Description
Lead ML Ops Data Scientist
Location: Remote within the US
Department: Data Science
Location Type: REMOTE
Employment Type: FULL_TIME
Remote (U.S.) | Data Science & Machine Learning
At Apartment List, we’re on a mission to help every renter find a home they love at the value they deserve. As one of the fastest-growing online rental marketplaces, we use data and machine learning to understand renter preferences and match them seamlessly with the right property. To date, we’ve helped over one million families find a home they love — and we’re just getting started. Join us!
The Opportunity
Apartment List is seeking a Lead ML Ops Data Scientist to help us scale and accelerate our use of machine learning across the renter and property experience. Our Data Science team has a strong foundation and a rich roadmap of high-impact initiatives — from personalized search to real-time AI-driven journey optimization. To fully realize this potential, we need a strong leader who can bridge the worlds of data science and engineering.
In this role, you’ll design and evolve the machine learning systems, infrastructure, and practices that allow us to move faster, build and deploy more sophisticated models, and drive measurable business impact. You’ll lead by doing — developing our platform and models yourself while enabling the broader team to experiment, iterate, and deploy at scale.
What You’ll Do
- Design and implement scalable MLOps systems and practices that streamline model development, deployment, and monitoring.
- Partner closely with Engineering and Product to ensure data scientists can experiment and deploy models quickly, efficiently and safely.
- Build tools and frameworks that automate or simplify feature integration, retraining, and experimentation.
- Develop and deploy production models for ranking, recommendation, and personalization, leveraging modern ML architectures and frameworks.
- Mentor data scientists on best practices in applied ML and MLOps, fostering a culture of technical excellence and efficiency.
- Continuously identify and address bottlenecks in our ML workflows to expand the team’s capacity for innovation.
What You’ll Bring
- A degree in Computer Science or Engineering, or related fields.
- 5+ years of experience developing, deploying, and maintaining machine learning models in production environments.
- Strong proficiency in Python, SQL, and cloud platforms (GCP/Vertex AI preferred).
- Experience building or standardizing ML platforms and infrastructure.
- Deep understanding of ML lifecycle management, CI/CD for ML, and monitoring tools.
- Hands-on experience with modern ML frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost), and orchestration and distributed computing tools (Airflow, MLflow, Kubeflow, Dask, Ray, or dbt).
- Proven ability to collaborate cross-functionally and lead technical initiatives that improve productivity and scalability.
- A passion for combining scientific rigor with strong engineering fundamentals.
Bonus Points For:
- Background in recommendation systems, ranking, or personalization.
- Contributions to open-source or shared ML tooling initiatives.
- Marketplace or PropTech experience.
- Advanced degree in a relevant field.
Why Join Us
- Impact: Shape the foundation of how machine learning powers every renter experience at Apartment List.
- Leverage: Multiply the output and effectiveness of the entire Data Science organization.
- Leadership: Blend hands-on technical work with strategic influence across Data Science and Engineering.
- Culture: A remote-first, high-bar environment where your work drives real results.
We’re building a diverse and inclusive team that reflects the renters we serve. If you’re excited about this opportunity but don’t meet every qualification, we still encourage you to apply.
Join us and help unlock the next era of intelligent renting at Apartment List.
Here's the Pay Range:
At Apartment List, we carefully consider a variety of factors to determine compensation for each position, including the role, level, and work. The US Total Target Compensation (TTC) for this position is:
- Zone 1: $189,000 - $229,000 TTC (including $170,000 - $206,000 base salary) + equity
- Zone 2: $ 175,000 - $212,000 TTC (including $157,000 - $191,000) + equity
- Zone 3: $ 160,000 - $195,000 TTC (including $144,000 - $175,000 base salary) + equity
This reflects the compensation target for new hire salaries for the position across all US locations. Please note, the compensation details provided do not include benefits and perks that we offer.
There are more than 50,000 engineering jobs:
Subscribe to membership and unlock all jobs
Engineering Jobs
60,000+ jobs from 4,500+ well-funded companies
Updated Daily
New jobs are added every day as companies post them
Refined Search
Use filters like skill, location, etc to narrow results
Become a member
🥳🥳🥳 452 happy customers and counting...
Overall, over 80% of customers chose to renew their subscriptions after the initial sign-up.
To try it out
For active job seekers
For those who are passive looking
Cancel anytime
Frequently Asked Questions
- We prioritize job seekers as our customers, unlike bigger job sites, by charging a small fee to provide them with curated access to the best companies and up-to-date jobs. This focus allows us to deliver a more personalized and effective job search experience.
- We've got over 200,000 jobs from 15,000+ vetted companies. No fake or sleazy jobs here!
- We aggregate jobs from 15,000+ companies' career pages, so you can be sure that you're getting the most up-to-date and relevant jobs.
- We're the only job board *for* software engineers, *by* software engineers… in case you needed a reminder! We add thousands of new jobs daily and offer powerful search filters just for you. 🛠️
- Every single hour! We add 2,000-3,000 new jobs daily, so you'll always have fresh opportunities. 🚀
- Typically, job searches take 3-6 months. EchoJobs helps you spend more time applying and less time hunting. 🎯
- Check daily! We're always updating with new jobs. Set up job alerts for even quicker access. 📅
What Fellow Engineers Say