bld.ai | Senior Data Scientist | Singapore | Hybrid (non-remote) | Relocation OK | Full-time
Lead client-facing AI + data science projects for enterprise clients. 6–10 yrs applied ML/AI experience, strong MLOps + data strategy background. Consulting or enterprise experience required. Salary 125–140K SGD. Master’s/PhD nice but not required.
Also looking for:
Junior AI Engineer / Data Scientist | Australia (Remote or Melbourne) | Full-time
Early-career role building + shipping real production ML. 1–3 yrs ML/Python/data pipelines. Cloud exp. (AWS/GCP/Azure) a plus. Remote-friendly across East Aus. Salary 100–115K AUD. Work closely with Singapore lead; real impact + fast learning curve.
__
Senior Data Scientist | USA (Remote) | Full-time | 150K USD + commission
Lead applied AI delivery + enterprise client conversations. 6–10 yrs in ML/DS/AI product work; MLOps + strategy skills. Consulting or enterprise background preferred. Master’s/PhD optional. Looking for polished stakeholder presence (ex-FAANG/MBB vibes welcome).
___
bld.ai | Junior AI Engineer / Data Scientist | USA (Remote) | Full-time | 100K USD + commission
1–3 yrs ML engineering or DS, Python + pipelines, cloud exposure. Comfortable async + independent; startup pace. Growth path to technical lead.
Full-Stack / App Developer (Client-Facing)
Location: USA (Houston, Chicago, or Bay Area, CA)
Compensation: 110–125K USD + commission
Role Summary:
We’re looking for an application developer who thrives at the intersection of software engineering and client delivery. You’ll design, build, and deploy production-grade applications—often integrating AI or data-driven components—and work closely with enterprise clients on-site (~50% travel). You’ll collaborate with our AI and data science teams to bring robust, user-ready systems to life.
Requirements:
1. 4–7 years of experience in full-stack or application development.
2. Strong proficiency in Python, JavaScript/TypeScript, and modern frameworks (e.g., React, FastAPI, Node.js, or Flask).
3. Experience deploying to cloud environments (AWS, GCP, or Azure).
4. Ability to translate business requirements into maintainable, scalable code.
5. Excellent client-facing communication and collaboration skills.
6. Willingness to travel up to 50% for on-site work with U.S. clients.
Ideal Profile:
A hands-on builder with a consulting mindset—comfortable both coding independently and representing the team in client environments. Prior experience in AI product development, data-intensive systems, or enterprise integrations is a plus.
Junior AI Engineer / Data Scientist
Location: USA broadly
100K USD + commission
Role Summary:
Support the development and deployment of AI systems, focusing on experimentation, data processing, and performance optimization. You’ll work closely with the Singapore lead to execute model training, testing, and integration tasks in production environments.
Requirements:
1. 1–3 years experience in machine learning, Python, and data pipelines.
2. Exposure to cloud environments (AWS, GCP, or Azure).
3. Comfortable working independently and asynchronously with remote teams.
4. Good communication skills and disciplined execution.
5. Bachelor’s in Computer Science, Data Science, or related field.
Ideal Profile:
Early-career data scientist or ML engineer with a startup or research background; eager to learn, ship fast, and grow into a lead role.
Senior Data Scientist
Location: USA broadly
150K USD + commission
Role Summary:
Lead client-facing AI engagements, represent the firm in discussions with enterprise clients, and oversee technical delivery across applied AI and data science projects. You’ll translate business problems into practical AI solutions while guiding a small, distributed engineering team.
Requirements:
1. 6–10 years in applied machine learning, data science, or AI product development.
2. Proven experience with enterprise clients or consulting environments.
3. Strong communication and presentation skills.
4. Technical depth in model design, MLOps, and data strategy.
5. Master’s or PhD preferred but not required.
Ideal Profile:
Ex-FAANG, Ex-MBB, or similar background; confident, articulate, credible in front of senior stakeholders.
Why do antitrust proposals always suggest breaking up Google by function—Search, Ads, Gmail, etc.? What if, instead, we cloned the whole company?
Start by splitting Google into two identical, full-stack companies, each with all the core products. A year later, split them again. Over time, you get 4 or 8 Googles competing across the board.
Employees could be assigned algorithmically to avoid chaos. This feels more like cell division than amputation—preserving the synergies while creating competition.
I would rather have us all weaned off the Google services. That would be a great outcome actually. I am guessing your idea is, that those 2 or 4 Googles would then compete and make better products. But I am not sure how likely it is, that they can fix the mess and pile of bloat, that their software is.
Because that's conceptually simple. With your idea, you cannot clone the domain 'gmail.com' so one of these must happen:
- one company gets control of gmail.com and the other has to register a new domain nobody has ever heard of.
