Applied AI Developer

Summary

Join our customer's team as an Applied AI Developer and work at the cutting edge of machine learning and generative AI. You will design, build, and deploy innovative AI solutions using state-of-the-art technologies such as LLMs and advanced NLP, while working closely with cross-functional teams. This unique opportunity allows you to deliver impactful solutions on massive datasets within a high-caliber, remote-first environment. The role involves building and refining ML engineering platforms, implementing ML Ops processes, deploying deep learning models, designing model pipelines, collaborating with client teams, and writing production-ready code. You will actively participate in agile ceremonies and adhere to best practices. The position offers a remote-first work environment and opportunities for growth and development within a startup setting.

Requirements

• Bachelor’s or Master’s degree in Computer Science or a related field from a top-tier university
• 4+ years of hands-on experience in machine learning, deep learning, and fine-tuning models (LLMs)
• Expert-level proficiency in Python; experience with backend API design and vector databases
• Solid understanding of ML Ops, including measuring and tracking model performance, and MLFlow
• Demonstrated experience in NLP, generative AI, and deploying real-time model predictions
• Strong communication skills—both written and verbal—are essential for cross-functional collaboration
• Experience with ML frameworks such as Keras and HuggingFace

Responsibilities

• Build, refine, and utilize advanced ML engineering platforms and reusable components to deliver scalable AI solutions
• Implement ML Ops processes, track model KPIs, monitor drift, and establish robust feedback loops for continuous improvement
• Deploy and operationalize deep learning models, with a focus on LLMs and generative AI, ensuring reliability and performance at scale
• Design and orchestrate model pipelines, including feature engineering, inferencing, and continuous training, to meet strict SLAs
• Collaborate with client-facing teams to understand high-level business contexts and translate them into technical requirements
• Write production-ready code with a focus on testability, maintainability, and handling edge cases and errors gracefully
• Actively participate in agile ceremonies, communicate progress effectively, and adhere to best practices for architecture, design, and code quality

Preferred Qualifications

• Familiarity with DevOps practices, CI/CD pipelines, cloud architecture, and data security
• Experience in data engineering for big data systems and knowledge of PySpark or Scala
• Background in computer vision and implementing end-to-end feature engineering pipelines

Benefits

Remote work, flexible hours