Product Pulse

We’re looking for a highly skilled AI Engineer to help us design, build, and scale intelligent systems across our next-generation global HR Tech platform. As an early-stage startup, we’re looking for someone who thrives in dynamic environments, is passionate about automation and AI-driven innovation, and brings hands-on experience developing AI/ML solutions within enterprise-grade SaaS platforms.  
  
You’ll work cross-functionally with product, data, and engineering teams to develop models that improve user experience, automate decision-making, and support smart HR and payroll solutions. This role reports directly to the Head of Engineering.  
  
<strong>What You’ll Do  
  
</strong>

*   Design and implement machine learning models to solve HR-specific challenges (e.g., intelligent automation, anomaly detection, personalized experiences)
*   Collaborate with product managers and engineers to bring AI features to life across the platform
*   Develop and optimize data pipelines to support model training and inference
*   Research and apply NLP, LLMs, and other AI/ML technologies to streamline and improve HR workflows
*   Monitor model performance and retrain/improve based on feedback and usage
*   Build scalable AI solutions using cloud-native tools (preferably AWS)
*   Contribute to data governance, ethical AI use, and compliance  
      
    

<strong>What You’ll Bring  
  
</strong>

*   4–6+ years of experience as an AI/ML Engineer or Data Scientist, ideally with startup or SaaS exposure
*   Strong understanding of supervised/unsupervised learning, NLP, neural networks, and generative AI
*   Proficiency with Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, or similar
*   Experience deploying models in production using cloud platforms like AWS Sagemaker, GCP Vertex AI, or Azure ML
*   Experience with data versioning, MLOps, and model lifecycle management
*   Ability to work autonomously and thrive in a startup environment
*   Familiarity with HR tech, payroll, or workforce data is a plus  
      
    

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Data

Amazon

Machine learning

Automation

Python

TensorFlow

Cloud

Azure

Support

Data Pipelines

SaaS

Research

Neural Networks

PyTorch

Compliance

Data governance

MLflow

Huggingface

Google Cloud Platform

MLOps

Cloud Native

Anomaly Detection

Supervised Learning

Unsupervised Learning

Generative AI

AI Engineer