AI/ML Developer – LLM & Prompt Engineering Focus

MUST submit a Resume in English

Location: Remote

Employment Type: Full-Time

Reporting To: AI/ML Developer – LLM & Prompt Engineering Focus

Fluency in English is a must

Working hours PST.

We are seeking a passionate and skilled AI/ML Developer with hands-on experience in Large Language Models (LLMs), Python, and prompt engineering. You will be responsible for designing, developing, and deploying AI-powered solutions using state-of-the-art machine learning models with a focus on language understanding and generation. This role requires a blend of technical depth, logical problem-solving, and strong communication skills to translate complex business requirements into scalable AI solutions.
Responsibilities:
– Design, fine-tune, and deploy LLM-based solutions for real-world business problems.
– Develop and optimize prompts to guide model behavior for various use cases.
– Write clean, efficient, and scalable Python code for model development and integration.
– Analyze model performance and troubleshoot issues with data quality, token usage, and output alignment.
– Collaborate with product owners, data scientists, and engineers to identify and prioritize AI use cases.
– Stay current with the latest advancements in AI/ML, especially in the generative AI space.
– Document model behavior, prompt iterations, and implementation decisions clearly for both technical and non-technical stakeholders. – Ensure ethical and responsible AI development practices.
Requirements :
➢ Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
➢ 2-5 years of proven experience working with LLMs (e.g., GPT, LLaMA, Claude, Mistral) in production or prototyping environments.
➢ Strong programming skills in Python, with experience using relevant libraries (e.g., Transformers, LangChain, OpenAI API, Hugging Face) ➢ Practical experience in prompt engineering, including prompt chaining, prompt tuning, and system message crafting.
➢ Solid foundation in machine learning concepts and natural language processing.
➢ Strong logical thinking and problem-solving skills with an ability to break down complex problems into structured solutions.
➢ Excellent communication skills – both written and verbal – to convey technical concepts to diverse stakeholders.
Preferred Qualifications :
➢ Experience with model fine-tuning or reinforcement learning from human feedback (RLHF).
➢ Familiarity with vector databases and retrieval-augmented generation (RAG) techniques.
➢ Exposure to cloud platforms like AWS, Azure, or GCP.
➢ Experience with ML Ops, containerization (Docker), and model deployment pipelines.
➢ Contributions to open-source AI/ML projects or publications in relevant areas.

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