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Senior Machine Learning Engineer, Real-Time Bidding

Trellis
locationBoston, MA, USA
PublishedPublished:Β 6/14/2022
Engineering
Full Time

Job Description

Job Description

Trellis is a profitable, fast-growing Series A startup backed by General Catalyst, QED, NYCA, and Amex Ventures. We're reimagining how people shop for home and auto insurance, using smart technology to make something historically painful feel refreshingly easy.

Every day, we help people save time, money, and unnecessary headaches. Behind the scenes, our fully remote team moves fast, owns their craft, and builds products that genuinely make life better.

Led by a three-time fintech founder with a proven track record of going big, we're building something special, and we're just getting started.

If you're hungry to make an impact and love solving complex problems with a scrappy crew, you'll love it here.

About the Role

Trellis is hiring a Senior Machine Learning Engineer to advance our real-time bidding (RTB) systems. You will design, implement, and scale ML models that directly power high-volume bidding decisions across millions of daily ad auctions. This includes end-to-end ownership of the ML lifecycle: data exploration, feature engineering, model training, deployment, and monitoring in production. You'll leverage Google Cloud Platform services (BigQuery, Vertex AI, Dataflow, Pub/Sub) and Python-based ML frameworks (TensorFlow, PyTorch, Scikit-learn) to deliver measurable improvements in bidding efficiency and ROI.

This is a fully remote position, based in the US or Canada, and will report directly into the Head of RTB, Thomas Boquet.

What You'll Do

  • Research, design, and implement advanced ML models for conversion rate prediction, value estimation, and pacing.
  • Build robust feature pipelines with BigQuery and Dataflow, ensuring low-latency inference at scale.
  • Deploy, monitor, and continuously improve models in production using Vertex AI.
  • Develop and maintain MLOps frameworks to automate training, evaluation, and deployment.
  • Partner with backend and distributed systems engineers to integrate models into high-throughput bidding services.
  • Contribute to experimentation frameworks and AB testing of ML-driven bidding strategies.

What You'll Need

  • 5+ years of ML engineering experience, including end-to-end deployment in production environments.
  • Proficiency in Python and ML frameworks (TensorFlow, PyTorch, or Scikit-learn).
  • Experience with cloud ML platforms, preferably GCP (Vertex AI, Dataflow, Pub/Sub, BigQuery).
  • Familiarity with MLOps practices (CI/CD for ML, monitoring, reproducibility).
  • Strong data skills: SQL, feature engineering, and big data processing.
  • A pragmatic mindset: delivering fast, measurable improvements while balancing complexity and scale.

Why Trellis? Because life's too short for boring jobs.

We're a team of builders, dreamers, and doers reshaping an industry that touches every household in America. At Trellis, you'll have real ownership, meaningful impact, and the chance to grow alongside a company that's scaling fast.

Here's what makes Trellis an incredible place to build your career:

  • ✨ A flat, transparent culture where your voice actually matters

  • πŸš€ Ground-floor opportunity with room to stretch and grow

  • 💰 Compensation at the 75th+ percentile

  • 🏑 100% remote... work from wherever you do your best thinking (In the US or Canada, that is)

  • πŸŽ‰ Quarterly team events that keep our fully remote culture connected and fun

And yes, the perks are pretty great too:

  • 🌴 Flexible vacation (seriously, we want you to take it)

  • 🩺 100% employer-paid health insurance for employees (65% for dependents)

  • 💻 Home office budget to set up your perfect workspace

  • πŸ§˜πŸΌοΈβ€β™‚οΈ Wellness events throughout the year, because we believe in investing in the full human, not just the employee
  • πŸ’Έ Automatic 401(k) contribution, FSAs, bonuses, and equity opportunities to invest in your future

  • 🐣 Paid parental leave

πŸ‘‰ If you're looking for a place where you can do the best work of your career, while building something that actually matters, we'd love to meet you.

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