LiftIgniter is a tight-knit team excited about solving real world problems with math and engineering.

Our team of top engineers has direct experience building state-of-the-art personalization systems at scale. We make it easy for publishers & e-commerce to harness the same techniques as Google, Amazon, and other consumer web pioneers. Born out of the top machine learning personalization teams at Google, LiftIgniter’s mission to enable better, more engaging user experiences by enabling content creators to put the best content and items in front of each individual user at each click. Websites & apps should react in real-time to their users.

Part of YCombinator’s winter 2014 class, we raised funding from some of Silicon Valley’s best investors. LiftIgniter is dynamic. LiftIgniter learns. LiftIgniter adapts to your changing users and changing content. LiftIgniter optimizes for the highest click-through-rate, engagement, reduced bounced, sharing, and conversion. Create brand affinity. Personalization is revolutionizing the Internet. Be part of the change.

Our Team


Indraneel Mukherjee
Founder & CEO

Indraneel loves to apply mathematical insights to solve hard real life problems. Prior to LiftIgniter, he worked in a small team at Google that pushed the boundaries of machine learning research and infrastructure by building one of the world’s largest personalization engines. Ever the geek, he participated in major programming competitions in high school, and went on to get a PhD in theoretical machine learning from Princeton. His research in boosting can be found here. He won the “Outstanding Student Paper” award at NIPS 2010 and had the high honor of an invitation to lecture at the same conference. In his spare time, he enjoys running and playing soccer.


Adam Spector
Co-Founder & Head of Business

Excited about building & creating, Adam joins LiftIgniter from Henge Docks where he was Chief Operating Officer. Adam previously ran his own social data science company, and did business development at Clearwell Systems, an e-discovery company that sold to Symantec for $400m. Before moving to California, Adam worked at Neustar, a trusted, neutral provider of real-time information. Adam holds a JD & MBA plus dual-majored with minor in undergraduate from the University of Miami and Vanderbilt. In his free time, Adam can be found scuba diving (he’s a board member of the Coral Restoration Foundation), reading, and skiing.


Vipul Naik
Head Data Scientist

Passionate about math since childhood, Vipul has won top medals, multiple times, at the prestigious International Math Olympiad, and holds a PhD in Math from the University of Chicago where his thesis was in group theory. His work in machine learning involves applying powerful math tools to achieve immediate real world impact. At LiftIgniter, he is developing cutting edge algorithms for massive datasets that provide dramatic improvements in cost as well as performance. In his spare time, he enjoys contributing to Wikipedia, reading about economics and psychology, and composing music.


Eric Johnston
Software Engineer

Eric enjoys the challenges that come when merging the mathematics of machine learning with the technical problems of building high performance, distributed systems. At Stanford, he double majored in physics and electrical engineering before focusing on machine learning for his masters degree. Prior to working at LiftIgniter, Eric built out a distributed platform for analyzing and classifying massive numbers of malicious files at FireEye. Outside of work, he enjoys rock climbing and biking and trying not to twist his ankle.


Eugene Lee
Software Engineer

Eugene likes math…enough to finish BSc. in Applied Math and BA in Pure Math at Brown University. He started programming in high school at a University lab in Korea Advanced Institute of Science and Technology, where he developed Android applications related to Ubiquitous Computing. Eugene lived throughout Denmark, Korea, and Rhode Island until he came to San Francisco Bay area and found an awesome home at LiftIgniter. Outside of work, Eugene likes playing video games and watching animations. He plans on going outdoors in the near future.


Yonathan Randolph
Software Engineer

Yonathan likes to make things more efficient and dive in to get to the bottom of problems. He finds infrastructures (and their speed & scalability) fascinating. Prior to Liftigniter, Yonathan made data capture programs at Acuitus and worked on book search at Google. He holds a BS in Electrical Engineering and Computer Science from the University of California, Berkeley. He loves coupons and deals and cooks a fair amount when time allows.