- the companies share control of gmail.com and users see no changes.
Anyone who must upend their digital life (email, contacts, Android login, YouTube login, analytics, 'login with Google' around the web, payment data, etc. etc.) has a problem, the company which gets the domain has a massive advantage. If they share it how are they competing with each other, which one can change the Gmail experience or pricing scheme?
Similar with GCP, which split gets to run a big customer's services? The customer isn't going to pay twice for them to be cloned. Does the customer have to update all their logins and API keys and contracts and payment details?
Who owns all the Exabytes of pre-existing YouTube data and what happens to all the ISP peering and CDN server hosting contracts which run it?
What happens to the legal contracts, tax deals to have offices in certain countries, employee visas, paying the datacenter maintenance bills or office cleaning bills? If the employees sit next to each other and now one works for Google_A and keeps everything the same, the other works for Google_1 and has to move to a new office which hasn't been built yet... same problem as Gmail but internally, one company gets a big advantage the other gets a big disruption.
What happens when you algorithmically split employees 'to avoid chaos' but one company ends up with no senior people who have access to a certain system?
Since we didn't ask for our accounts to be copied to Google1, do hundreds of millions of us have send Google1 a 'delete my account' request to get rid of them? If I delete my account from GoogleA do they have access and legal right to delete the copy from Google1 as well? If they don't, does my deleted login to GoogleA still work backed by the copy of my account on Google1, because there is only one GMail.com domain and it has to keep working?
It's conceptually easier to say maps.google.com is under control of a new company, not subsidised by Google Advertising income, and it needs to compete with other map providers, even if technically it's hard to extract the accounts and data from Google's server infrastructure.
You will:
1. Build in Swift.
2. Creating fluid swipe and transition animations.
3. Optimizing data structures to minimize server load times by predictive preloading and caching.
4. Integrate OpenAI APIs into a Swift front-end (I already deployed a prototype that works).
5. Implement fast and reliable peer-to-peer, one-on-one video streaming.
6. Implement Web3 payment integrations on CELO Level 2 blockchain, including Apple Pay token purchasing.
I will:
- Pay you $1,000/month while we aren't funded.
- Meet w you 30 minutes/day to review, problem solve, and plan your 7-8 hours of work. 4PM Singapore time.
- Use V0 by Vercel prototype as design reference.
Agreed. It's important to put enough effort that you find meaning in your work, but not so much that it ruins your wellbeing. Here's a rough algorithm that works for me:
1. Estimate the hours you think it will take to complete a task.
2. Double it and let the team know you did that.
3. Do the work well including good documentation.
4. Assess your progress when you've spent 50% of the planned hours. If you're not at least halfway done, avoid overworking. Instead, seek help within the team and descope.
5. Utilise any extra time for learning new and useful skills, if you finish ahead of schedule.
I agree. This requires a healthy workplace though.
I worked somewhere, well two places where I was literally taken to task about how long something took. Repeatedly. They didn’t care about why, just that it wont happen again.
It didn’t: in both cases it’s time to fire up Word again and edit my CV (pretty much the one reason I use that program!)
Maybe. But that’s like learning to build a car and then building one and fine tuning one because I had to go to an office 200 meters away once in a few years.
Yeah, I did Texin’ in college and tried after that as well. No body gave a shit and now when I look at CVs for hiring purposes I don’t give a shit either. Now my CV is on a live.com free throwaway account — that’s where it resides and gets worked upon and converted to PDF when needed.
We are a design + dev shop. We bill our clients hourly in USD. We give all IP to our clients and are long-term partners with a dozen well funded startups (e.g., backed by a16z, YC, etc.) and multiple Fortune 100 companies. We are 3 years old, employee owned, and 100+ employees.
Our teams are passionate about UX. We practice test-driven development. We are transparent about finances and compensation. We want diversity by design. We systematically invest the majority of our profit in recruiting, training, and mentoring each other.
Competitive salary, benefits, paid vacation, equity, and sick leave.
We are a design + dev shop. We bill our clients hourly. We give all IP to our clients. We are long term partners with a dozen well funded startups (e.g., backed by a16z, YC, etc.), an energy super major, a giant tech, and more. We are 3 years old, now 80 employees, and growing at 100% every 9 months.
Passionated about UX. Test driven development. Transparent about finances and compensation. Diversity by design. Employee owned. We systematically invest the majority of our profit in recruiting, training, and mentoring each other.
Lead client-facing AI + data science projects for enterprise clients. 6–10 yrs applied ML/AI experience, strong MLOps + data strategy background. Consulting or enterprise experience required. Salary 125–140K SGD. Master’s/PhD nice but not required.
Email priscilla.mariana@bld.ai