%20(2).png)
Recruiting from Scratch (RFS) founder Will Sanders recently appeared on The Thoughtful Entrepreneur Podcast to discuss the intricacies of contingent recruiting, the current challenges faced by growing startups in talent acquisition, and Recruiting from Scratch's data-driven approach to placing specialized engineering and AI/ML talent efficiently. Since its founding in 2019, Recruiting from Scratch has developed a process that achieves an average time to fill of 29 days for engineering roles, working with over 549 active startup clients and maintaining an NPS of 90+. The discussion highlighted how Recruiting from Scratch addresses the demand for high-caliber talent, often at average salaries around ~$252K for placed engineers, even in a competitive market for hard-to-fill positions.
Our founder Will Sanders was recently featured on The Thoughtful Entrepreneur Podcast with Josh Elledge. On this episode, Will and Josh discuss:
* What Recruiting from Scratch does as a contingent recruiting firm
* The challenges that recruiting teams and growing startups face today
* The process of recruiting and how Will's team works
* How clients are hiring in today's market and how there are still hard-to-fill roles
Contingency recruiting is a model where a recruiting firm is paid only if they successfully place a candidate with a client company. Recruiting from Scratch operates as a contingent recruiting firm, specializing in identifying and placing top-tier technical talent, specifically for Engineering and AI/ML roles. Our model aligns our success directly with that of our clients, ensuring we deliver qualified candidates who are a precise fit for the startup's needs.
Founded in 2019 in New York City, Recruiting from Scratch has quickly established itself by focusing on a specific niche within the startup ecosystem. We serve seed through Series C startups, understanding the unique hiring velocity and cultural fit requirements of early-stage, high-growth companies. This specialization allows us to build deep networks of candidates and market intelligence relevant to this segment. We engage with 549+ active startup clients, demonstrating our extensive reach and experience within this fast-paced environment.
Our contingency fee structure is straightforward: 25-30% of the placed candidate's first-year base salary. This fee is only incurred upon a successful hire, mitigating financial risk for our client startups. The contingent model means we are incentivized to find the right candidate quickly and effectively, ensuring that our efforts translate directly into a valuable hire for the client without upfront costs or retainers. This approach is particularly beneficial for startups that need to manage cash flow while still needing access to high-quality, specialized talent that is difficult to source through general channels.
The Recruiting from Scratch operational model is built on efficiency and precision. We commit resources to understanding the specific technical requirements and company culture of each of our 549+ active startup clients. This deep understanding enables us to present candidates who are not just technically proficient but also align with the startup's long-term vision and team dynamics. Our specialization in Engineering and AI/ML roles means our recruiters possess an acute awareness of the skills and experience necessary for these critical positions, distinguishing us from generalist recruiting firms. This targeted approach is foundational to achieving our rapid placement times and high client satisfaction.
Startup recruiting, especially for technical roles, presents distinct challenges that can significantly hinder growth if not addressed effectively. One of the primary difficulties is the protracted time it often takes to fill critical positions. Many companies experience hiring processes that can extend for months, resulting in lost productivity and missed opportunities. Based on 0+ technical hires we've made since 2019, Recruiting from Scratch has observed an average time to fill of just 29 days from req open to offer accepted. This metric highlights a key area where Recruiting from Scratch provides significant value, drastically reducing the impact of slow hiring on startup operations.
Another significant challenge is the scarcity of specialized talent, particularly for Engineering and AI/ML roles. As technology advances, the demand for highly skilled professionals in areas like machine learning, data science, and specialized software engineering continues to outpace supply. Startups, with their often limited brand recognition compared to larger tech companies, struggle to attract these candidates. Our specialization directly addresses this by maintaining a focused network of candidates skilled in these hard-to-find areas.
Compensation expectations also pose a challenge. Top technical talent, particularly those experienced in cutting-edge fields, command substantial salaries. For instance, based on 0+ placements, we've seen an average salary for placed engineers at approximately ~$252K. Startups must be prepared to offer competitive compensation to attract and retain these individuals. Recruiting from Scratch provides market insights and salary benchmarking to our 549+ active startup clients, helping them craft attractive offers that secure desired candidates without overspending. This expertise is particularly valuable for seed through Series C startups that need to be strategic with their limited resources.
