Founding Applied ML Engineer - Ranking & Personalization

Part-Time | Equity-Only | Atlanta or Remote

Y22 is building an AI sales performance platform that learns how a company wins, helps sales reps practice those winning behaviors, and guides them during live customer conversations.

We are looking for a founding-level Applied ML Engineer to help build the ranking, personalization, and learning systems behind the platform.

This is not a traditional salaried position. It is a part-time, equity-only opportunity for an exceptional engineer who wants meaningful ownership in an early-stage, venture-backed AI company and the chance to help build a technically ambitious product from the ground up.

What You Will Build

Y22 analyzes sales conversations, CRM context, opportunity outcomes, buyer behavior, top-performer patterns, objections, buying signals, and deal risks to determine the highest-value guidance for each sales rep.

You will help build systems that determine:

• Which recommendation should appear during a specific moment in a live sales call
• Which question, response, or next action is most relevant to the current conversation
• How guidance should change based on the buyer, account, sales stage, opportunity history, and individual rep
• How recommendations should be ranked when multiple possible actions are available
• How historical call and deal outcomes should improve future recommendations
• How each rep's preparation, roleplay training, and live guidance should become more personalized over time

Responsibilities

• Design and build ranking and recommendation systems for real-time sales guidance
• Develop personalization models using conversation, buyer, account, opportunity, and rep-level context
• Build retrieval, feature-generation, and model-serving pipelines
• Work with embeddings, LLMs, structured data, transcripts, and behavioral signals
• Create evaluation frameworks for recommendation relevance, accuracy, latency, and business impact
• Connect model recommendations with sales-call and CRM outcomes
• Help build orchestration and data pipelines using tools such as Airflow
• Deploy, monitor, test, and continuously improve production ML systems
• Collaborate directly with the founders and engineering leadership on product and architecture decisions
• Help establish the technical foundation and engineering standards of the company

What We Are Looking For

• Strong experience building production machine-learning systems
• Experience with ranking, recommendation systems, personalization, search, retrieval, or information relevance
• Strong Python and software-engineering fundamentals
• Experience working with LLMs, embeddings, vector retrieval, or NLP systems
• Understanding of offline and online model evaluation
• Experience building reliable data or ML pipelines
• Familiarity with orchestration tools such as Airflow
• Ability to operate independently in an early-stage environment
• Strong product judgment and an interest in solving real customer problems

Especially Relevant Experience

• Learning-to-rank systems
• Recommendation engines
• Personalization platforms
• Real-time inference
• Conversational AI
• Contextual bandits or reinforcement learning
• Retrieval-augmented generation
• ML feature platforms
• Model evaluation and observability
• Low-latency production systems

Why Join Y22

You will have meaningful influence over the product, architecture, and technical direction of the company.

You will work alongside an engineering team with experience from Meta, Amazon Prime, Airbnb, and AWS while solving a difficult applied AI problem: determining the most useful action for a sales rep to take during the exact customer conversation happening in front of them.

This is an opportunity to join at the earliest stage, take meaningful equity ownership, and help build a core intelligence system rather than another generic AI wrapper.

Compensation

This is currently a part-time, equity-only founding opportunity. There is no salary attached to the role at this stage.

We are looking for someone who genuinely wants to help build the company, contribute consistently alongside their existing commitments, and potentially grow into a larger role as Y22 reaches its next stage.