Jobiak Founder Venkat Janapareddy: Building an AI-Powered Marketplace for Job Optimization and Distribution

How Jobiak's AI helps companies to optimize job posts and increase conversion.

Yuliya Sychikova
COO @ DataRoot Labs
11 Jun 2020
10 min read
Jobiak Founder Venkat Janapareddy: Building an AI-Powered Marketplace for Job Optimization and Distribution

Venkat Janapareddy is the CEO and Founder of Jobiak, the industry’s first AI-based recruitment marketing platform designed to allow recruiters and talent acquisition teams to quickly push their job posts to Google for Jobs, optimize the content for maximum visibility, and A/B test those posts to ensure the highest quality application process.

Founded in 2018, Jobiak raised $2.3 million in Seed funding round led by a group of private investors and successful entrepreneurs. The founder, Venkat Janapareddy, has invested an additional $500k in this round. Jobiak is headquartered in Woburn, MA, with international offices in India.

How was the idea of Jobiak born? Why have you decided to found the startup?

Venkat Janapareddy: I have been in the resource augmentation and job tech business for the past 20 years with two successful exits under my belt. I am very passionate about this industry and always inquisitive about the opportunities that the changing landscape presents. I saw a huge opportunity with the shift of looking for jobs on search engine and social media platforms instead of the traditional means such as job boards.

The idea of Jobiak was formed with the launch of Google for Jobs which required enterprises to follow a specific schema to post their jobs. This evolved into a bigger vision of Jobiak becoming the global marketplace for job optimization and distribution.

Jobiak’s machine learning is designed to optimize job posts for top 20 ranking on Google for Jobs resulting in 4x more applications and 3x conversion. How does your ML actually work? Where does the data come from and how does the algorithm improve the ranking and conversion?

Jobiak automatically optimizes job posts for high ranking using machine-generated keywords, titles and descriptions, based on analysis of both real-time information and learnings from millions of monitored postings. Jobiak’s advanced Artificial Intelligence (AI) powered machine learning (ML) tools are designed specifically for job postings, scouring millions of job descriptions to ensure a high degree of accuracy.

Our platform has been trained to automatically recognize all of the key Google tag attributes including title, job location, job description, date posted, and hiring organization. Once identified, Jobiak automatically transforms those attributes into the required HTML and JSON schema tags. Next, Jobiak embeds each tag within the job posting, publishes the page to the web, and then signals to Google to crawl this new job post.

While Jobiak’s AI patent backed model may appear to be a simple solution for recruiters, it is composed of 400,000 man-hours of data collection that scoured three million of job descriptions to ensure a high degree of accuracy, and is trained on a daily basis to generate high-performing keywords and make real-time SEO adjustments based on local market demand.

Jobiak’s sophisticated modeling accounts for over 25 “signals” that factor into Google for Jobs rankings. It automatically optimizes job posts for the highest rank mathematically possible, using machine-generated keywords, titles and descriptions, based on analysis of both real-time information and learnings from millions of monitored postings.

Jobiak is currently the only solution in the recruiting industry with the power to fully automate and dynamically optimize listings on Google for Jobs, in real time, in as little as 48 hours.

Jobiak is currently the only solution in the recruiting industry with the power to fully automate and dynamically optimize listings on Google for Jobs, in real time, in as little as 48 hours.

Venkat Janapareddy

Founder & CEO @ Jobiak

Currently Jobiak employs over 150 people across the US and India. What do most of the employees do? How big is your AI team and what are their key challenges?

80% of our employees are engineers and 30% of them work on our platform and 70% of them work on ML, feature engineering and training our ML models. AI and ML skills are still relatively new and hiring has been the biggest challenge for us.

Google for Jobs has been launched in 2017 and currently rolled out in 120+ countries including the UK and the US. Do you foresee the platform to pose a formidable competition to job aggregators? Which job tech verticals are most likely to be disrupted by this Google product?

Over 73% of all job searches start on Google. 34% of all job searches drop off due to the inefficiencies of the current process of connecting job seekers with job givers. We believe Google is in a great position to capitalize on this situation by connecting the candidates directly with employers and thereby create a great job seeking experience. All intermediaries, especially job boards, need to adapt in order to survive, keeping in mind the changing needs and current pain points faced by the stakeholders.

