Senior ML Engineer
Ping Data Intelligence | REMOTE or ONSITE (Miami, FL) | Full-Time | https://www.pingintel.com
Ping Data Intelligence is a dynamic startup based in Miami, FL, revolutionizing the property insurance sector with cutting-edge web technologies and ML-powered tools. Despite rapid growth, we retain the stability of a self-funded, profitable company.
About the Role
As a Senior ML Engineer at Ping, you will sit at the intersection of research and data engineering — designing, training, and deploying machine learning models that power our property attribute classification, document extraction, and geospatial products. This is a hands-on role for someone who can read a paper in the morning, prototype an idea by lunch, and ship it to production by end of week. You will own ML systems end-to-end: from data pipeline design and feature engineering through model training, evaluation, and production deployment. The role is remote-friendly, with the option to work onsite at our Miami, FL office.
Responsibilities
- Design, train, fine-tune, and evaluate ML models (LLMs, classification, sequence models) for property insurance.
- Build and maintain robust data pipelines that feed training, evaluation, and inference workloads at scale.
- Develop rigorous evaluation frameworks — establish metrics, build rater alignment processes, and apply statistical methods to determine when a candidate model is genuinely better than production.
- Run controlled experiments, ablations, and A/B tests; communicate findings clearly with appropriate uncertainty quantification.
- Deploy models to production and own their performance, drift monitoring, and iteration cycles.
- Collaborate with the engineering team to integrate ML services into our backend (Django/Python) and frontend (React/TypeScript) products.
- Stay current with the ML literature and translate relevant advances into practical improvements for our products.
Requirements
- PhD in Statistics, Machine Learning, Computer Science, Applied Mathematics, or a closely related quantitative field (or equivalent research experience with a strong publication or production track record).
- Strong foundation in statistics — experimental design, hypothesis testing, Bayesian methods, and uncertainty quantification.
- Minimum 5 years of combined research and applied ML experience, with a proven track record of shipping models to production.
- Deep proficiency in Python and the modern ML stack (PyTorch, Hugging Face, scikit-learn, pandas, NumPy).
- Hands-on experience with LLMs, including fine-tuning (LoRA/QLoRA, full fine-tunes), prompt engineering, and evaluation.
- Strong data engineering skills — comfort building reliable pipelines over messy real-world data, working with SQL and columnar formats.
- Excellent debugging, problem-solving, and written communication skills.
Why Join Ping
- Work directly on ML systems that touch real production traffic from day one.
- Collaborate with a small, senior team of insurance and tech veterans building products that are reshaping the property insurance industry.
- Enjoy the autonomy of a research role with the impact of an applied one — your models will be in production, used by real customers, and you will see the results immediately.
To Apply
Please apply at jobs@pingintel.com