Senior machine learning engineer

We are a Silicon Valley based product company building a next‑generation AI‑native B2B platform for hospitality. We’re looking for a

Senior Machine Learning Engineer

who is excited about the craft of machine learning—especially the

mathematical and statistical foundations

behind models—and who can turn that depth into solutions that scale in real-world use. If you’re someone who enjoys choosing the right model for the problem, validating it rigorously, and improving it through iteration, you’ll feel at home here.

This is an opportunity for an engineer who wants to

grow into a future architect , help define large-scale backend systems, and become a true

technical champion

within the team. If you are passionate about modern backend engineering, clean architecture, and scalable distributed systems, you’ll love working with us.

What you’ll do Design, train, and improve

statistical and machine learning models

for real product use cases. Apply strong fundamentals in

probability, statistics, and modeling

to make sound decisions on approach and evaluation. Build

scalable ML solutions

that can be used reliably in production environments. Develop capabilities to support

agent-like experiences

within our platform (e.g., intelligent workflows, tool-using behaviors, retrieval patterns, guardrails). Define and monitor meaningful model metrics, run error analysis, and iterate based on results.

What we’re looking for We’re intentionally not treating this as a checklist. If you’re strong in the fundamentals and have built real ML systems, we’d love to hear from you. You’ll

be successful

in this role

if you have : Strong knowledge across a broad range of

machine learning algorithms

(supervised/unsupervised methods, ensembles, linear models, tree-based methods, deep learning basics) and the judgment to choose appropriately. Solid grounding in

statistics and mathematical reasoning

(e.g., bias/variance tradeoffs, uncertainty, evaluation design). Experience building ML solutions in practice: data understanding, feature design, training, evaluation, and iteration. Strong Python skills and the ability to write clear, maintainable code. Familiarity with standard ML tooling (e.g., scikit-learn, PyTorch/TensorFlow). Nice to have (not required) Experience with

NLP and/or LLMs

(helpful, but not a core requirement). Exposure to ML-related capabilities on

AWS , such as training/inference workflows or managed ML services (e.g., SageMaker), and working with storage/data access patterns commonly used for ML. Experience implementing or integrating

vector search / embedding-based retrieval .

Why Join Us You will work in a modern, AI-native engineering culture building applied machine learning systems that ship. You’ll have the opportunity to design mathematically grounded models, turn them into scalable product capabilities, and help define how intelligent agents live inside our platform. This role is ideal for someone who loves ML fundamentals, enjoys solving real problems end-to-end, and wants to grow into a senior technical leader shaping our ML direction.

Equal Opportunity Directful is an equal opportunity employer. We welcome candidates of all backgrounds and do not discriminate on the basis of any protected characteristic.