Senior Machine Learning Engineer

What You’ll Do

• You’ll help our data science team grow by sharing your ideas, challenging status quo, and influencing the direction of the team
• You’ll demonstrate a broad knowledge of ML approaches and are pragmatic about solutions. E.g., you create business value and fit models
• You’ll work across supervised, unsupervised, and deep learning approaches while being comfortable using inferential statistics, time series, LLMs, or computer vision approaches to solve a given problem (we don’t expect expertise in all!)
• You’ll design, engineer, test, document, and explain production ML systems in Azure, Python, SQL, and Git
• You’ll take the lead gathering input from non-technical customer stakeholders and senior IT leadership to plan what to build and set project scope
• You’ll frame complex problems and propose options to either use data when it’s available or pursue alternatives when it’s not
• You’ll take the lead in technical design discussions, remove blockers, and align stakeholders
• You’ll use Big Data tools (Databricks, Spark, Azure, SQL, Python) to carry out supporting analyses and build production solutions
• You’ll fit, tune, test, validate, and deploy ML models in an MLOps setting to solve real-world problems
• You’ll discuss project issues and topics simply when presenting to customers  

What You’ll Need

• Strong coding skill in SQL and Python (especially pandas, numpy, scikit-learn, Tensorflow/PyTorch)
• Experience designing and implementing LLM systems. (Multi-tooled single agents, multi-agent systems, custom routing and gateways)
• Relative experience (~20+ projects) in cloud development. Azure is preferred but AWS and GCP are acceptable  too
• Professional experience using Databricks/Spark and Docker/Kubernetes
• 7+ years experience owning ML systems from idea to maintenance
• Demonstrable thought leadership evidenced by an active GitHub, blog posts, or publication record
• Deeply curious and motivated by challenge. Does not shy away from potential failure
• Willing to challenge the status quo to propose improvements
• Can communicate simply and intuitively to diverse audiences with varying technical background
• Proven success with--and interest in--owning end-to-end projects solo but knowing when to escalate and delegate
• Experience with--and interest in—developing in a production MLOps setting
• Practical experience with tools for the ML lifecycle, including EDA, data prep, data verification, modeling, testing, deploying, and relevant object-oriented software development tasks
• Experience using data visualization to understand and persuade 

What Will Set You Apart

• Having most of the above characteristics and experiences 
• Above average experience in cloud development 
• Strong software engineering experience 
• Experience working in a professional services organization 
• Product mentality but a professional services approach