Senior AI/ML Engineer
5 days ago
Role Overview
As a Senior AI/ML Engineer, you will play a critical role in shaping our AI initiatives. You will lead the development of RAG pipelines, fine-tuned LLMs, and advanced analytics solutions to power our products. This is a hands-on role, ideal for someone who thrives in fast-paced environments and enjoys building robust, production-ready AI solutions.
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.
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