Job Summary
The Full Stack Data Engineering Developer will support the development and deployment of production-grade machine learning and Generative AI solutions at scale. The role requires a strong data science background with experience in NLP, recent hands-on Generative AI and LLM applications, RAG implementations and evaluations, and production ML systems. The candidate will work closely with Machine Learning Engineers and other Data Scientists throughout product development, deployment, maintenance, and new feature development, with an opportunity to grow into a technical lead role.
Key Responsibilities
• Support the development, deployment, maintenance, and enhancement of production-grade machine learning systems.
• Develop and implement Generative AI, LLM, and RAG solutions, including evaluation of deployed solutions.
• Work alongside Machine Learning Engineers through product development and production deployment.
• Apply machine learning algorithms including deep learning, gradient boosting, and random forests.
• Work directly with large language models and Transformer-based architectures including BERT, RoBERTa, and T5.
• Apply LLM technologies including ChatGPT, GPT 3.5, Claude, and Mistral to relevant business and technical solutions.
• Work with large datasets and distributed computing systems such as Hadoop and Spark.
• Contribute to scaling and maintaining production-grade ML systems.
• Participate in product build, new feature development, deployment, and ongoing maintenance activities.
• Mentor and train colleagues and serve as a subject matter expert.
• Collaborate with Data Scientists and Machine Learning Engineers to support technical delivery and product objectives.
Required Qualifications
• 10+ years of data science experience.
• Strong background in Natural Language Processing (NLP).
• 4-5 years of strong hands-on Generative AI data science experience.
• Strong experience with production-grade ML systems at scale.
• Strong hands-on experience deploying LLM, Generative AI, and RAG solutions.
• Experience with RAG implementation and evaluation.
• Experience following the full deployment lifecycle, including product build, maintenance, and new feature development.
• Experience working alongside ML Engineers through product deployment.
• Strong Python programming background.
• Experience with machine learning algorithms including deep learning, gradient boosting, and random forests.
• Experience working with Transformer-based architectures such as BERT, RoBERTa, and T5.
• Experience working with LLM technologies including ChatGPT, GPT 3.5, Claude, and Mistral.
• Experience working with large datasets and distributed computing systems such as Hadoop and Spark.
• Experience mentoring, training, and serving as a subject matter expert.
