Welcome to Startup Life: Unscripted, a newsletter by The Nudge Group, where we feature candid conversations with startup operators about their career journeys and experiences. If you received this email as a forward, you can read all our past interviews and subscribe right here.

From Amazon to AI Startups: Chatting with Predibase's Julian Bright

Welcome back to Startup Life: Unscripted! Today, we are super excited to introduce Julian Bright, an accomplished tech leader currently steering the helm as the Platform Engineer Manager at Predibase, a startup company that has been making strides in the declarative machine learning space.

Julian's impressive career trajectory has taken him through an array of tech roles, from his early days at tech giants like Amazon, Microsoft, and SEEK, to becoming a founding engineer and key player at Predibase. With more than two years at Predibase, he has been instrumental in the company's journey from stealth mode to a generally available product, fostering an innovative environment in the artificial intelligence and machine learning space.

Join us as we delve into an in-depth conversation with Julian about his unique journey through the landscape of technology, from major corporations to a startup. If you're eager to glean insights from the inner workings of a tech startup, this is an interview you won't want to miss!

Key interview takeaways:

🌐 Julian's tech expedition: From establishing his name in tech powerhouses like Amazon, Microsoft, and SEEK, to becoming a cornerstone at Predibase, Julian’s career journey is a testament to how tech expertise and the right mindset can propel you to new horizons.

📘 Embracing the shift: His transition from senior technical roles to a leadership role came with its challenges, but it proved to be a monumental step in his career. The secret to his success? A mixture of technical proficiency, empathetic leadership, and deep understanding of customer needs.

👨‍💻 The delight of leading: Julian doesn't just focus on getting the job done. He ensures his team flourishes in the process. He's elevated team management to another level, fostering individual growth, celebrating successes, and cultivating a culture of collaboration and innovation.

🚀 Career wisdom from Julian: For those aspiring to traverse a career path similar to Julian's, his advice is invaluable. Grab opportunities, value unique experiences, and remember - an exceptional career isn't just about the paycheck or the title. It's about passion for your work, maintaining a balance, and continually learning and growing.

Hey Julian, great to have you here with us today. As a founding engineer of Predibase, you've seen the company grow from its seed stage to where it is now. Can you tell us about the journey and how it has shaped your experience of working in a startup?

Thanks for having me! I joined Predibase as employee number 8, the first fully remote and most senior in a cohort of engineers that started the month before our first company offsite in November 2021. It was an exciting time, we were investing heavily in our open source library Ludwig, and building the early enterprise product whilst still in stealth mode.

I had interviewed for the position remotely while on holidays, and really loved the vision that the founders Perio, Travis and Dev had for Predibase. I was already sold on the benefits of the declarative machine learning approach having helped customers adopt Ludwig at Amazon, and having met Piero at a conference a few years back found him to be a very genuine and down to earth person which gave me confidence of a good cultural fit.

We came out of stealth in May 2022 and worked closely with design partners before announcing our second round of funding and generally available in June 2023. The journey was one of focus and iteration, a culmination of two years of effort still with a fairly lean team of less than 30 people.

It was a new experience for me working for a US startup, and felt different to the Australian startup ecosystem which typically favours bootstrapping and finding product market fit before taking on outside capital.

Being a well funded Silicon Valley Startup, gave us the opportunity to build while in stealth and bring a capable product to market that delivered value to customers right away. This was particularly important given we were needing to both educate the market on the value proposition of declarative machine learning, and position ourselves as a category leader in this space.

With over 20 years of experience at companies like Amazon, Microsoft, and SEEK, how has this depth of experience influenced your approach as an Engineering Manager at Predibase? What lessons from these large companies have you been able to apply in a startup environment?

My move into engineering management is a relatively recent one, having worked as an individual contributor (IC) in senior technical roles up until a few years ago.

