Tilt (formerly Empower) Logo

Tilt (formerly Empower)

Lead Machine Learning Engineer (MLOps)

Sorry, this job was removed at 10:10 p.m. (PST) on Friday, Oct 17, 2025
Remote
Hiring Remotely in United States
230K-270K Annually
Remote
Hiring Remotely in United States
230K-270K Annually

Similar Jobs

13 Days Ago
In-Office or Remote
United States
73K-171K Annually
Senior level
73K-171K Annually
Senior level
Information Technology
The Lead Machine Learning Engineer will optimize AWS SageMaker, manage ML pipelines, develop infrastructure as code with Terraform, build CI/CD pipelines, and collaborate with data scientists to deploy models in production.
Top Skills: Amazon SagemakerApi GatewayAWSAws LambdaDynamoDBGithub ActionsPythonServerless ArchitecturesSqsTerraform
14 Minutes Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
100K-125K Annually
Senior level
100K-125K Annually
Senior level
Cloud • Mobile • Software
Lead discovery, design, configuration, testing, and validation of accounting integrations between BuildOps and customers' ERPs. Map GL/accounts/entities, build and execute test plans for AP/AR/POs/payments, reconcile data, troubleshoot discrepancies, document solutions, and advise customers on best practices to ensure scalable, accurate end-to-end syncs.
Top Skills: APIsBoomiBuildopsCeligoCsvErpExcelGoogle SheetsIpaasMulesoftNetSuiteQuickbooks OnlineSage IntacctSpectrumViewpoint VistaWorkato
20 Minutes Ago
Easy Apply
Remote
USA
Easy Apply
186K-219K Annually
Senior level
186K-219K Annually
Senior level
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Own reliability, automation, and DevOps for Coinbase's corporate IAM platform: on-call/incident response, CI/CD and IaC pipelines, identity lifecycle tooling, observability and disaster recovery, documentation, and cross-team IAM advisement to ensure secure, scalable access for a global workforce.
Top Skills: AbacAuth0AWSAzureC#Ci/CdContainer OrchestrationDuoEntraidGCPGenerative AiGitGoIacJavaMfaOktaPingPythonRbacRubySsoTerraform
Join the Tilt team

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 Our mobile-first products and machine learning-powered credit models look beyond outdated credit scores, using over 250 real-time financial signals to recognize real potential.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: Lead Machine Learning Engineer (MLOps)

Our Machine Learning Engineering team, focusing on MLOps, is looking for a great technical lead. You will play a pivotal role in operationalizing our ML platform, including our production ML models, ensuring they are scalable, reliable, and easy to monitor. You’ll work closely with our data scientists, server engineers, and infrastructure teams to build feature stores for model development and inference, 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.

How You'll Make an Impact

  • Lead and help grow our ML Platform team

  • 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

  • 4+ years of experience in MLOps, ML Engineering, or DevOps for machine learning.

  • Experience with machine learning algorithms and model development process.

  • Strong expertise in cloud platforms (AWS or Azure) for ML deployment.

  • Experience with CI/CD pipelines (e.g., GitHub Actions, Jenkins) for ML.

  • Strong knowledge of model monitoring tools (e.g., Evidently AI, MLflow).

  • Hands-on experience with orchestration frameworks (e.g., Airflow, Kubeflow).

  • Familiarity with Pyspark and Databricks is a plus.

  • Familiarity with infrastructure-as-code (Terraform, CloudFormation) 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.

What you'll get at Tilt
  • 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.

The Tilt Way

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.

HQ

Tilt (formerly Empower) San Francisco, California, USA Office

660 York St, San Francisco, CA , United States, 94110

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account