We're seeking an engineer in large language models (LLMs).
In this role, you'll collaborate with cutting-edge teams to customize models like GPT or Llama for real-world applications.

Priority focus: Leverage Google's Gemini as the primary tool over OpenAI models for tasks involving pattern detection in text based on trained data, ensuring efficient, scalable analysis with reduced hallucinations and seamless integration via Vertex AI.

Key Responsibilities:

• Assess client needs and design tailored fine-tuning strategies using tools like Hugging Face, LoRA, or PEFT—prioritizing Gemini for text pattern recognition (e.g., themes, sentiments, or motifs in large corpora).
• Implement, evaluate, and optimize fine-tuned models for performance, efficiency, and ethical alignment, with hands-on expertise in multimodal and structured data processing.

Requirements:

• 3+ years in ML/AI, with proven experience in LLM fine-tuning, particularly pattern-finding in text using pre-trained models.
• Proficiency in Python, PyTorch/TensorFlow, and model deployment (e.g., via APIs or cloud services); strong hands-on with Gemini's ecosystem.
• Strong communication skills to translate complex concepts for non-technical stakeholders.
• Experience with domain-specific tuning (e.g., legal, healthcare) or multilingual models; familiarity with OpenAI as a secondary option.