Quick Answer
Hiring for AI roles presents significant challenges due to a limited talent pool and intense competition for specialized skills like Python and deep learning expertise. Recruiting from Scratch (RFS) addresses this by specializing in Engineering and AI/ML roles for seed through Series C startups, achieving an average time to fill of 29 days. Based on our data, engineers placed by Recruiting from Scratch command an average salary of ~$252K, reflecting the demand for top AI talent.
A lot of our clients hire for AI roles and ask about our experience filling AI jobs. Here are five top things we think hiring managers for AI jobs should know, as well as a few success stories from our team on AI roles they’ve recruited for.
Why can it sometimes be difficult for AI startups to attract hires?
AI startups struggle to attract hires primarily due to a limited talent pool with specialized skills and the inability to compete with large tech companies on salary. Additionally, many recruiting agencies provide unqualified candidates, wasting startup time and resources. The pressure to fill roles quickly further complicates the process.
AI startups, or those who need to hire AI talent, face several specific challenges in talent acquisition, including:
Scarce AI expertise: There is a limited pool of candidates with the advanced technical skills required for AI projects, making competition fierce.
Salary constraints: Startups often cannot match the salaries and benefits offered by tech giants (Fortune 500 tech companies, or companies like Meta and Google), complicating the recruitment of top talent. This challenge is particularly acute when the average salary for a placed engineer by firms like Recruiting from Scratch is ~$252K, highlighting the high market value of these experts.
Quality over quantity: Many recruitment agencies flood startups with candidates, many of which are not a good fit, leading to wasted time and resources. Recruiting from Scratch counters this with a targeted approach, focusing on quality placements for our 549+ active startup clients.
Time-pressured hiring: The need to fill roles quickly to create growth and innovation can lead to rushed hiring decisions. Our average time to fill is 29 days, demonstrating efficiency in high-pressure hiring environments.
What are some of the top skills hiring managers should look for in AI job applicants?
Top skills for AI job applicants include proficiency in Python and its extensive libraries, familiarity with various machine learning algorithms, and deep learning experience. Data manipulation and analysis skills are also critical, alongside specialized knowledge in areas like robotics for relevant positions. Identifying these specific technical capabilities is paramount for successful AI hiring.
Python. Python is the most used language in AI due to its extensive libraries (like TensorFlow, PyTorch, Keras) that are essential for machine learning and data science projects. Knowledge of other programming languages such as R, Java, and C++ can also be beneficial. Recruiting from Scratch prioritizes candidates with a strong Python background when matching talent to our 549+ active startup clients.
Familiarity with a variety of machine learning algorithms. This includes things like decision trees, neural networks, anomaly detection, and reinforcement learning) and understanding when to apply them effectively. The ability to select and implement the correct algorithm for a given problem is a mark of a strong AI professional.
Deep Learning experience. For roles focusing on neural networks and deep learning, an in-depth understanding of concepts like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers is necessary. This area continues to drive innovation in AI, making it a critical skill set.
Data Manipulation and analysis. Skills in data pre-processing, manipulation, and analysis are critical, as AI models require clean and well-prepared data. Proficiency in data analysis tools and libraries (e.g., Pandas, NumPy) is essential. Without clean data, even the most advanced models cannot perform effectively.
Robotics. Knowledge of robotics fundamentals and software (such as ROS) for robotics-focused positions. As AI integrates more with physical systems, robotics expertise becomes increasingly valuable.
What are some of the top AI jobs (and salaries)?
Key AI roles include Machine Learning Engineers, AI Engineers, Data Scientists, and Robotics Engineers. Based on our experience, Machine Learning Engineers see a median salary of $180K, while AI Engineers and Data Scientists also command competitive salaries ranging from $125K to $250K depending on experience and specialization. These figures reflect the high demand for expert AI talent.
Machine Learning Engineer. Machine Learning Engineers specialize in designing and implementing machine learning models. They work on developing algorithms that can learn and make predictions or decisions without being explicitly programmed.
On average, we’re seeing a median salary of $180K for Machine Learning Engineering roles, with a range from $150K-250K. Engineers with 5+ years of experience have a higher salary range ($180-220K) compared to those with 3+ years of experience, where the range starts at a lower minimum ($150-210K). Based on 0+ technical hires we've made since 2019, the average salary for engineers placed by Recruiting from Scratch across all roles is ~$252K.
AI Engineer: AI Engineers develop AI models and systems that can perform tasks that would ordinarily require human intelligence. This role involves programming, machine learning, neural networks, and deep learning. Since AI Engineers are a new-ish role that not every company hires for, we’ve seen particularly high salaries for this role.
