Attracting Top Talent to Fill AI Teams

AI powered Insurance Claims
Too Many High Caliber Candidates.

An AI first startup aiming to revolutionize the insurance industry by changing the way insurance claims are handled, moving from human-based reasoning to data-driven optimal handling. We were tasked on doubling their current AI team of 15 to 30. After 2 months, we not only got them exceptional candidates but also gave them AI compensation landscape details to attract them.

See the High Caliber Talent and how they got interested
Exceptional Results within 2 Months

Reviving the Hiring Pipeline with the Top Talent from the Top Companies

Before working with AITA

Extremely difficult to attract critical AI/ML Hires at all Levels
Low candidate pipeline (Only 7 candidates, none excited about)
Unqualified applicants
50+ hrs/week wasted screening and sourcing uninterested or unqualified
Did not know where to find AI candidates with specific experience
Did not know AI engineering compensation levels, target companies, and AI engineering hiring best practices
Understaffed and overworked internal recruiting team
“Results have shown us that AITA attracts candidates of higher quality. I don't know how they do it.
CEO, AI Powered Insurance Claims Company

After 2 Months with AITA

Updated compensation to be competitive based on the caliber of the top talent
4850 qualified senior level AI engineers contacted
58 Exceptional Candidates Submitted
3501 Opens for Outreach Emails
(72% Open Rate)
849 Responses from AI / ML Engineers
(24% Response Rate)
208 Interested from just outreach
Screen / Submit only the top 10-20%
(22 Exceptional Candidates including PhDs and FAANG)
42 Interviews scheduled
Serious about growing your Team? We can help!
Profile of our Client

Client's AI Hiring Plan

Founded by a senior Google AI expert (9+ years at Google), the company is looking to double their team of 15 AI engineers by the end of the year with a focus on attracting and recruiting senior level AI talent.

Founded in 2019.
Current Company Size: 27 Employees
Current AI Team: 15 Engineers ranging from Director of Data Science to Applied ML Engineers
Objective: Senior Applied Machine Learning Engineers, Senior Data Scientists, and some lower level ML roles.
Timeline on our Exceptional Results

“Finding top talent is just the start. We know how to get them interested in your company.”

Michael, Director of Recruiting at Artificial Intelligence Talent Agency
Day 0 - Initial Onboarding Call
We discovered AI engineering hiring challenges, hiring ops improvements, and profiles for AI roles. We kicked-off outreach to our massive AI candidate network within 24 hours.
Day 7 - Hiring Pipeline grew from 7 to 22 Candidates
After 7 days, we grew their pipeline with 6 exceptional candidates. Our client, started scheduling out interviews with the new candidates.
Day 15 - Pipeline grew to 25 and Reviewed Compensation Landscape with their CEO and AI Team to Better Attract Candidates
By the 15th day, we grew the pipeline to 25, but we noticed a trend for the compensation being to low for the high caliber talent. Met with their team to discuss the AI engineer compensation landscape.
Day 30 - Revamped Compensation and Reached Back to All Candidates
At the end of the first month, the team updated their compensation by 50% for base salary. Immediate results came in the same day from the new updated compensation campaigns.
Day 62 - Pipeline grew to 65 (More Than Double the First Month).
22 Candidates from FAANG and PhDs with the relevant experience.
At the end of 62 days, we grew the pipeline to 65 candidates (40 from updated compensation campaigns). 22 are highly qualified from FAANG and PhDs with production experience. Company needs help optimizing their hiring ops, and AITA provides as much insight to make the process as smooth as possible.
A Few Profiles of our Top candidates at the Senior+ Level

Production-Grade Machine Learning, Top Companies, and Perfect-Fit Expertise

Tech lead for a team of 5 on a project to automate a deep learning recommendation model generating over $200MM in annual product sales.

Strong current tenure
(4 years FAANG)
Software Engineer, Machine Learning at Amazon
PhD in Mathematics

8+ Years of Industry experience with computer vision and machine learning.

FAANG (Working at Apple and at Amazon before)
Senior Machine Learning Scientist at Apple
7+ Years of Industry experience of applying ML for production.

Tech Lead for Communications AI systems that supports about 8 different products.

MS in Computer Science
Machine Learning Engineer at LinkedIn
Ph.D. Computer Science, Machine Learning - GPA 3.98

Machine Learning Scientist with 15 yrs experience leading research and engineering projects.

Strong current tenure
(6 years FAANG)
Senior Machine Learning Scientist at Amazon

We loved working with them, let's work with you!

We are excited and ready to grow ambitious AI companies across the United States. We look forward to jumping on a call and putting your company & mission in the minds of 10,000+ of candidates.