Even the market leader Indeed is at risk of losing a substantial share of its current market if Google, Facebook and Microsoft were to partner with Jobiak which will enable them to capture every online job, optimize and make them available to job seekers in their search results.

Do you plan to work with other platforms aside from Google for Jobs?

Jobiak is an AI-driven, ML based job tech platform which has been built for aiding social and search platforms to directly connect candidates with enterprises. Our goal is to help the entire recruitment ecosystem meet their specific goals by being THE global marketplace for job optimization and distribution. Whilst Google for Jobs is currently the biggest opportunity, companies like Facebook for Jobs, Bing for Jobs, Twitter etc. can equally benefit by partnering with Jobiak.

Our goal is to help the entire recruitment ecosystem meet their specific goals by being THE global marketplace for job optimization and distribution.

Venkat Janapareddy

Founder & CEO @ Jobiak

Congrats on the recent fundraising round closed in November 2019! What features are next for your clients? What do you hope to achieve 3-5 years from now as an organization?

We are currently meeting our industry leading success metrics on posting, ranking jobs and generating applications for enterprises. This has been our immediate goal which we are consistently accomplishing. Our next goal is to be able to scrape and optimize every online job there on career sites which is waiting to be filled. Within 3-5 years, our goal is to be the #1 AI-driven, ML based global marketplace for job optimization and distribution (very similar to global distribution systems i.e. Sabre, Amadeus, Travelport etc.).

What are you most proud of as a founder?

As a serial entrepreneur, I’ve always enjoyed finding opportunities that are disruptive to the HRTech industry and going through the whole start-up journey which can be challenging at times. My background in recruiting and staffing and my interest in applying ML technology to simplify hard problems helped me become more successful.

What resources (books, publications, movies) can you recommend to a founder just starting AI-driven business?

I love Office Space movie and HBO Silicon Valley. They are fun and showcase start-up life and ups/downs of being an entrepreneur. I really like deepmind blog. There are a lot of blogs on our site on Google for Jobs and you might find some of them very helpful especially this one.

Now, as you very well know, there is a certain unease among people about AI in general as AI is expected to replace jobs. Jobiak makes it very easy for recruiters, talent acquisition teams and HR professionals to use a complex tool. Does it mean that their job functions are becoming more “nominal” and less essential? Do you think that Jobiak is contributing to replacing the jobs problem widely discussed in the media or transforming the rules of Job tech for all?

Jobiak’s primary target end user is the recruiter who is currently struggling to win the talent war cost effectively and in a timely fashion. Jobiak is targeting the individual recruiter and talent acquisition managers within a company. We believe this is an underserved community starving for solutions for their day to day challenges. They are focused on getting qualified candidates into their pipeline as quickly and efficiently as possible.

They have to rely on stretched and limited IT resources, to do the necessary coding and maintain the required jobs schema, for Google for Jobs to be an effective recruitment channel. Our goal is to remove/reduce recruiters` reliance on IT resources, which sometimes adds substantial delays in fulfilling critical time-bound jobs and become self-sufficient in meeting their recruitment goals. In addition, our fully automated tool allows recruiters to focus more on planning and strategy and less on clerical tasks thereby improving their overall productivity substantially.

The job search has changed dramatically in the past few decades. The power was transferred from physical job boards to internet job boards and now to job aggregators. AI is certainly speeding up the change and, most importantly, empowers those with most data. What in your opinion will we see in the next 5 years? Who are the new market winners and losers?

Google, Bing and Facebook have entered the jobs space and they want to disrupt the job industry and fundamentally change how job seekers connect with employers; I expect more than 80% of job seekers applying for jobs on these three platforms in five years.

Author

Yuliya Sychikova
COO @ DataRoot Labs
Yuliya is a co-founder and COO of DataRoot Labs, where she oversees operations, sales, communication, and Startup Venture Services. She brings onboard business and venture capital experience that she gained at a leading tech investment company in CEE, where she oversaw numerous deals and managed a portfolio across various tech niches including AI and IT service companies.

Co-Authors

Ivan Didur
CTO @ DataRoot Labs
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Yuliya Sychikova
COO @ DataRoot Labs
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