
Tracked openings
1,609
Remote share
5%
Top location
CA, US
Top category
Machine Learning And Ai Engineering
Inside The Product
SummaryMeta is hiring across AI/ML product research and engineering, large-scale infrastructure and data center operations, and product/platform teams that support billions of users. Openings emphasize scaling GenAI and LLM personalization, building and operating data and compute infrastructure, and maturing cross‑product operational and risk processes.
What They Build
- AI/ML and GenAI — LLM post‑training, personalization, RL environments, synthetic data curation
- Data operations and annotation pipelines that power machine learning products
- Infrastructure and data center engineering — ASICs, energy strategy, global supply chain and accounting
- Platform and tooling for Global Operations to unify production workflows and developer tooling
- Product growth and monetization systems embedded in product teams
- Games platform and central technology to scale multiple game titles
Customers & Users
- End users of Meta apps at global scale (Facebook, Instagram, WhatsApp, Oculus)
- Internal product and engineering teams that consume models, tooling, and operational services
- Businesses and advertisers that use Meta products
- Regulators, auditors, and external assessors involved in risk and compliance reviews
- Data center and infrastructure partners/stakeholders
Workflows & Systems
- Cross‑functional program management to launch and scale GenAI programs and annotation operations
- Large‑scale data curation and labeling pipelines feeding ML training and personalization efforts
- Unified tooling and last‑mile engineering to remove bottlenecks across Global Operations
- Hardware design and verification cycles for data‑center accelerators (ASIC development and validation)
- End‑to‑end infrastructure accounting and operationalization of new accounting programs
- Risk assessment and remediation workflows involving product, engineering, legal and external auditors
- Policy engagement and advocacy workflows tied to site selection, energy, and regulatory interactions
- Embedded product growth loops combining analysis, experimentation, and cross‑functional execution
Role Insights
Machine Learning & AI Engineering
Hiring to advance GenAI and LLM personalization via post‑training techniques, RL recipes, synthetic data curation, and large‑scale user profiling.
Data Operations & Annotation
Program managers and operators are scaling global annotation and workforce management to deliver training data and insights for core ML products.
Data Engineering & Global Operations
Backend and full‑stack engineers are building unified, interoperable tooling to mature production workflows and remove engineering bottlenecks across Global Operations.
Infrastructure & Hardware Engineering
ASIC and infrastructure hires focus on designing and verifying accelerators and operating efficient, high‑uptime data centers.
Risk, Compliance & Assurance
Product risk program managers are conducting assurance assessments, validating privacy/risk determinations, and driving remediation with product, legal and external assessors.
Finance & Infrastructure Accounting
Accounting roles are operationalizing end‑to‑end accounting processes to support rapid infrastructure expansion and supply chain investments.
Product Growth & Analytics
Growth analysts are embedded in product teams to run experimentation, analysis and ideation that directly tie to product metrics for global apps.
Policy & Energy Strategy
Policy hires work with regional teams and business stakeholders to shape energy and site selection policy that impacts data center operations.
Game Development Engineering
Tech leads are building scalable central game tech and platforms to support multiple new mobile game titles under Central Technology guidance.
Team Focus
- Machine Learning And Ai Engineering: 96 roles (6.0%)
- Manufacturing Engineering: 58 roles (3.6%)
- Embedded Software Engineering: 55 roles (3.4%)
- Data Engineering And Infrastructure: 53 roles (3.3%)
- Engineering Management: 46 roles (2.9%)
- Manufacturing And Production: 38 roles (2.4%)
- Data And Analytics: 34 roles (2.1%)
- Heavy Equipment Operations: 33 roles (2.1%)
Skill Stack
Machine Learning And Ai Engineering
Manufacturing Engineering
Embedded Software Engineering
Data Engineering And Infrastructure
Engineering Management
Manufacturing And Production
Location Footprint
- CA, US: 456 roles (28.3%)
- Canada: 189 roles (11.7%)
- WA, US: 148 roles (9.2%)
- India: 73 roles (4.5%)
- NY, US: 65 roles (4.0%)
- United Kingdom: 63 roles (3.9%)
- Remote (US): 59 roles (3.7%)
- OH, US: 51 roles (3.2%)
Seniority Mix
- Mid: 1219 roles (75.8%)
- Senior: 209 roles (13.0%)
- Entry: 105 roles (6.5%)
- Intern: 76 roles (4.7%)
Role Types
- full_time: 1488 roles (92.5%)
- internship: 100 roles (6.2%)
- contract: 10 roles (0.6%)
- other: 7 roles (0.4%)
- part_time: 4 roles (0.2%)