One such role was a Solutions Architect at Amazon which taught me a lot about creating scalable business processes for everything from hiring, sales plays, to thought leadership. As a company that operates at a massive scale, Amazon still feels like a startup, providing loads of autonomy to people and teams, with a culture of saying yes more often than you would think.

Having not previously worked in a customer facing role, I learnt about the sales and marketing side of a business, the importance of working backwards from the customer, and I gained an appreciation for the soft skills required to develop relationships with the C-suite. It also provided me the opportunity to develop my own profile through public speaking at events, and publishing content in blogs and open source samples on GitHub.

On the flip side Amazon was still a very US and Seattle centric business and prior to the pandemic not very remote friendly, so having an impact from Australia could be challenging, which was an important lesson I took away and revisited when building our remote-first culture at Predibase.

At SEEK the senior leadership team did a great job of setting clear strategic priorities, and celebrating success along the way to that vision. I had the opportunity to move from my role in the Architecture team into a new Data Science team tasked with building products on the rich datasets that had been collected over the years.

From this experience I took away a much better understanding of the data science workflow, and the many challenges in operationalising machine learning. Another great take away from my time at SEEK was the value generated from the company-wide Hackathons. These provide a great opportunity to think outside the box and build something impactful in a few days.

I encourage all companies to make this investment, knowing that it may take some time to get the mechanics right. A couple of lessons we learnt: make it as much about the pitch as the idea or solution, have a committee of volunteers to keep it running smoothly, and pick a theme - make it fun!

I worked for Microsoft much earlier in my career, but one thing that stood out then that is still true today - they really understand the importance of building a thriving development community. Successful software companies don’t need to invest as heavily in marketing when the community is out there talking about them on their behalf.

As an engineering manager at Predibase I have responsibility for leading our platform teams. Having been a customer building machine learning solutions, as well as working on the sales side, I understand the pain points and expectations that enterprises have when it comes to adopting a machine learning platform. As a startup with a relatively small team we are focused on building an easy to use, reliable and scalable platform all the while listening to our customers and the market.

Working remotely has become a significant aspect of startup culture, especially in tech. How has leading your team remotely from Melbourne affected your team dynamics and your management approach?

As a remote first company, Predibase has some rituals that help to ground us and keep us connected. These included Monday all-hands where we would hear from the CEO, heads of Product and Technology as well as Sales & Marketing.

Our cross functional teams run daily stand-ups, and we encourage everyone to share learnings through writing good documentation, as well as participate in our regular Tech Talks which give folks across the organisation a chance to share what they have been working on.

Our low ego culture also helps encourage debate and discussion, which typically happens in an async fashion though slack and facilitated with tooling to support issue tracking, code reviews, automated builds and testing.

We now have a San Francisco and New York office for people to work out of 2 days a week, but it’s up to each team to synchronise on a daily standup at a time that works for them. Since there is a good few hours overlap between the US West coast and Melbourne, I schedule my team meetings and 1-1’s in the mornings, then catch up on the various async threads before getting into some deep work in my afternoon for a few hours.

Working remotely requires you to be more disciplined with time management, effective at note taking, and have good processes and tooling for tracking work in progress and inter-team dependencies. I have found working remotely can provide a better quality of life, providing opportunities for travel or being able to make time for your family schedule.

Global startup job opportunities:

• 💻 Mid-Senior Software Engineer

• 📊 Paid Media Manager - Search

• 📲 Paid Social Media Manager

• 🏢 Account Director

• 📚 Junior Office Administrator

• 🚀 Head of Marketing & Monetisation

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• ⚙️ Senior Tech Engineer - Managing Projects

As someone who is both leading the platform team and actively building the next generation declarative machine learning platform, how do you balance your management responsibilities with hands-on work?

As an engineering leader, your team is looking to you to provide a clear direction on “where” to head to meet the company goals, and “what” to build in the short term . On the other hand, you will be looking to your team to figure out the “how”. I believe the best managers should still be very capable individual contributors. I regularly dive deep with my team on solution design, and try to spend 50% of my time writing code including building proof of concepts to validate my thinking.

