Staff MLOps Engineer

Grindr • Palo Alto, CA

1d • Hybrid

About The Position

We at Grindr believe that AI can revolutionize the dating industry. As a Staff MLOps Engineer, you will build and own the infrastructure, tooling, and scalable systems that make high-impact AI possible. You’ll architect and maintain the platforms that power data ingestion, feature computation, model training, automated evaluation, deployment, and ongoing monitoring for the ML teams building recommendations, LLM-based experiences, ads, visual search, growth, and trust & safety. You will design foundational systems that allow our ML engineers to experiment faster, ship models more reliably, and operate them with confidence in production. We’re looking for an exceptional MLOps engineer who’s passionate about enabling ML at scale, (>6M daily active users and 100’s of millions of daily user interactions). Someone who loves building robust, automated pipelines; creating reliable production training and inference systems; and establishing the infrastructure and processes that accelerate ML product development across the organization. In this role, you will shape and execute the strategy for Grindr’s ML platform and end-to-end model lifecycle.

Requirements

• Bachelor’s degree in CS, Engineering, Mathematics, or related field.
• 5+ years experience in MLOps, ML platform engineering, ML infrastructure, or similar roles.
• Strong experience building production ML pipelines and supporting end-to-end ML workflows.
• Excellent engineering fundamentals: Python, SQL, bash, Git.
• Experience with big data and distributed compute: Snowflake, Spark/pySpark, Airflow, Kubernetes, Docker, Helm.
• Experience with ML frameworks (PyTorch, TensorFlow) sufficient to support training pipelines and deployment workflows.
• Strong understanding of cloud platforms (AWS, GCP, or Azure).
• Ability to produce well-engineered, maintainable software with tests, documentation, and operational rigor.
• Experience with data quality frameworks, observability tooling, or experiment tracking systems.

Nice To Haves

• Experience implementing full model lifecycle management (from data → training → deployment → monitoring).
• Experience with vector databases, embeddings pipelines, or retrieval systems.
• Familiarity with NLP/LLM-based data pipelines or image/vision data workflows.
• Experience with recommendation system infrastructure.
• Strong grasp of classical ML concepts as they relate to platform design.
• Knowledge of data governance, compliance, retention, and classification.
• Track record of partnering with research/ML teams to operationalize models at scale.

Responsibilities

• Build and maintain end-to-end ML pipelines for data ingestion, feature computation, model training, validation, deployment, and inference, all at substantial scale of data
• Stand up and manage a feature store, ensuring feature consistency, lineage, and reuse across teams.
• Expertise with best in class tools for managing deployment, scheduling, and environments and how to use them in the specialized regime of ML Infrastructure.
• Develop automated model deployment workflows with CI/CD, safe rollout strategies, and reproducibility guarantees.
• Implement monitoring and observability for ML systems, including data quality checks, drift detection, performance metrics, and alerting.
• Build and support training environments with experiment tracking, distributed training, hyperparameter tuning, and artifact and environment management.
• Collaborate with ML engineers and data engineers to streamline workflows, improve model iteration speed, and enforce MLOps best practices.
• Ensure reliability, scalability, and maintainability of ML systems through strong engineering and operational rigor.

Benefits

• Family Insurance: Insurance premium coverage for health, dental, and vision for you and partial coverage for your dependents.
• Retirement Savings: Generous 401K plan with 6% match and immediate vest in the U.S.
• Compensation: Industry-competitive compensation and eligibility for company bonus and equity programs.
• Queer-Inclusive Benefits: Industry-leading gender-affirming offerings with up to 90% cost coverage, access to Included Health, monthly stipends for HRT, and more.
• Additional Benefits: Flexible vacation policy, monthly stipends for cell phone, internet, wellness, food, and commuting, breakfast/lunch provided onsite, and yearly travel & leisure stipend.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 101-250 employees