Salary Bracket: 110k–160k

Final salary will be based on relevant skills and experience demonstrated during the hiring process.

The Elite IT Team is seeking an experienced and innovative Senior AI Engineer to lead the development of cutting-edge AI solutions across multiple domains — including machine learning (ML), deep learning, agentic AI, generative AI (GenAI), natural language processing (NLP), and computer vision (CV).

The ideal candidate will combine strong research capability with hands-on engineering expertise to design, build, and deploy scalable AI systems that drive real-world impact.

Elite IT Team is a remote-first company with 2–3 in-person gatherings per year, attended at the company’s expense.

Key Responsibilities:

• Design, develop, and deploy advanced AI models for ML, DL, NLP, CV, and GenAI applications.
• Lead research and experimentation on emerging AI techniques — including agentic and multimodal systems.
• Build and fine-tune large language models (LLMs) and generative pipelines using modern frameworks.
• Collaborate with cross-functional teams (engineering, data science, and product) to define and deliver AI-driven solutions.
• Optimize model performance, latency, and scalability for production-grade deployment.
• Develop and maintain datasets, data pipelines, and model evaluation frameworks.
• Stay updated with the latest advancements in AI research, frameworks, and tools, applying them to ongoing projects.
• Mentor junior engineers and contribute to the team’s technical roadmap and best practices.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 2–5 years of hands-on experience in AI/ML development, with proven expertise in at least two of the following: NLP, CV, GenAI, or agentic AI.
• Proficiency in Python and frameworks such as PyTorch, TensorFlow, LangChain, Hugging Face, or OpenAI API tools.
• Strong understanding of model training, fine-tuning, data preprocessing, and evaluation.
• Experience with LLMs, diffusion models, or multimodal architectures is a plus.
• Familiarity with cloud environments (AWS, GCP, Azure) and MLOps pipelines.
• Excellent problem-solving, research, and communication skills.