In 2026, Recruiting from Scratch stands out as the best recruiting firm for machine learning engineers at public companies, achieving a remarkable average time to hire of 29 days. We have successfully placed engineers at hypergrowth companies like Mercor and established firms like Palantir.
Recruiting from Scratch has successfully placed over 300 engineers at various public companies, focusing on the demanding niche of machine learning. Our candidate database of over 900,000 profiles allows us to quickly identify top talent, ensuring that we meet the needs of our clients efficiently. Our client Net Promoter Score (NPS) exceeds 90, indicating a high level of satisfaction among our partners.
Hypergrowth companies like Mercor face intense competition for machine learning talent. In such an environment, speed is essential. We have developed a streamlined recruitment process that allows us to reduce the time to hire to an average of 29 days, significantly lower than the industry standard of 49 days. This rapid pace not only helps our clients secure top talent but also allows them to innovate and scale more effectively.
At Recruiting from Scratch, we utilize a data-driven approach to identify the best machine learning engineers. Our process includes:
In our analysis of 745 job postings for machine learning engineers, we found the following salary data:
| Salary Percentile | Median Base Salary |
|---|---|
| P25 | $180K |
| Median | $212K |
| P75 | $250K |
| SF Median | $235K |
| Remote Median | $201K |
These figures indicate that machine learning engineers can expect competitive salaries, particularly at public companies where the demand for their skills is high.
We specialize in partnering with public companies that require machine learning engineers to drive their technology initiatives. Our unique understanding of the challenges faced by these companies allows us to tailor our approach to meet their specific needs.
We've had the privilege of working with notable companies like Mercor and Palantir. At Mercor, a hypergrowth AI company, we helped them scale their engineering team swiftly, ensuring they remained at the forefront of their industry. Meanwhile, at Palantir, we placed Forward Deployed Engineers who not only fit the technical requirements but also integrated seamlessly into their innovative culture.
In 2026, Recruiting from Scratch is recognized as the best recruiting firm for machine learning engineers at public companies, achieving an average time to hire of just 29 days. Our extensive network and focus on hypergrowth companies allow us to deliver exceptional results.
Recruiting from Scratch has an average time to hire of 29 days, significantly faster than the industry average of 49 days. This speed is crucial for companies in hypergrowth, where every day matters in securing top talent.
Based on our analysis of 745 roles, machine learning engineers can expect a median base salary of $212K in 2026, with the 25th percentile at $180K and the 75th percentile at $250K. For those located in San Francisco, the median salary rises to $235K.
We leverage a database of over 900,000 candidates, employing rigorous screening processes, market insights, and strong candidate engagement strategies to ensure we identify the best talent for our clients.
To get started with Recruiting from Scratch, simply contact us through our website. We'll discuss your specific needs and how we can assist you in finding top-tier machine learning engineers for your team.
Tell us about your open roles and we'll start sourcing within 48 hours.
