HireIQ Intelligence Brief
Week 1 — Edition 001

Post Series E close. Scaling safety & product teams simultaneously. Highest hiring velocity since 2023.

Grok 3 training in progress. Colossus cluster expansion driving infra hiring surge. Compensation packages reportedly 1.3–1.5× market.

Building San Francisco office. European talent visa restrictions creating urgency for US-based sourcing. Series B closed at €1B+ valuation.

Command R+ traction driving enterprise deals. GTM hiring spike. Engineering headcount targeted to double by Q3.

Revenue-driven hiring. $73M Series B. Product team growing aggressively around AI search. Strong emphasis on speed and system design.

Infrastructure and trust & safety teams reduced ~12%. AI-assisted labeling automation cited as primary driver. Core ML research team untouched.

Full hiring freeze across all teams following leadership restructuring. R&D budget under review. Several senior researchers actively exploring options.

Post-Microsoft pivot, remaining team is minimal. Most original headcount has already exited. Strong alumni pool dispersed across Anthropic, Google DeepMind, and Meta AI.

US go-to-market buildout now fully funded. Hiring 30–50 engineers and commercial roles in SF over next 6 months. Decision-maker: Chief People Officer (LinkedIn reachable).

Extremely small team (~30 people). Capital deployed toward 2–3x headcount in next 90 days. Expect SWE and ML Engineer openings at premium comp. Source from Codeforces / competitive programming communities.

Japan-based but building distributed research team. Remote-first. Focus on evolutionary/nature-inspired AI architectures. Niche but valuable sourcing opportunity for researchers with optimization or neuroevolution backgrounds.

Total comp widened significantly due to equity upside variance. Anthropic and xAI both offering above-median equity refreshes to retain. Don't anchor to base alone.

Research roles at Big Tech remain competitive vs. labs. DeepMind London comp in GBP is often underbid — candidates comparing US offers need guidance on currency-adjusted TC.

GPU cluster optimization skills commanding 20–30% premium over standard SWE infra roles. CUDA/Triton experience effectively adds $40–70K to market value this cycle.

SSI now has ~30 open roles across alignment research and infrastructure. No products — pure research funding model. Strong sourcing pool for candidates motivated by safety-first mission over commercialization.

Several of Kass's former GTM reports are now exploring options. OpenAI enterprise sales team has experienced above-average churn since departure. Good moment to source OpenAI's commercial-side talent.

Hi [First Name],

I came across your work on [specific project, paper, or open-source contribution] — the [one specific detail that shows you actually read it] piece was particularly interesting given what we're building.

I'm recruiting for a Senior ML Engineer role at [Company]. The team is working on [1-sentence specific problem], and your background in [relevant skill from their profile] seems like a strong fit for the challenges we're trying to solve.

A few things that might be relevant for your decision-making:
• Comp: $[X]K base + meaningful equity (happy to share the full details)
• Stack: [specific technologies — be precise, not generic]
• Team: [team size], reporting to [credible name or title]

No pressure if the timing isn't right — but if you're at all curious, I'm happy to share more details on what we're working on before any formal process.

Worth a quick call?

[Your name]
[Title] @ [Company]

• →Replace [specific project/paper] with something real from their GitHub, Google Scholar, or LinkedIn — never template this line
• →Lead with the specific detail before the ask — it signals you aren't mass-blasting
• →Comp transparency in first message increases response rate ~40% for senior ML talent
• →Send Tuesday–Thursday, 9–11am target timezone for peak open rates

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