Remote vs Onsite AI Engineer:
Which Work Style Fits Your Career?

Location-adjusted: Remote AI engineers outside tech hubs earn $130K-$200K. Onsite engineers in SF/NYC earn $180K-$300K+. However, cost of living dramatically affects real purchasing power. A $180K remote salary in Austin or Denver often provides better lifestyle than $250K in San Francisco. Some companies pay 'location-adjusted' rates (10-25% less for remote). Others pay the same regardless of location—these are premium remote opportunities. The trend: large tech companies increasingly adjust pay by location, while AI-native startups often pay uniformly.

Research suggests remote workers do get promoted slightly slower—about 30% less likely in some studies. Visibility matters for promotions. However, this varies dramatically by company culture. Remote-first companies (GitLab, Zapier, many AI startups) promote remote workers normally. Traditional companies with forced-remote create two-tier systems favoring onsite. The key: choose companies with remote-friendly culture, not companies tolerating remote work. Ask during interviews: 'What percentage of your engineering leadership works remotely?'

AI-native companies often have strong remote cultures: Anthropic, Hugging Face, and many AI startups. Remote-first companies (GitLab, Zapier, Automattic) hire AI engineers fully remote. Big tech varies: Google and Meta have pushed RTO, while Microsoft and some others maintain hybrid flexibility. The most competitive remote AI roles: specialized positions at AI-native companies, contract work for multiple clients, and infrastructure/MLOps roles that don't require on-prem access. The least remote-friendly: roles requiring access to proprietary data or specialized hardware.

For experienced engineers, remote productivity is typically equal or higher—fewer interruptions, no commute, focused deep work time. For junior engineers, remote can slow learning—less spontaneous mentorship, harder to ask quick questions. AI engineering specifically: most work is individual coding and research, which suits remote well. Collaborative work (system design, debugging sessions) is harder remote but manageable with good tools. The real productivity factor: your personal work style and home environment. Some people thrive remote, others need office structure.

The market has settled into three tiers: (1) Fully remote: AI-native startups, remote-first companies, contract/consulting work. (2) Hybrid (2-3 days onsite): most large tech companies, well-funded startups in tech hubs. (3) Fully onsite: some enterprises, companies with on-prem requirements, roles requiring specialized hardware. The trend: RTO mandates have stabilized. Companies that went hybrid in 2024-2025 are staying hybrid. Fully remote opportunities have decreased but still exist for strong candidates. AI-specific trend: the most cutting-edge AI companies (working on frontier models) often require onsite for security and collaboration.

Choose remote if: you have strong self-discipline and work-from-home setup, you want geographic flexibility (travel, live in preferred location), you're mid-career or senior with established skills, or you're optimizing for lifestyle over maximum compensation. Choose onsite if: you're early career and need mentorship, you want fastest possible career progression, you thrive on in-person collaboration, or you want access to the highest-paying roles in tech hubs. Consider hybrid if: you want some flexibility without full isolation, you're near a tech hub but don't want daily commute, or your company's culture centers on office presence but allows flexibility.

Junior engineers (0-2 years) benefit significantly from onsite work: real-time mentorship, watching senior engineers work, spontaneous learning. Remote junior roles exist but require exceptional self-direction. Mid-level (3-5 years) can work remotely effectively with occasional in-person time. Senior (5+ years) can be fully remote—they've already built the fundamentals and network. The exception: if you're at a remote-first company with strong async culture and dedicated onboarding, junior remote can work.

Remote: no commute saves 1-2 hours/day, but boundaries blur—work can creep into evenings and weekends without physical separation. Onsite: commute adds 1-2 hours/day, but work stays at work with clearer boundaries. Hybrid: middle ground, with commute days requiring more time. Remote workers often report working more hours than onsite workers despite saving commute time. The key to healthy remote work: strict boundaries, dedicated workspace, and intentional 'end of day' rituals.

You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.

Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.

Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.

Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.