Shawn Naggiar
Chief Revenue Officer

Shawn joins LiftIgniter with over 22 years experience in technology go-to-market. Most notably, he was with WebEx for 6+ years before its acquisition by Cisco for $3.2B. After WebEx, Shawn was the first non-engineer to join marketing automation leader, Act-On. After personally signing the first 30 customers, his team grew to over 330 people across 3 continents in 4 years. Together, the team acquired and supported over 3,000 paying customers and received countless awards for growth and customer satisfaction. Shawn often dates himself with colleagues by talking about Terminal Emulation Software or saying things like “I remember when Al Gore invented the internet”.

team-Won Jun Bee

Won Jun Bee
Software Engineer

Wonjun loves to work on cool new products people love to use. Prior to Liftigniter, he worked at a corporate wellness startup and a product discovery startup. He also worked on several AAA video games such as Dead Rising 2, Monster Lab, Activision Hits Remixed, Fifa World Cup: Germany 2006, and SSX on Tour. He holds a B. Eng in Computer Engineering from McGill University. Outside of work, Wonjun likes to travel and walk around new places.

team- Eric Schilling

Eric Schilling
Senior Personalization Specialist

Eric is a veteran sales executive with a successful and consistent track record selling SaaS based solutions for 18+ years. His sales experience started with PeopleSoft Inc. and he quickly became a serial Top Performer and continued his success throughout his career at Act-On Software, an industry leading marketing automation platform where he was employee #20.

Eric continued his career in sales with Oracle where he was again a Top ASM Performer selling their Customer Experience (CX) Cloud Solutions and most recently he served as Director of Sales for startup Collective[i], a machine learning/AI platform for Sales Leaders.

When Eric isn’t working he enjoys running, biking and spending his time with his wife, daughter and two large dogs in Northern California or at their cabin in Lake Tahoe.

team-Jason Demant

Jason Demant
Senior Personalization Specialist

Before joining LiftIgniter Jason was the founder and CEO of Bento which he grew to a $1.3M run-rate business. Prior to that, he was CEO of LAUNCH Media where during his tenure, the company doubled revenue as well as the size of the team. When not in front of the computer or on the phone, Jason is the proud father of 2 young daughters and enjoys playing basketball.

team-Tim Parsons

Tim Parsons
Senior Personalization Specialist

Born and raised in the Silicon Valley, Tim is a proven and successful sales executive who enjoys competition and the excitement of disruptive startups. Graduating from Cal Poly SLO, he embraced the entrepreneurial lifestyle building his own sales agency representing the top lifestyle and action sports brands. After successfully selling his online e-commerce company he joined Act-On and consistently lead the team in their record breaking sales growth. His next startup took him into the world of AI, so joining Liftigniter was a perfect fit to bring his passion and experience to the team.

In his free time Tim enjoys spending time with his wife and two young sons where they can often be found outdoors, snowboarding, boating, wakesurfing, mountain biking and traveling.

team-Jeff Isgrig

Jeff Isgrig
Senior Personalization Specialist

Jeff has been in technology sales and account management for more than 20 years. Jeff has been instrumental in the growth, coaching, and development of sales teams and strategies for companies like Cisco Systems, WebEx, E*TRADE, Forte Design, and Act-On. With a strong track record of exceeding revenue goals and fostering long term customer relationships, Jeff prides himself most on deeply understanding his customer business, challenges, and opportunities to deliver solutions with unquestionable value and ROI. Jeff just celebrated his 13th wedding anniversary and is a proud father of 2. He calls Northern California home and enjoys spending his free time exploring the great outdoors with his family, reading, bike riding, golfing, and bowling.

team- Ernie Bayless

Ernie Bayless

Ernie is no stranger to the adrenaline rush of tech startups. He was most recently with Act-On Software, an industry leader in marketing automation software. Prior to Act-On he served as Vice President of Strategic Sales with Texas based software provider, Remote Dynamics, Inc. NASDAQ (REDI). Ernie also held the position of President and CEO of Vericom Technologies, a New York Based GPS hardware provider. Ernie experienced the thrill of an IPO while working as Vice President of Strategic Sales for Silicon Valley based @Road NASDAQ (ARDI). He is an avid golfer and claims to be terrible at the game.

