Build and manage the complete machine learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance.
Design, develop, and deploy LLM-based and generative AI models to power scalable and intelligent enterprise applications.
Architect, optimize, and maintain retrieval-augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases.
Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement.
Conduct fine-tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness.
Collaborate with data science, engineering, and product teams to translate business needs into generative AI-driven solutions.
Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency.
Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities.
Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle.
Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies.

Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)
1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments (Required)
5+ years of experience building and maintaining end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization (Required)
3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions (Required)
5+ years of experience collaborating with cross-functional teams (engineering, data science, and product) to deliver AI-powered applications (Required)
2+ years of experience in programming languages such as Python/R, Java/Scala, and/or Go, with hands-on experience in frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face (Required)

Senior Engineer, Machine Learning Engineering

Key skills