Entry-level AI Engineer responsible for developing, testing, and deploying ML and LLM-based solutions. Supporting foundational engineering skills across AI spectrum in a hybrid work environment.
Responsibilities
Support data collection, cleaning, and preprocessing for ML and LLM projects.
Assist in implementing, evaluating, and optimizing AI/ML models and LLM pipelines.
Develop and test prompt templates, retrieval chains, and agentic components under guidance.
Contribute to fine-tuning and lightweight adaptation (LoRA, adapters, instruction-tuning) of models.
Implement model APIs or inference endpoints, and integrate them into applications or microservices.
Participate in debugging, troubleshooting, and monitoring both ML pipelines and agentic workflows.
Document data flows, model architectures, and experiment results clearly.
Stay current with advances in machine learning, generative AI, and agent frameworks (LangChain, LangGraph, vLLM etc.).
Requirements
Education: Bachelor’s in Computer Science, AI, ML, Data Science, Electrical Engineering, or related field.
Experience: 0 to 3 years in software development or academic AI/ML projects.
Technical Skills
Solid programming skills (Python, R, Java, C++).
Understanding of ML concepts (supervised/unsupervised learning, evaluation metrics).
Familiarity with LLM ecosystems (OpenAI API, Hugging Face, LangChain).
Exposure to fine-tuning and prompt engineering.
Knowledge of data structures, algorithms, and Git.
Basic understanding of MLOps / AgentOps workflows.
Soft Skills
Curiosity, teamwork, and proactive learning attitude.
Analytical mindset with good communication skills.
Customer-centric thinking and disciplined work ethic.
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