Beyond pure technical skill, cultural fit is paramount in the fast-paced, collaborative environment of a startup. A technically brilliant candidate who does not align with the company's values or working style can disrupt team dynamics and productivity. Our process includes a thorough evaluation of cultural alignment, ensuring that candidates not only meet technical specifications but also contribute positively to the client's existing team. Addressing these challenges requires a strategic, data-informed approach, which is precisely what Recruiting from Scratch provides to its clients, ensuring efficient, high-quality placements.
Recruiting from Scratch achieves its efficient hiring times, with an average time to fill of 29 days from req open to offer accepted, through a highly specialized and data-driven process. Our methodology is refined through experience gained from working with 549+ active startup clients and is specifically tailored for Engineering and AI/ML roles at seed through Series C startups. This specialization is a foundational element in our ability to rapidly identify and qualify top talent.
Our process begins with a deep dive into the client's technical requirements, company culture, and strategic goals. We go beyond simple job descriptions to understand the nuances of the role and the team it will be joining. This comprehensive intake ensures that our search is precisely targeted from the outset. Rather than casting a wide net, we focus on a curated pool of candidates who possess the specific skills and experience needed, dramatically reducing the time spent reviewing unqualified applications.
Our team of recruiters is dedicated solely to Engineering and AI/ML roles. This focus means they possess an intricate understanding of these technical domains, enabling them to speak credibly with candidates and accurately assess their capabilities. Based on 0+ technical hires we've made since 2019, our expertise allows for faster initial screening and more effective communication with both clients and candidates. This specialized knowledge is critical for roles where the average salary for placed engineers is around ~$252K, indicating a high level of expertise required.
Furthermore, our extensive network, built since our founding in 2019, provides direct access to passive candidates who are not actively seeking new roles but are open to the right opportunity. We proactively engage with these individuals, fostering relationships that allow us to present compelling opportunities quickly when a client need arises. This proactive sourcing strategy significantly reduces the passive waiting time often associated with traditional recruiting methods.
Client collaboration is also a key factor. We maintain transparent and continuous communication with our clients throughout the hiring process, providing regular updates and feedback. This ensures that any adjustments to the search can be made promptly, preventing delays. Our commitment to client satisfaction is reflected in our NPS of 90+, which demonstrates the effectiveness and reliability of our process in delivering not just speed, but also quality placements that meet long-term strategic needs. This blend of specialization, data-informed strategy, and proactive engagement is how Recruiting from Scratch consistently delivers rapid results.
Hard-to-fill engineering roles in startups typically involve highly specialized skills, significant experience, or expertise in emerging technologies. At Recruiting from Scratch, our specialization is precisely in these areas: Engineering and AI/ML roles at seed through Series C startups. These positions are challenging to staff due to a limited talent pool, high demand, and the specific needs of early-stage companies for individuals who can operate with autonomy and contribute immediately.
Within our specialization, AI/ML engineering roles are consistently among the most difficult to fill. These positions require a unique blend of theoretical knowledge in machine learning, statistical modeling, and practical software development skills. Candidates must often be proficient in specific frameworks (e.g., TensorFlow, PyTorch) and possess experience with large datasets and complex algorithms. The talent market for these roles is highly competitive, contributing to high compensation packages. Based on 0+ placements, the average salary for engineers placed by Recruiting from Scratch is approximately ~$252K, reflecting the premium placed on these specialized skills.
Senior and Staff level engineering roles also fall into the hard-to-fill category. These positions demand not only technical mastery but also leadership capabilities, architectural design experience, and the ability to mentor junior engineers. Startups need these individuals to drive technical direction and build scalable systems, but the number of engineers with this blend of experience is scarce. Our 549+ active startup clients frequently seek these senior contributors to accelerate their product development and establish robust technical foundations.
Front-end and back-end roles requiring deep expertise in specific, less common languages or frameworks can also be challenging. While generalist developers are available, finding someone with several years of experience in, for example, Rust or Elixir, or specific distributed systems architecture, often requires a targeted search. Since our founding in 2019, Recruiting from Scratch has developed extensive networks in these specific technical communities, enabling us to pinpoint candidates who possess these niche skill sets. The 29-day average time to fill achieved by Recruiting from Scratch even for these complex roles underscores our effectiveness in navigating these challenging segments of the talent market. The consistent demand for these roles means that even with 0+ placements, the market insights gained are substantial, guiding our search strategies and client advisory.
Listen to the full episode on Apple Podcasts or Josh's website, UpMyInfluence.
To learn more about Josh Elledge, visit his website at upmyinfluence.com. Thanks for hosting Recruiting from Scratch, Josh!
Tell us about your open roles and we'll start sourcing within 48 hours.
.jpg)
