Overview
Turing is a private AI talent and services company headquartered in Palo Alto, California. The firm reached profitability in 2024 on roughly US$300 million in annual recurring revenue and most recently raised a US$111 million Series E in 2025, taking total funding to US$249 million. Turing operates with about 6,500 internal employees and runs an AI-vetted talent cloud of more than four million software engineers, data scientists, and STEM specialists. Founder Jonathan Siddharth is CEO.
Turing's business has bifurcated since 2024. The largest revenue stream is AI training and reasoning data work for frontier model labs, where Turing supplies vetted technical contributors to OpenAI, Anthropic, Google, Meta, and other labs to advance coding, agentic, multimodal, and STEM capabilities. The second stream is enterprise staff augmentation — placement of vetted remote engineers and AI specialists into customer engineering teams on monthly retainer. AI-specialist roles attract a premium and now represent the fastest-growing revenue segment.
Turing fits buyers that need senior or specialist engineers quickly at globally distributed pricing, particularly for AI, ML, data, and modern web stacks. It is not a fit for onshore-only US federal work, traditional managed services, or buyers that prefer a single employed-team model over distributed contractors.
Services Offered
- Vetted software engineer placement (full-stack, mobile, backend)
- AI and machine learning specialist placement
- LLM training, RLHF, and model evaluation contributor sourcing
- Data engineers and analytics talent
- Managed engineering pods for product teams
- DevOps, SRE, and platform engineering contractors
- QA automation and test engineering
- Forward-deployed AI engineers and MLOps specialists
- Generative AI application development
- Contractor compliance, payroll, and IP assignment
Typical Engagement
| Engagement Type | Model | Typical Range |
|---|---|---|
| Sourcing & vetting (free trial) | No cost | 2-week trial standard |
| Individual engineer placement | Monthly retainer | $10K–$28K/month per engineer |
| AI specialist / staff engineer | Monthly retainer | $25K–$80K/month per role |
| Managed engineering pod | Monthly retainer | $60K–$220K/month (4–10 people) |
| Staff augmentation (hourly equivalent) | Hourly bill rate | $55–$200/hour blended |
Pricing ranges verified May 2026 from public statements, customer reference checks, and Turing's published rate cards. Rates vary by seniority, region, and AI specialisation. Frontier-AI lab contributor work is priced separately under outcome-based contracts.
Strengths
- AI-driven matching engine reduces typical placement cycle to under two weeks
- Deepest specialist bench for LLM training, RLHF, and AI evaluation among staff aug providers
- Free two-week trial period materially reduces buyer placement risk
- Talent cloud of 4M+ vetted candidates provides redundancy when a placement does not work out
- Demonstrated work with all major frontier AI labs lends credibility on advanced AI roles
- Private, profitable, and well-capitalised after a 2025 Series E
Limitations
- Pricing for senior AI specialists has risen materially since 2024, narrowing the discount versus US onshore rates
- Limited bench for security-cleared US federal or defence engagements
- Engineers are independent contractors, not Turing employees, which limits long-term retention guarantees
- Less suited to fixed-scope outcome-based delivery than systems integrators
- Quality variability reported across non-AI generalist roles versus its strong AI specialist tier