team-Jonathan Evans

Jonathan Evans
Senior Personalization Specialist

Jonathan is a tech veteran, with over 84 quarters of providing value to customers and making them smile. Born and raised in Canada, Jonathan and his family immigrated to Silicon Valley in 2005. His straightforward and consultative approach to sales and customer service has allowed him to be a top performer throughout his career. He has proudly helped start-up companies hit needed growth while fostering long term relationships with enterprise clients and partners. Jonathan is about to celebrate his 25th anniversary and is a proud father of 4 amazing boys and just recently became a grandfather. Jonathan spends much of his free time giving back by supporting national and local charities. He is most passionate about his work with the Kidney Foundation as he was the recipient of a kidney transplant in 2014. Jonathan credits the foundation with his walking the earth today. #thankful

Our Advisors

David Blei

David Blei is a Professor of Statistics and Computer Science at Columbia University. His research is in statistical machine learning, involving probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference algorithms for massive data. He works on a variety of applications, including text, images, music, social networks, user behavior, and scientific data.

David earned his Bachelor’s degree in Computer Science and Mathematics from Brown University (1997) and his PhD in Computer Science from the University of California, Berkeley (2004). Before arriving to Columbia, he was an Associate Professor of Computer Science at Princeton University. He has received several awards for his research, including a Sloan Fellowship (2010), Office of Naval Research Young Investigator Award (2011), Presidential Early Career Award for Scientists and Engineers (2011), Blavatnik Faculty Award (2013), and ACM-Infosys Foundation Award (2013).


Tony Jebara

Tony Jebara is Associate Professor of Computer Science at Columbia University and Director of Machine Learning Research at Netflix. His research intersects computer science and statistics to develop new frameworks for learning from data with applications in social networks, recommendation, spatio-temporal data, vision and text. Jebara has founded and advised several startups including Sense Networks (acquired by, Evidation Health, Agolo, Ufora, MagikEye, and Bookt (acquired by RealPage NASDAQ:RP). He has published over 100 peer-reviewed papers in conferences, workshops and journals including NIPS, ICML, UAI, COLT, JMLR, CVPR, ICCV, and AISTAT. He is the author of the book Machine Learning: Discriminative and Generative and co-inventor on multiple patents in vision, learning and spatio temporal modeling. In 2004, Jebara was the recipient of the Career award from the National Science Foundation. His work was recognized with a best paper award at the 26th International Conference on Machine Learning, a best student paper award at the 20th International Conference on Machine Learning as well as an outstanding contribution award from the Pattern Recognition Society in 2001. Jebara’s research has been featured on television (ABC, BBC, New York One, TechTV, etc.) as well as in the popular press (New York Times, Slash Dot, Wired, Businessweek, IEEE Spectrum, etc.). Esquire magazine named him one of their Best and Brightest of 2008. Jebara will be General Chair for the 34th International Conference on Machine Learning (ICML) in 2017and was a Program Chair for the 31st International Conference on Machine Learning (ICML) in 2014. In 2006, he co-founded the NYAS /Machine Learning Symposium / and has served on its steering committee since then. He obtained his PhD in 2002 from MIT.

Our Investors

Khosla Ventures
Y Combinator
SV Angel
Data Collective
Initialized Capital
Jeff Epstein
Scott Banister
Alexander Gerko
Adrian Aoun
Mark Pincus


Adam Spector: Adam Spector interviews with Kevin Horek of Building the Future

5-year trends in artificially intelligent marketing: Recommendation and personalization predicted to be greatest profit opportunity
20 Most Promising Cognitive Solution Providers – 2017: LiftIgniter uses cutting edge machine learning to help publishers and retailers optimize their websites and mobile apps in real-time, for each impression with 80 percent+ improvements

I’ll Be Back: The Return of Artificial Intelligence: “Behind much of the proliferation of AI startups are large companies such as Google, Microsoft Corp., and Amazon, which have quietly built up AI capabilities over the past decade to handle enormous sets of data and make predictions, like which ad someone is more likely to click on.”

