Website:
halcer.com
Job details:
Role Overview
We are looking for ambitious, high-potential fresh graduates and entry-level engineers to join our core team as a Software Engineer – AI / ML & Generative AI. This entry-level role is tailored for talented individuals who have a strong foundation in computer science and an eager passion to master modern artificial intelligence. You will receive hands-on mentorship while building, experimenting with, and deploying state-of-the-art Large Language Models (LLMs), deep learning networks, and generative AI systems into production software.
What You Will Do
- Build Next-Gen AI Applications: Help integrate foundation models (OpenAI, Gemini, Llama, Claude) into real-world applications using orchestration tools like LangChain and LlamaIndex.
- Develop Retrieval Systems: Work on Retrieval-Augmented Generation (RAG) pipelines and vector databases to empower AI models with custom knowledge and search capabilities.
- Write Production-Ready Code: Build reliable backend microservices and APIs using modern Python frameworks to power AI-driven user experiences.
- Learn MLOps Best Practices: Collaborate with senior engineers to track, evaluate, monitor, and deploy models using automated workflows and continuous integration tools.
- Optimize AI Performance: Experiment with model fine-tuning techniques, prompt engineering, and low-latency inference setups to make our AI systems fast and cost-effective.
What We Are Looking For
- Strong Programming Core: Solid proficiency in Python combined with a clear understanding of fundamental Data Structures, Algorithms, and Object-Oriented Programming principles.
- AI & Machine Learning Knowledge: Firm academic or project-based grasp of core ML concepts, Deep Learning fundamentals (especially Transformers architecture), and basic experience with frameworks like PyTorch or TensorFlow.
- Generative AI & LLM Curiosity: Hands-on experience through academic projects, internships, or personal repositories working with LLM APIs, prompt engineering, fine-tuning concepts, or RAG architectures.
- Data Management: Working knowledge of SQL/NoSQL databases, data manipulation libraries (Pandas, NumPy), and vector search concepts (Pinecone, Chroma, Milvus, or Qdrant).
- Development Basics: Familiarity with Git for version control, basic Linux environments, and exposure to containerization tools like Docker.
Bonus Points (Nice to Have)
- Academic degrees in Computer Science, Data Science, AI, Mathematics, or related STEM fields.
- Strong GitHub portfolio featuring completed AI, ML, or GenAI personal projects.
- Prior internship experience in software development, data science, or AI engineering.
- Contributions to open-source AI projects or participation in hackathons/Kaggle competitions.
- Familiarity with emerging AI agent frameworks such as LangGraph, CrewAI, or AutoGen.
Click on Apply to know more.
