Full-Time Senior Machine Learning Engineer
Accesa is hiring a remote Full-Time Senior Machine Learning Engineer. The career level for this job opening is Experienced and is accepting Romania based applicants remotely. Read complete job description before applying.
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We are seeking a highly motivated and technically skilled Senior Machine Learning Engineer with a strong focus on Prompt Engineering, Large Language Model (LLM) Evaluation, and Python-based development. This role is central to the enhancement and evaluation of our custom GPT-based systems.
Responsibilities
- Prompt Engineering & Enhancement: Design, extend, and customize system prompts, evaluate the impact of prompt changes, and continuously improve GPT usage scenarios.
- Experimental Feature Development: Conceptualize, prototype, and validate new GPT-based features to extend system capabilities.
- Model Evaluation & Tracking: Evaluate new GPT/LLM releases, monitor response quality and consistency, and assess upgrade relevance for various user tiers.
- Knowledge Sharing & Research: Stay up to date with the latest techniques and prepare detailed evaluation reports.
- Python Development & Prototyping: Develop both prototype and production-level code to support AI features.
- LLM Integration & Optimization: Utilize frameworks like Langchain to build solutions and implement advanced chatbot capabilities.
Requirements:
- 4+ years of experience with Python and its data science ecosystem (Pandas, NumPy, Scikit-learn).
- Proven experience in prompt engineering and LLM behavior analysis.
- Familiarity with LLM integration frameworks such as Langchain or similar.
- Experience in data curation, preprocessing and tokenization for LLM training
- Deep understanding of GPT-based systems and their customization potential.
- Ability to translate product requirements into reliable, maintainable code.
- Experience with experimental feature development and technical feasibility evaluation.
- Excellent documentation and communication skills.
Nice to have:
- Experience with distributed training
- Experience with MLOps for LLMs