Siri Is Savvier, but Still Not Smarter Than a Fifth Grader: “Siri and other virtual assistants are designed for a more useful purpose: To reduce the time mobile users spend performing everyday tasks.”
LiftIgniter official press release/launch: “LiftIgniter dramatically increases website visitors’ click through rates with automated personalized recommendations for additional content at every interaction point.”
Customer Engagement Through Personalization Heads to Next Level in 2016: “We expect personalization to go to the next level in 2016. Websites and apps will be forced to personalize more as competition grows even stronger. Time is a zero sum game and each shopper (or user) has a multitude of options. If your site or app is unable to show users exactly what they want at the right moment, then they will leave and find a competitor who does.”
Creating a personal experience: Misconceptions, why data is a critical element : “Personalizing the retail consumer experience is a must for retailers given what shoppers and potential customers have come to expect given personal experiences with social networks, mostly notably Facebook.”
LiftIgniter wants to rid the web of garbage link recommendations : “LiftIgniter, one of the startups competing in the Battlefield competition at TechCrunch Disrupt London this week, wants to fix the system by making websites better customized. The three-year-old company, which graduated Y Combinator and has raised close to $2 million from investors, dispenses with garbage links and makes websites more dynamic and personal to readers using its machine learning model.”
London Startup Battlefield Finals: LiftIgniter : “LiftIgniter pitches their big data and machine learning-powered web personalization engine at the TechCrunch Disrupt London 2016 Startup Battlefield finals.”
Here are the winners of the Google Cloud machine learning pitch-off : “LiftIgniter, a former TC Disrupt Battlefield competitor, wants to help businesses personalize the content they deliver to users. Today, big players like Amazon and Spotify have their own advanced recommendation systems that drive engagement, but many other businesses struggle to deliver the same demanding technology.”
Announcing the winners of our Machine Learning Startup Competition : “LiftIgniter is a machine learning personalization layer powering user interactions on every digital touchpoint. Built by the team behind YouTube’s recommendation algorithm, LiftIgniter runs their full stack on GCP. LiftIgniter’s customers include Vevo, Fandom, and Tableau.”

LiftIgniter prides itself on our team.

First and foremost – that means a group of people who enjoy spending time together. We work hard but we’re also friends. Second – brains. It’s almost cliched to say but we truly only want to work with the best. We push each other and expect you, as our new teammate, to push us too.

Key Openings

Engineering Lead

LiftIgniter’s engineering team is growing fast. We are looking for a strong leader who can help manage, innovate and train the team. Our customers expect the highest level of speed and high quality machine learning personalization, which requires the strongest engineering. Our engineers are some of the brightest in the world but every team can become stronger. We’re hoping to find an ideal person who can mesh with our team while also leading it to new success.

Key requirements:

  • Grew and led an engineering & development team of 5-30 employees
  • Startup experience and comfort with moving fast
  • Strong technical chops in infrastructure and interest in machine learning
  • Proven ability to recruit, train and manage a team
  • Comfort in talking to customers

Join us by emailing

Machine Learning Engineer

LiftIgniter delivers billions of personalized recommendations and experiences every month, on some of the largest websites across the world. Building machine learning products at this scale is extremely hard, and not well solved by existing academic literature. At the same time, a few extra points in improvement can mean millions in incremental revenue, and the difference between success and failure. So we innovate, at the cutting edge. Our current team of ex-IMO, IOI, Phds from MIT, Stanford, Berkeley, Princeton love the challenges. If you’re excited by the problem and team, we should talk!

Key requirements:

  • Strong background in linear algebra, analysis and statistics
  • Very strong software design skills
  • Solid foundations in algorithms and data-structures
  • Good performances in IMO / IOI / ACM-ICPC a plus
  • PhD in Math / Statistics / Machine learning a plus

Join us by emailing