As a manager one of the most valuable things I can be doing is unblocking issues and increasing my team's velocity. That often boils down to reducing the time between someone writing code and when that code goes live. In practice this touches on everything from the developer experience, versioning and dependency management, continuous integration and deployment infrastructure (CI/CD), to the quality of our observability and monitoring. Getting this right can be a virtuous cycle and make a huge impact on your team's productivity.

You're in a unique position of having experience at major corporations, a startup, and also as an investor/advisor in the startup community. How has this trifecta of experiences informed your perspective on career pathways in tech?

I believe the key to a successful career in tech is to always stay curious, and develop a lifelong learning mindset. There is a saying “The Only Constant in Life Is Change”, and I think this is especially true in AI and machine learning and technology in general.

Given this, as a leader I believe it's important to have strong opinions, but for them to be weakly held. It’s unlikely that you will always have the right answers, so it's important to be able to have a robust debate with your colleagues, but when the time comes to making a decision you all need to be heading in the same direction.

For someone early stage in their career, I would encourage them to consider working at a startup. Whilst the money may not be at the same level, you will have greater autonomy and the learnings you get taking something from zero to one will often be far more valuable in the long run then working in a larger business where you might be responsible for a small fraction of a product.

I would also recommend against focussing too narrowly on any one area of technology early in your career. In my experience generalists have a real advantage in that they can see the bigger picture, and often are able to come up with more creative ways to solve problems.

This will also help you to figure out what you really enjoy doing, and once you know this, you can start working on making yourself more “T Shaped”, where the vertical line in the metaphor represents an area where you start to specialise and develop over the course of your career.

For those looking to enter the startup world as an engineer, what advice would you offer? What are some essential skills or experiences you believe are crucial for success?

Startups are typically looking to hire individuals that stand out from the crowd. The best way to achieve this is to find ways to give back to the community and build a name for yourself.

This could be by writing a blog, getting involved in an existing open source project, or starting your own. This will help you build your network, and since many job opportunities in early stage companies are not advertised via traditional job boards, it will increase your chances of hearing about these roles.

Working at a startup often requires you to wear many hats in the early days, so it’s also valuable if you can demonstrate your versatility. Make sure you can showcase experiences where you took on diverse responsibilities, collaborated with cross-functional teams, or successfully worked on projects beyond your core expertise.

If you do get an offer to interview, I would also encourage you to do your homework, come prepared by researching the company and the industry, and have a list of questions that will show you have given some thought to the particular opportunity on offer.

Lastly, as head of platform engineering at Predibase, what are you most excited about for the future of the company and the next generation of tooling for AI/ML?

It’s an incredible time to be working at an AI/ML startup. Generative AI has taken the world by storm and has huge economic potential. Right now we are seeing a massive explosion of new startups and investments in this space, as well as the accelerating pace of innovation in open source LLMs.

Predibase is well positioned to capitalise on this renewed interest in AI as we have both an open source and commercial offering that incorporates state of the art advances in AI, and makes it accessible using our declarative approach to machine learning.

In my 20+ years working in technology, I have witnessed a few major shifts such as the rise of the internet, mobile and cloud computing. It feels like we are at the beginning of another major shift as companies look to adopt AI as a core part of doing business, and I couldn’t be more excited about that.

Give It A Nudge

On our latest episode, Steve sat down with Joey Moshinsky, Co-Founder and Joint CEO of the EdTech startup, Tutero. Steve and Joey talk about the startup’s ideation during the COVID-19 pandemic to achieving exponential growth, Tutero’s unique business model, and plans for future expansion.

And that's a wrap! We hope you've enjoyed this edition as much as we loved putting it together. Stay curious, keep learning, and above all, enjoy the rollercoaster ride that is Startup Life. Catch you in the next one! 👋 Not subscribed yet? Do it here and don't miss out! Subscribe Now.