Staff Machine Learning Engineer, Trellis
+ Bonuses and equity opportunities
P&C insurance data services
Posted today
P&C insurance data services
21-100 employees
Posted today
+ Bonuses and equity opportunities
21-100 employees
Company mission
To build industry-leading solutions that make insurance easy for everyone, from consumers to partners to insurers.
Role
Who you are
- Analytical & Detail-Oriented: You have a solid grounding in statistics and machine learning, with a keen eye for detail
- Collaborative Communicator: You excel at working cross-functionally, ensuring technical and business trade-offs are clearly understood
- Self-Motivated & Pragmatic: You thrive in fast-paced environments, managing multiple priorities while delivering practical, scalable solutions
- Innovative Problem-Solver: You’re eager to tackle complex challenges, iterating quickly and learning continuously
- Proficiency with complex queries, performance tuning, and managing large-scale data processing
- Experience collaborating with a Data Engineering team to ensure data integrity and efficiency
- Experience with or good understanding of the RTB ecosystem (DSPs, SSPs, auctions, ROI optimization) and designing low-latency systems
- Solid foundation in statistics, probability, and modern ML techniques
- Proficiency with frameworks like TensorFlow, PyTorch, XGBoost/Catboost, or scikit-learn
- Demonstrated success working with cross-functional teams, clearly articulating technical and business trade-offs
- Self-driven and capable of managing multiple priorities while making practical trade-offs in a dynamic startup environment
- Proven experience designing, deploying, and maintaining services on GCP or another major cloud platform
- Deep hands-on experience with Kubernetes for container orchestration and microservices architecture
What the job involves
- As a Staff Machine Learning Engineer on Trellis’s Real-Time Bidding team, you will build, deploy, and optimize the ML models that drive >$100 million of annual programmatic marketing spend
- You will work side-by-side with our Data Engineering team to harness high-quality data, craft robust real-time solutions, and continuously enhance model performance in a low-latency, revenue-critical environment
- Design, build, deploy, and improve ML models that power our real-time bidding platform
- Continuously monitor, evaluate, and optimize model performance for maximum ROI
- Work cross-functionally with product and business stakeholders to translate high-level objectives into tangible, ML-driven solutions that maximize ROAS in programmatic auctions
- Utilize advanced statistical techniques and modern ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.) to predict auction outcomes and user behaviors
- Incorporate real-time feedback loops to adapt swiftly to shifts in the RTB marketplace
- Mentor and guide team members through technical leadership, code reviews, and sharing best practices
- Balance urgency with the delivery of robust, scalable solutions in a dynamic startup environment
- Leverage Kubernetes and managed services on GCP to deploy and orchestrate low-latency, high-availability services
- Implement best-practice observability, logging, and monitoring to ensure system reliability and efficiency
Our take
Changing insurance providers can be a daunting and overwhelming process. Its a complex and lengthy undertaking, resulting in many people sticking to the same provider, even if it doesn't best suit their needs.
Recognizing the need for a better solution is Trellis, that delivers an API platform for consumers to compare insurance policies side-by-side. It also partners with digital banks and financial institutions to offer new insurance options to their existing customers - a feature which allows it to stand out from the competition.
Trellis has seen exponential growth since founding in 2019, and has secured strong funding from the likes of Amex Ventures. The company is now in a prime position to accelerate its offerings and further innovate the insurance market.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
May 2022
$5m
EARLY VC
Jun 2021
$10m
SERIES A
Total funding: $15m
Company benefits
- Bonuses and equity opportunities
- Unlimited vacation time
- 100% employer-paid insurance for employee, 60% for dependents
- 401K plan
- Annual in-person retreats
Company values
- Speed: We work quickly and pragmatically. We move fast and get things done
- Craft: We are constantly learning and better ourselves and the way we work.
- Extreme Ownership: We fulfill our promises to each other and our customers. We own our responsibilities 110%
- Collaboration: We work transparently, solicit feedback, and leave our egos at the door
- Positivity: We see a cup half-full, focus on the teams potential, and rise to the challenges
Company HQ
SoMa, San Francisco, CA
Articles
Leadership
Daniel Demetri
(Founder & CEO)Previously co-founded the insurance company, Doma. Also worked as a Product Manager at Google as well as a Product Lead/Head of Product Management at Earnest.
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