At Tilt (formerly Empower), we see a side of people that traditional lenders miss. Our mobile-first products and machine learning-powered credit models look beyond outdated credit scores, using over 250 real-time financial signals to recognize real potential. Named among the next billion-dollar startups, we're not just changing how people access financial products — we're creating a new credit system that backs the working, whatever they're working toward.
The Opportunity, Machine Learning Engineer, APAC
As an Machine Learning Engineer focusing on MLOps, you will play a pivotal role in operationalising our ML models, ensuring they are scalable, reliable, and easy to monitor. Working in a small team of Data Scientists and Data Engineers in APAC, you'll build feature stores for model development, facilitate model refit/retrain iterations, enhance model deployment (CI/CD) pipeline, as well as strengthen model monitoring.
Tilt is a remote-first company. We drive connectivity through regular company offsites. Travel for company offsites is expected at a minimum 2 times a year.
What you'll be doing
Design and Implement Scalable MLOps Infrastructure: Develop and maintain the infrastructure required for the entire machine learning lifecycle, from data ingestion and model training to deployment and monitoring.
Build and Maintain Feature Stores: Design and implement robust feature stores to ensure consistent and efficient feature management across all ML models
Automate ML Workflows: Develop and implement CI/CD pipelines for machine learning models, automating the deployment and monitoring process.
Implement Resource Management and Orchestration: Utilize tools like Kubernetes, Airflow, or similar technologies to effectively manage and orchestrate ML resources.
Monitor and Debug Production ML Systems: Establish comprehensive monitoring and alerting systems to ensure the health and performance of deployed ML models.
Collaborate with Data Scientists and Server Engineers: Work closely with data scientists and server engineers to understand their infrastructure needs and provide effective solutions.
Why you're a great fit
3+ years of experience in MLOps, ML Engineering, or DevOps for machine learning.
Experience with machine learning algorithms and model development process.
Demonstrated programming/software engineering experience.
Strong expertise in cloud platforms (AWS, Azure or GCP) for ML deployment.
Strong knowledge of model monitoring tools (e.g., Evidently AI, MLflow).
Hands-on experience with orchestration frameworks
Familiarity with Pyspark and Databricks is a plus.
Able to effectively leverage AI-powered development tools (e.g., Cursor, Augment, Factory) to enhance productivity, code quality, and collaboration.
Don’t meet every qualification? We care about potential over your past. If you're bringing ambition and drive to what we're building, we want to hear from you.
Virtual-first teamwork: The Tilt team is collaborating across 14 countries, 12 time zones, and counting. You’ll get started with a WFH office reimbursement.
Competitive pay: We're big on potential, and it's reflected in our competitive compensation packages and generous equity.
Complete support: Find flexible health plans at every premium level, and substantial subsidies that stand up to global standards.
Visibility is yours: You can count on direct exposure to our leadership team — we’re a team where good ideas travel quickly.
Paid global onsites: Magic happens IRL: we gather twice yearly to reconnect over shared meals or kayaking adventures. (We’ve visited Vail, San Diego, and Mexico City, to name a few.)
Impact is recognized: Growth opportunities follow your contributions, not rigid promotion timelines.
We're looking for people who chase excellence and impact. Those who stand behind their work, celebrating the wins and learning from the missteps equally. We foster an environment where every voice is valued and mutual respect is non-negotiable — brilliant jerks need not apply. We're in this together, working to expand access to fair credit and prove that people are incredible. When you join us, it's not just another day at the [virtual] office, you're helping millions of hardworking people reach better financial futures.
You’re pushing ahead in your career? We can get behind that. Join us in building the credit system that people deserve.
