Founding AI/ML Engineer

About Kickker AI

We are building a new breed of AI that transforms how B2B companies sell and procure. Our agents (1) conduct autonomous product demos in real-time, (2) understand and qualify buyer intent, (3) reason and adapt across complex sales conversations, and (4) are AI native and support agent-to-agent interactions.

We are currently working at the intersection of voice AI and browser automation and plan to build multimodal action models.

About this Role

We believe the next generation of sales intelligence will be powered by models trained on rich, behavioral interaction data and that synthetic data is a critical lever to get there faster. We're looking for a Founding AI/ML Engineer/Scientist to be the first member of our AI/ML team and set the technical foundation for everything we build.

The conversational and behavioral signals such as voice, language and action sequences are a rich source of data reflecting how real sales interactions unfold, and our models need to process these signals to: (a) understand the current state of a buyer conversation, (b) predict what a buyer needs next and how they will respond, and (c) plan and execute multi-step demo sequences that adapt in real time.

You will work closely with the founders focussing on:

1. Designing and running end-to-end ML experiments rapidly, from hypothesis to evaluation to production decision, often within a single week
2. Building synthetic data pipelines to generate high-quality training data for conversation quality, lead qualification, and demo execution models
3. Adapting and fine-tuning foundation models (LLMs and voice models) to our domain using synthetic data, self-instruct, distillation, and RLHF techniques
4. Have knowledge of vision models to support browser automation.
5. Developing evaluation frameworks that reliably measure model quality on both synthetic and real-world distributions
6. Owning scalable infrastructure for data preprocessing, experiment tracking, model versioning, and deployment
7. Sitting in on live sales calls and customer sessions to ground your research in real-world signal

Minimum Qualifications:

Bachelor's degree or equivalent experience in Computer Science, ML, or a related field

Proficiency in Python and the modern LLM ecosystem (Hugging Face, OpenAI/Anthropic APIs, LangChain or equivalent)

Ability to design, run, and analyze ML experiments independently, managing multiple research threads in parallel

Understanding of ML fundamentals and experience with large-scale training, and GPU/TPU-based compute environments.

Comfort operating as a solo contributor where you can own the full ML lifecycle without a team around you

Preferred Qualifications:

Strong track record of building and deploying high-performance ML models to production (not just notebooks)

Experience with synthetic data generation techniques such as self-instruct, distillation, RLHF pipelines, or data quality filtering

Experience fine-tuning or adapting foundation models on domain-specific datasets

Proficiency in PyTorch/Tensorflow, especially for distributed training and efficient inference

Experience in a 0 to 1 environment: early-stage startup, research lab, or internal projects

Familiarity with conversational AI, voice and vision models, and multi-agent systems

Compensation: Equity-only (up to 5%) with a pre-negotiated salary that activates on close of our funding round. You know the number before you sign.