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.