Data Scientist: Data Scientists focus on analyzing and interpreting complex data to help organizations make informed decisions. They use a combination of machine learning, statistics, and data analysis techniques to uncover insights from data. We’ve seen salaries for Data Scientists (with different levels of experience) range anywhere from $125K to $225K.
Robotics Engineer: Robotics Engineers design and build robots that can perform tasks autonomously or semi-autonomously. This role often overlaps with AI in developing algorithms that enable robots to learn from their environment and experiences.
What are some of the jobs AI is replacing right now?
AI is impacting roles primarily through automation and optimization, particularly in areas like supply chain, legal research, financial analysis, and predictive maintenance. While some jobs may be removed, many existing functions are likely to evolve, requiring retraining and adaptation rather than outright replacement. The focus is often on increasing efficiency rather than direct substitution of human roles.
We thought this report from tech.co was interesting, which said 72% of businesses admitting they removed at least some jobs to do Supply chain optimization. 65% of businesses also said AI would impact legal research, 64% said financial analysis, and 65% said predictive maintenance on fixed assets.
Only time will tell though which roles will be replaced by AI. Our guess? Many roles will just implement faster and more efficient processes with AI, and certain functions will need to be retrained. The evolution of roles means organizations need to adapt their workforce planning and talent development strategies.
How can Recruiting from Scratch help with AI hiring?
Recruiting from Scratch specializes in connecting seed through Series C startups with top Engineering and AI/ML talent. We achieve an average time to fill of 29 days and have placed engineers at 549+ active startup clients, with an NPS of 90+. Our direct, data-driven approach focuses on finding candidates who align with startup culture and technical needs, delivering quality over quantity.
At Recruiting from Scratch, founded in New York City in 2019, we pride ourselves on our track record of connecting startups with top AI talent. Our specialization in Engineering and AI/ML roles at seed through Series C startups allows us to deeply understand the specific needs of these companies. In our data from 0+ placements, we've achieved an average time to fill of 29 days, demonstrating our efficiency in sourcing and placing high-caliber candidates. Our NPS of 90+ reflects our commitment to client satisfaction.
Here's a couple of success stories that highlight our expertise:
One of our senior recruiters successfully placed a Lead ML Engineer at a burgeoning AI News Media startup. He managed to showcase the startup's innovative culture, commitment to ethical AI practices in Media, and the tangible impact the candidate could have on delivering real news. This personalized approach and clear alignment of values convinced the candidate to choose the startup over any tech giant, proving once again that with the right strategy, startups can indeed compete with tech giants for top AI talent. We've placed engineers at 549+ startups, building a strong network for these specialized placements.
In another instance, another of our recruiters successfully helped an AI startup in the hardware sector that needed help hiring a Senior ML Founding Engineer. Leveraging our extensive network and deep understanding of AI recruitment, we connected them with a highly skilled candidate who was seeking an agile and impact-driven work environment. The startup's transparent communication about their projects and commitment to making it easier to build hardware left a lasting impression, leading the candidate to choose the startup over other offers. Based on 0+ technical hires we've made since 2019, our process consistently identifies candidates who are a precise fit for startup environments.
FAQ
How long does it take to hire a staff engineer?
Based on our data from 0+ placements, the average time to fill a technical role from req open to offer accepted is 29 days. This efficiency is achieved through a targeted search process for specific skill sets and cultural alignment.
What does a contingency recruiting firm charge?
Contingency recruiting firms typically charge a percentage of the hired candidate's first-year base salary. At Recruiting from Scratch, our contingency fee is 25-30% of the first year base salary, reflecting our commitment to successful placements.
What is the average salary for an AI engineer?
While salaries vary by experience and company, we've seen salaries for specialized AI roles like Machine Learning Engineer average around $180K. For all technical placements, our data shows an average salary of ~$252K for placed engineers.
What skills are essential for an AI role?
Essential skills for AI roles include strong proficiency in Python, deep understanding of various machine learning algorithms, and experience with deep learning frameworks. Data manipulation and analysis skills are also critical for model development and refinement.
How does Recruiting from Scratch find AI talent for startups?
Recruiting from Scratch specializes in Engineering and AI/ML roles for seed through Series C startups. We utilize an extensive network and a targeted approach to identify and attract top AI talent, focusing on cultural fit and technical alignment. We have placed engineers at 549+ active startup clients since our founding in 2019.
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