AI Developer

CODA100 is seeking a talented and versatile AI Developer/Engineer to design, develop, and implement AI-driven solutions that leverage Machine Learning (ML), Large Language Models (LLMs), and Natural Language Processing (NLP). This role combines hands-on technical work with opportunities to collaborate, innovate, and create impactful solutions tailored to real-world business challenges. You will work with cutting-edge technologies like Retrieval-Augmented Generation (RAG) and modern deployment tools to deliver production-ready systems that drive meaningful change. 

Project Scope: 

As an AI Developer/Engineer, you will focus on building, deploying, and optimizing AI-powered solutions. This includes: 

• Experimenting with Large Language Models, Generative AI frameworks and advanced search technologies to design and deploy scalable solutions for tasks such as text generation, summarization, conversational AI, and recommendation systems.
• Developing and managing APIs that connect AI capabilities with external systems.
• Collaborating with clients and stakeholders to identify AI-driven opportunities and create tailored solutions.
• Delivering training sessions, workshops, or presentations to share AI insights and demonstrate solutions.
• Designing scalable AI architectures and deploying them using containerization tools like Docker and Kubernetes. 

Duties

Deliverables:  

• Build, fine-tune, and deploy AI and LLM models for tasks such as text generation, summarization, and semantic search.
• Implement Retrieval-Augmented Generation (RAG) workflows to enhance AI performance using vector databases and embeddings.
• Develop robust APIs for seamless integration of AI capabilities into business workflows.
• Use cloud platforms (e.g., AWS, Azure) for AI solution deployment and scaling.
• Optimize and deploy containerized AI solutions with tools like Docker and Kubernetes.
• Create presentations, documentation, and training materials to support knowledge-sharing and solution adoption. 

Responsibilities: 

• AI Solution Development: Design, implement, and test AI models, focusing on Machine Learning, Generative AI, and LLMs.
• RAG Integration: Build workflows leveraging Retrieval-Augmented Generation to enhance search and recommendation capabilities.
• API Development: Develop and maintain scalable APIs for AI models to ensure easy integration and usability.
• Cloud Deployment: Deploy AI applications on AWS, Azure, or similar platforms, ensuring reliability and scalability.
• Containerization: Use Docker and Kubernetes to manage containerized applications and streamline deployment processes.
• Knowledge Sharing: Lead or support training sessions, workshops, or presentations to share AI best practices and insights with teams and clients.
• Collaboration: Work closely with cross-functional teams to identify AI opportunities and deliver tailored solutions.
• Continuous Improvement: Monitor and refine deployed solutions to ensure optimal performance and alignment with business objectives. 

Required skills

Skills and Qualifications: 

Education

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field; a Master’s degree is a plus. 

Experience 

• Practical experience with Large Language Models (LLMs), Generative AI frameworks, and Machine Learning (ML) techniques.
• Hands-on experience in building and deploying AI solutions using modern frameworks and cloud platforms.
• Familiarity with Retrieval-Augmented Generation (RAG) workflows, vector databases, and embeddings.
• Proven ability to plan and deliver trainings, workshops, or presentations related to AI technologies.  

Technical Skills

• Strong proficiency in Python for AI development.
• Experience with AI and ML frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Knowledge of Natural Language Processing (NLP) concepts and tools (e.g., spaCy, NLTK).
• Familiarity with containerization tools like Docker and orchestration platforms like Kubernetes.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Proficiency in developing and deploying APIs for AI models and solutions. 

Preferred Skills

• Familiarity with prompt engineering techniques (e.g., zero-shot, few-shot prompting).
• Understanding of data pipelines and tools for data preprocessing and feature engineering.
• Hands-on experience in training and fine-tuning open-source models using transfer learning or reinforcement learning.
• Experience with frontend frameworks like React, Vue.js, or Angular to create user-friendly interfaces for AI solutions.
• Knowledge of ethical AI principles and their application in solution design. 

Certifications (Optional)

• Relevant certifications such as AWS Certified Machine Learning – Specialty, Azure AI Engineer Associate, or TensorFlow Developer Certificate are a plus. 

Soft skills

• Strong analytical skills with a focus on problem-solving.
• Excellent communication skills to collaborate with technical and non-technical teams.
• Ability to deliver engaging and informative presentations.
• Adaptability to work in an Agile environment and handle diverse projects.

What we offer

Work Arrangement

• Location: Remote work
• Work Hours: Availability for 30-40 hours per week.
• Agile collaboration in an international team

Compensation and Payment Terms 

• Hourly Rate: Negotiable, depending on experience.
• Payment Schedule: Monthly