Interested in this AI Safety role at Biohub?
Apply Now →About This Role
Biohub is the first large\-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general\-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.
The Team
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Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state\-of\-the\-art AI to accelerate discovery and drive transformative insights in biology—developing novel AI models purpose\-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide.
Our approach is comprehensive and integrated, bringing together world\-class AI model development, exceptional engineering talent, high\-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world\-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools.
The Opportunity
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This is an opportunity to shape the future of biological research by pushing the boundaries of what AI can achieve in science. You'll work alongside leading experts in AI and biology, with the resources and mandate to tackle some of the most important questions in human health—advancing frontier AI research, accelerating engineering velocity, connecting rich biological data to AI systems, enabling reliable compute across environments, and translating models and data into usable, scalable applications that drive scientific impact for the public good.
The Staff Research Scientist is part of the AI Research team, which focuses on training AI models in biology and reasoning at the frontier of data, scale and compute. We are a mostly flat organization of researchers to enable rapid and dynamic AI development.
What You'll Do
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- Rigorously think through important open scientific questions that don't have textbook answers.
- Design and build safety evaluations to understand AI capabilities at the frontier of biology.
- Collaborate closely with scientists across Biohub to build safeguards that are robust to potential misuse, enabling our AI systems to be used for maximum societal benefit .
- Gain direct access to a network of leading external experts and Biohub partners for collaboration and to inform your safety work.
- Monitor capability advancements and emerging technologies across AI and assess how these advances impact the robustness of our safeguards.
- Partner closely with colleagues to develop, implement, and evolve our frontier safety policy.
- Communicate our safety work to internal teams as well as external partners.
What You'll Bring
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- PhD in computer science or a related field, or equivalent experience.
- Expertise in biological sciences.
- Significant experience building, using, and/or evaluating deep learning systems, ideally in research\-driven environments.
- Strong engineering and scientific fundamentals.
- Comfort with ambiguity, rapid iteration, and loosely\-defined research problems.
- Strong communication skills across technical and scientific audiences.
- Interest in shaping the frontier of safety for AI \& biology, no prior safety experience required.
Compensation
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The New York City, NY base pay range for a new hire in this role is $241,000 \- $301,000\. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job\-related skills and experience, as evaluated throughout the interview process.
Pay ranges outside New York City, NY are adjusted based on cost of labor in each respective geographical market. Your recruiter can share more about the specific pay range for your location during the hiring process.
This position may be eligible to participate in our discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with our total rewards philosophy and may vary by role.
Better Together
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As we grow, we're excited to strengthen in\-person connections and cultivate a collaborative, team\-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in\-office days determined by the team's manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
Benefits for the Whole You
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We're thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
- Provides a generous employer match on employee 401(k) contributions to support planning for the future.
- Paid time off to volunteer at an organization of your choice.
- Funding for select family\-forming benefits.
- Relocation support for employees who need assistance moving
If you're interested in a role but your previous experience doesn't perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
\#LI\-Hybrid
Salary Context
This $241K-$301K range is above the median for AI Safety roles in our dataset (median: $262K across 8 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 4,317 AI roles we're tracking, AI Safety positions make up 0% of the market. At Biohub, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills in Demand for This Role
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Safety roles pay a median of $287,500 based on 34 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($271K) sits 6% below the category median. Disclosed range: $241K to $301K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include Research Engineer ($272,100) and AI Engineering Manager ($244,000). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Biohub AI Hiring
Biohub has 1 open AI role right now. They're hiring across AI Safety. Based in New York, NY, US. Compensation range: $301K - $301K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into AI Safety roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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