About the job
As a Senior Machine Learning Engineer with experience in training or fine-tuning large language models (LLMs), including both text and multimodal systems, reinforcement learning, agentic AI architectures, and inference optimization you will join a team of passionate engineers and scientists, driving ideas to impactful results in a fast-paced environment. You will work on designing, building, and deploying large-scale machine learning (ML) and agentic systems, with an emphasis on production-grade solutions involving data pipelines, large-scale training, model serving, and performance optimization. You are experienced in machine learning engineering from ideation and algorithm selection to architecture and implementation, to deployment and continuous improvement.
Responsibilities
Lead the design and architecture of ML solutions for projects/sub-systems.
Select appropriate models, training regimes, and serving approaches.
Produce maintainable, efficient, and explainable ML code.
Drive monitoring for model drift, bias/fairness, and reliability.
Mentor early-in-profession engineers, provide design/code reviews, and raise quality standards.
Partner with other teams to ensure integrated ML systems are production-ready.
Qualifications
Minimum
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python with experience in at least one deep learning framework such as PyTorch, JAX, or TensorFlow.OR equivalent experience.
Preferred
Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Experience with Microsoft’s LLMOps stack: Azure AI Foundry, Azure Machine Learning, Semantic Kernel, Azure OpenAI Service, and Azure AI Search for vector/RAG. Familiarity with responsible AI evaluation frameworks and bias mitigation methods. Experience across the product lifecycle from ideation to shipping. Experience deploying Fine Tuned LLMs or multimodal models in live production environments. Experience shipping and maintaining production AI systems.