Machine Learning Engineer
March 19
🔄 Hybrid – Manhattan
Description
• Focus on ML, especially LLMs, model performance, security, and robustness: make LLMs and model-based systems respond accurately, quickly, and comprehensively to general and task-specific interactions by both natural and adversarial users – for example, checking veracity of responses, hardening against prompt injection, query-based routing to different models, and generation of evaluation datasets • Build out new techniques and tooling in ML model monitoring: data drift detection, high-dimensional density estimation, time series anomaly detection; detection and mitigation of issues in fairness and bias in ML algorithms • Run machine learning experiments independently and in collaboration with product teams, and communicate results to internal stakeholders as well as the broader ML community via publications in top-tier conferences, industry conference presentations, deep technical blogs, and events • Drive value creation using our product with our customers in collaboration with our customer teams by engaging in targeted and focused short-term project work to understand, experiment, refine and deploy ML-enabled features for customer use-cases
Requirements
• 5+ years of professional experience in Machine Learning, and/or Engineering providing strong ML support, or Data Science/Statistics with 2+ years of Engineering expertise • Deep experience writing production-grade python, in addition to experience using ML frameworks, such as JAX, Tensorflow, or PyTorch • Understanding of software engineering best practices, version control, and containerization • Customer empathy and a willingness to engage directly with customers and stakeholders • Experience with deploying ML models to production and with comprehensive model risk management • Deep interest in LLMs (to start) and multimodal generative models (soon!), specifically around measuring bias or performance • Enthusiasm for staying up to date on the latest developments in the field – we operate in a nascent space with plenty of signal and plenty of noise coming from arXiv and open source projects • Knowledge of and ability to (re)learn statistical methods and contemporary ML algorithms
Benefits
• Competitive compensation plus medical, dental, and vision insurance, and a 401K (with matching) • Equity in what we’re building together, backed by some of the most respected VCs in the industry • A flexible learning and development budget: we’ll support ways to learn and grow in the areas that matter to you • Highly discounted wellness and fitness benefits • Flexible PTO with vacation minimums, which we really want you to take and enjoy • The ability to work in a highly flexible hybrid environment - both from home, and from our NYC office with our team
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