Senior Machine Learning Engineer

September 20

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Description

• 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

Requirements

• 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

Benefits

• Be Yourself: Be the best version of your whole self. Your authenticity matters. • Be Bold: Bravely and respectfully take risks and challenge the norm. • Have a Growth Mindset: Be open to learning and apply your expertise. • Be the Difference: Ensure that every interaction with your colleagues, clients and community improves their lives. Pay it forward. • Assume Positive Intent: Lead with giving the benefit of the doubt.