Senior AI/ML Engineer

Role Overview

Senior AI/ML Engineer

Key Responsibilities

AI/ML Development

• Design, implement, and optimize

  Retrieval-Augmented Generation (RAG)

  systems.
• Fine-tune

  large language models (LLMs)

  for domain-specific applications.
• Research and apply best practices in embeddings, vector databases, and retrieval strategies.
  
• Build scalable pipelines for training, evaluation, and deployment.
  

Data Analytics

• Analyze structured and unstructured datasets to derive actionable insights.
  
• Design dashboards and visualizations to support decision-making.
  
• Translate business and client needs into data-driven AI solutions.
  

Deployment & Engineering

• Deploy and maintain ML/AI models in

  production environments

  .
• Integrate AI models with product stack (Supabase, n8n workflows, AWS S3, React/Tailwind).
  
• Optimize inference performance and ensure security and compliance.
  

Collaboration & Leadership

• Collaborate with product and engineering teams to align AI capabilities with business goals.
  
• Mentor and guide junior engineers on AI/ML best practices.
  
• Stay updated with the latest advancements in LLMs, fine-tuning, and AI infrastructure.
  

Qualifications & Experience

Education

• Bachelors or Masters degree in

  Computer Science, Data Science, AI/ML, or related fields

  .
• Strong academic foundation in algorithms, mathematics, and statistics.
  

Experience

• 5–8 years of hands-on experience

  in Machine Learning, Deep Learning, and Data Analytics.
• Proven track record in

  LLM fine-tuning, RAG pipelines, and production deployments

  .
• Experience with

  Python, PyTorch/TensorFlow, LangChain/LlamaIndex

  , and related frameworks.
• Knowledge of

  SQL & NoSQL databases

  , data preprocessing, and feature engineering.
• Familiarity with

  MLOps practices

  , cloud services (AWS/GCP/Azure), and API integrations.
• Exposure to

  Supabase, AWS S3, and workflow tools (like n8n)

  is a plus.

What We Offer

• Opportunity to lead AI initiatives across multiple industry domains.
  
• Work on challenging, real-world AI/ML problems with direct client impact.
  
• A collaborative environment with room for technical and career growth.
  
• Pathway to grow into a

  Lead/Head of AI role

  as the company scales.