Machine Learning Engineer

Range is creating AI-powered solutions to eliminate financial complexity for our members. We’re transforming wealth management through the perfect blend of cutting-edge technology and human expertise. We’re obsessed with member experience! We’ve built an integrated platform that tackles the full spectrum of financial needs–investments, taxes, retirement planning, and estate managment–all unified in one intuitive system.

Backed by Google's Gradient Ventures and Cathay Innovations, we're in hyper-growth mode and looking for exceptional talent to join our starting lineup. Every Ranger at this stage is shaping our culture and way of life—from former CEOs and startup founders to experts from leading hedge funds and tech companies.

If you're ready to build something that truly matters in financial services, bring your talent to Range. Here, you'll make a genuine impact on how people manage their financial lives while working alongside a team that celebrates wins, makes big decisions, and blazes new trails together

About the role

Range is hiring for a Machine Learning Engineer to help advance our AI-powered wealth management platform. This engineer will work closely with product and data teams to enhance our data pipelines, build and deploy lightweight ML models, and evolve the infrastructure that supports our production data and model workflows.

The ideal candidate has experience building and operationalizing machine learning systems that are performant, maintainable, and aligned with product goals. As an ML Engineer, you’ll be responsible for designing and implementing data transformations, training and deploying models in production, and improving the observability and scalability of our ML stack. You’ll play a key role in shaping our approach to data-driven automation while partnering with engineers, data scientists, and product managers to ensure our ML systems deliver real value to our users.

We're excited to hire this role at Range's Headquarters in McLean, VA, or one of our hub locations in New York City, or Seattle. All of our positions follow an in-office schedule Monday through Friday, allowing you to collaborate directly with the team. If you're not currently based in one of these areas but love what you see, let’s discuss relocation options as part of your journey to joining us.

What you’ll do with us

• Build and deploy lightweight ML models that power intelligent, user-facing financial features across our platform

• Partner with product and engineering teams to enhance our production data stack and enable new ML-driven capabilities

• Improve the performance and maintainability of our ML systems by refining data pipelines, model architectures, and deployment workflows

• Help shape our approach to data collection, labeling, and feature engineering to support robust model training and evaluation

• Bring modern best practices in machine learning engineering—including monitoring, versioning, and continuous deployment—and help the team stay ahead as the ML ecosystem evolves

What will set you apart

• Hands-on experience with modern data and ML stacks and a strong perspective on their strengths, weaknesses, and evolving capabilities

• A track record of building ML-powered product features such as intelligent workflows, personalized recommendations, or real-time financial insights—not just proof-of-concepts

• Experience integrating structured data for search and retrieval with generative AI technologies like embedding models and vector databases

• Comfort working across the ML lifecycle: writing clean, production-ready code, deploying to cloud infrastructure (AWS preferred), and setting up real-time monitoring and alerting

• Fluency with AWS services including EC2, ECS, RDS, DynamoDB, S3, and CloudWatch—or equivalent cloud platforms

• Strong product sense: you’re motivated by helping users get smarter, faster answers—not just pushing the boundaries of ML for its own sake

• Proven ability to tackle ambiguous problems, work independently, and bring structure to chaos in a fast-moving startup environment

• Bonus points for experience with security, regulated industries like fintech, or building AI systems that meet compliance and reliability standards
  

Benefits

• Health & Wellness: 100% employer-covered medical insurance for employees (75% for dependents), plus dental and vision coverage

• 401(k): Retirement savings program to support your future

• Paid Time Off: time to reset and recharge + most federal holidays

• Parental Leave: Comprehensive leave policy for growing families

• Meals: Select meals covered throughout the week

• Fitness: Monthly movement stipend

• Equity & Career Growth: Early exercise eligibility and a strong focus on professional development

• Annual Compensation Reviews: Salary and equity refreshes based on performance

• Boomerang Program: After two years at Range, you can take time away to start your own company. We’ll hold your spot for 6 months - and pause your equity vesting, which resumes if you return

Range is proud to be an equal opportunity workplace. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. As a company, we are committed to designing products, building a culture, and supporting a team that reflects the diverse population we serve.