Job Description: Junior AI Solutions Developer
Location: Remote
Employment Type: Full-time
Experience Level: 0-1 year (Fresh graduates with exceptional internships encouraged)
About Us
We pioneer intelligent systems that transform industries through AI/ML innovation. Our team builds scalable solutions leveraging generative AI, machine learning, and data engineering to solve complex challenges. Join us to accelerate your career while working on cutting-edge projects from concept to deployment.
Role Overview
We seek a Junior AI Solutions Developer to design, build, and optimise Python-based AI solutions. You’ll develop production-ready systems using large language models (LLMs), NLP pipelines, and data engineering frameworks while collaborating with cross-functional teams to solve real-world problems.
Key Responsibilities
AI/ML System Development
- Develop, test, and maintain Python applications for AI/ML solutions across diverse domains.
- Implement and fine-tune ML models using frameworks (LangChain, Hugging Face, TensorFlow/PyTorch).
- Hands-on experience with at least one AI Agent framework. e.g. CrewAI, LangGraph, AutoGen, or Semantic Kernel.
- Build NLP systems for text analysis, summarisation, and information extraction.
- Build solutions using embeddings, transformers, and retrieval-augmented generation (RAG).
- Proficient in using LangChain framework.
- Familiarity with vector databases (e.g., ChromaDB, FAISS, Pinecone)
Data Engineering & Optimisation
- Apply data structures & algorithms (DSA) to optimise model performance and scalability.
- Design data pipelines for processing unstructured documents → structured databases (MySQL focus).
- Conduct data analysis, feature engineering, and predictive modeling.
Cross-Functional Integration
- Integrate AI models into business workflows via APIs and cloud platforms (AWS/Azure/GCP).
- Containerise solutions using Docker for deployment and scalability.
Research & Documentation
- Stay current with emerging AI/ML technologies (LLMs, vector DBs, agentic frameworks).
- Document workflows, pipelines, and technical specifications for knowledge sharing.
Skills & Qualifications
Technical Competencies
- Proficient in Python with strong DSA fundamentals
- Experience with AI/ML frameworks: LangChain, Hugging Face, PyTorch/TensorFlow
- Understanding of NLP, embeddings, transformer architectures, and LLM fine-tuning
- Experience with RAG implementations and model inferencing
- MySQL (required), Vector DBs (ChromaDB/Pinecone), or PostgreSQL
- Cloud platforms (AWS Sagemaker, Azure ML, or GCP Vertex AI)
- Experimentation tools (Google Colab, Jupyter Notebooks)
- Data validation/cleaning techniques and pipeline orchestration
Professional Attributes
- Analytical problem-solver with rigorous debugging/testing approach
- Collaborative team player comfortable in Agile environments
- Proactive learner with the ability to document technical processes clearly