About the role

Arthur is looking for a product-focused Machine Learning Engineer to join our team, to operate with autonomy and with the support of the team to lead and build out our product vision and deliver value to our customers.

What you'll do

Focus on ML, especially LLMs, modelperformance, 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 modelmonitoring: 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

What we're looking for

3-5+ 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

You might also have (nice to have)

Experience with public cloud services, such as AWS, Google Cloud, or Azure
Experience or interest in interactive machine learning, HCI, human-centered ML and LLM evaluation, etc.
Experience or interest in explainability and fairness of recommender systems
A body of ML-focused publications (we tend to have a presence at NeurIPS/ICML, KDD, AAAI, CHI, and the newer responsible AI conferences like SaTML, FAccT, and AIES), technical blogging, and/or open source projects
A Masters or PhD in a quantitative field – we’re not sticklers for degrees (many of us have Masters/PhDs, so we intimately understand thisisn’tthe only way to be a domain expert)

What to expect at Arthur

Teammates who value curiosity, hard work, collaboration, and creative problem-solving -- and good swag.
A team of professionals who are passionate about our work and making a positive impact through AI.
A caring culture; we value and prioritize our team’s physical and mental health, encouraging and celebrating life outside of work.
Autonomy to pursue your role and interests with room to grow, with a team behind you that always has your back.
Joy, humor, and a little dose of healthy competition (in our business, we win as a team; on company game night, may the best Arthurian win…).

We offer

Competitive compensation plus medical, dental, and vision insurance, and a 401K.
Our target base salary range for this role is $160,000 - $230,000, based on your experience and how your skills align with role requirements
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 cover a masters in computer science, or support ways to learn and grow in the areas that matter to you.
Highly discounted fitness and wellness 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 with our team in NYC.