Founding AI/ML Engineer

At Kubbly, we're changing how businesses actually talk to their customers. We built a predictive AI platform that lets brands have real conversations with people through email, text, and WhatsApp. Our system figures out what each person will probably want next and knows when they're most likely to care. We're not sending marketing spam, instead we're starting actual conversations. People can even finish their orders right there in the chat, which we still think is pretty wild.

We need someone who can help us scale this whole personalized engagement. If you have a knack for building systems that can predict what people want and actually care whether conversations feel real or like talking to a bot, you'll fit right in. You'd be joining at that perfect stage: proven enough that we know it works, early enough that you'll shape how it grows.

Reasons to join us:

• The founders actually built similar stuff before. Piyush and Giorgos have previous experience building similar startups, licensing technologies to Fortune 1000 companies, and 10+ years experience building ML and recommendation systems at Amazon and Goldman Sachs.

• We're backed by Bek Ventures (formerly Earlybird Digital East). They backed UiPath and Payhawk before they were cool. They're founder friendly, provide immense value to their portfolio companies and don't micromanage.

• You'll own the full pipeline, not tickets. Your code won't go through 5 layers of review. You'll have major role in deciding what to be built, how something should work, build it, ship it, and see customers use it.

• We actually talk about technical problems. Weekly tech talks, paper discussions, post-mortems on interesting bugs. The founders are engineers first - they'll geek out with you about implementation details.

• Competitive comp + equity.

At Kubbly, we believe AI will really change the way customer engagement works. We believe getting to know your customer is a right that not only large businesses or third-party marketplaces can afford. Everyone from medium- to small businesses to solopreneurs should be able to get to know their customers and create engaging ways to interact with them. As Founding ML Engineer you’ll be responsible for building the agentic systems and tools that would enable businesses to drive customer engagement and enable two-way conversation. You will work alongside the founding team to drive the product roadmap, develop new features and scale the platform. You will be product- and customer-obsessed. This is a great opportunity to play a key role in the design and development of product directly used by businesses to drive customer engagement.

Our philosophy: We operate on high conviction, low ego. We value passionate, data-driven ideas. We debate vigorously to find the best solution, but then align as a team to execute.

We are mostly in-office from our awesome HQ in Williamsburg - 4 days per week. That’s not because we’re obsessed with processes but because we’ve seen it in our previous roles that live collaboration fosters cross-pollination and team bonding that a fully remote team cannot experience.

• This is a founding role - You get to collaborate closely with the founders to help shape the vision and product roadmap.

• Own the production performance of AI features, including latency, cost, reliability, and model behavior monitoring.

• Architect, prototype and deploy LLM-based solutions that would expand our customer engagement engine or customer two-way communication product.

• Stay on top of the latest developments in AI and dev tooling and find tangible ways to introduce them to our daily work.

• Define and own evaluation frameworks, offline benchmarks, and production metrics to measure the quality and business impact of AI systems.

• Build feedback loops, datasets, and human-in-the-loop workflows that continuously improve model and agent performance.

• Run A/B tests and user experiments to validate hypotheses.

• Partner with founders and fellow engineers to architect and build scalable AI solutions.

• Create and maintain clear documentation while adhering to code best practices (git, PRs).

• Mentor and provide guidance to the team, helping them grow their expertise in AI.

• Stubbornness on the vision, flexibility on the details (borrowed by Jeff Bezos 😀). This means that:

  • You are flexible and curious to learn about new things constantly.

  • You are perfectly fine to bury the hatchet for efforts that don’t lead to PMF and view this is as a learning opportunity.

• Customer Obsession: we’re small and what we build is driven only by our desire to achieve PMF. This means we listen to our customers’ pains and work backwards to create awesome solutions.

• Desire to work (mostly in person), next to CTO, CEO and being involved with engineering decisions.

• Exceptional collaboration, and communication skills that foster a high-performing team environment (we believe that less is more when it comes to communicating clearly).

• 3+ years of industry experience developing machine learning models production and driving business impact.

• Experience shipping AI/ML systems into production, including inference, monitoring, guardrails, and cost/latency optimization.

• Strong experience using LLMs, agentic workflows and systems.

• Experience using GenAI work boosting tools in your day-to-day job (ChatGPT, Claude, Gemini, etc).

• Strong programming skills (Python preferred).

• Experience training and finetuning models using PyTorch/Hugging Face.

• Some proficiency applying LLMOps best practices, incl. prompt engineering.

• Solid backend engineering skills and experience building APIs/services that expose ML capabilities in real products.

• Strong skills in shell scripting (bash, zsh) and terminal multiplexers (tmux).

• Experience in cloud platforms (AWS preferred - SageMaker, EC2, S3, Lambda, CloudWatch), including building and maintaining containerized applications (e.g., Docker, Kubernetes).

• Experience in early-stage or high-growth tech environments.

• Experience with retrieval-augmented generation (RAG), ranking, and vector search.

• Familiarity building and managing data and process pipelines using Airflow or other workflow orchestration tools.

• Some experience building and deploying recommendation systems that have led to improved user engagement and/or business outcomes.

• Experience with conversational AI, safety/guardrails, and privacy-aware handling of user data.

• A great opportunity to shape the future of Kubbly and grow into leadership roles as the company grows 🌱

• Competitive salary and generous equity 🚀

• 14 paid company holidays (most companies recognize 11-12) 📆

• Unlimited paid time off 🏖

• Significant coverage of medical, dental, and vision insurance 🏥

  • Contribution towards medical, dental, and vision insurance for dependents

• Generous 401(k) company match 📈

• Home office set-up 🖥

• Gym membership

• All the cold brew when the machine is not broken and every type of coffee possible ☕️ 😛

• Great views of the Manhattan skyline 🌇

$120,000 - $170,000 USD (for NY- or SF-based candidates) plus significant equity

(Base salary will be a factor of location, experience and participation in the equity)