Junior AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate in the creation of AI-driven features utilizing Python, LLM tools, ML libraries, APIs, and internal platform services.

• Assist in prompt engineering, prompt testing, model comparison, and the evaluation of outputs generated by AI.

• Aid in the construction and upkeep of RAG workflows, which encompass document preparation, chunking, metadata tagging, embedding generation, retrieval testing, and result analysis.

• Prepare, clean, format, and validate datasets intended for model testing, prompt evaluation, and AI experimentation.

• Support the assessment of models and workflows by reviewing outputs, pinpointing errors, documenting trends, and comparing performance across different methodologies.

• Develop clean and readable Python code for scripts, internal tools, prototypes, experiments, and service components.

• Assist in debugging AI workflows, data pipelines, API integrations, and model behavior under the mentorship of senior engineers.

• Engage in code reviews, design discussions, team planning, and documentation initiatives.

• Acquire and implement production engineering practices, including Git workflows, testing, logging, Docker, CI/CD, and the fundamentals of deployment.

• Clearly document experiments, implementation details, findings, and recommendations for the technical team.

⛳️ Requirements

• 0–2 years of experience in AI engineering, machine learning, software engineering, data science, or a related technical field.

• Relevant internship experience, academic projects, bootcamp assignments, portfolio work, or contributions to open-source projects are considered acceptable.

• Strong proficiency in Python programming.

• Basic understanding of machine learning, deep learning, NLP, data processing, and model evaluation principles.

• Familiarity with tools or libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, pandas, NumPy, or similar technologies.

• A keen interest in LLMs, GenAI systems, prompt engineering, embeddings, semantic search, RAG, and AI agents.

• Capability to work with both structured and unstructured data.

• Proficiency in using Git, notebooks, command-line tools, APIs, and collaborative development workflows.

• Strong attention to detail, a curious mindset, problem-solving skills, and a willingness to learn from feedback.

• Excellent written communication skills for documenting technical work and experimental results.

🏝️ Benefits

• Competitive salary and opportunities for professional growth.

• Collaborative and innovative work environment.

• Access to cutting-edge technology and resources.

• Flexible work arrangements to support work-life balance.