Senior Staff Machine Learning Platform Engineer

Faire

Senior Staff Engineer architecting Faire’s machine learning platform for a global technology wholesale marketplace. Scaling ML workflows, Databricks infrastructure, governance, and AI productivity tools.

Posted 8/19/2026full-timeRemote • Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Idaho, Illinois, Kentucky, Maine, Maryland, Massachusetts, Minnesota, Missouri, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Utah, Virginia, Washington, Wisconsin • 🇺🇸 United StatesSenior💰 $295,000 - $405,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in Databricks lakehouse architecture and machine learning platform evolution, with a strong focus on technical leadership, system design for data science teams, and optimizing ML workflows. Proficient in mentoring and establishing standards for code quality and MLOps practices.

Highest-signal resume keywords

Databricks Lakehouse ArchitectureMachine Learning Platform DevelopmentTechnical LeadershipPython ProficiencyMLOps (CI/CD) Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData Platform DevelopmentDistributed SystemsCloud ArchitectureSQLKotlinPyTorchPySparkSparkMLflow

Soft Skills

MentoringTechnical AdvisingCollaboration

Tools & Technologies

DatabricksUnity CatalogAWSS3KubernetesDockerGitHub ActionsTerraformKafkaAirflow

Industry Keywords

MLOpsFeature ManagementModel Lifecycle ManagementObservabilityData/ML Mesh Patterns

Tech Stack

Tools & technologies

AirflowAWSCloudDistributed SystemsDockerKafkaKotlinKubernetesMySQLOpen SourcePySparkPythonPyTorchSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Own the technical vision and evolution of Faire’s machine learning platform
Define and drive long-term architecture covering training, inference, feature management, and governance
Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability
Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns
Architect scalable ML workflows using Spark, Delta Lake, and MLflow
Optimize platform performance, reliability, and cost
Evaluate and integrate emerging Databricks features
Engage with the latest developments in machine learning and AI
Advise Faire’s data science and production engineering teams as a senior ML technical advisor
Represent Faire at ML conferences and meetups
Mentor ML engineers and raise the overall machine learning standard at Faire

Requirements

What you’ll need

10-12 years of experience building and improving large-scale ML or data platforms
A degree in Computer Science, Engineering, Statistics, or a related technical field (graduate level preferred)
Deep expertise in Databricks lakehouse architecture, including Unity Catalog governance, Workflows orchestration, and cost optimization
Ability to design systems supporting multiple data science teams and production workloads
Strong background in distributed systems, ML infrastructure, and cloud architecture
Demonstrated technical leadership across teams and organizations
Proficiency with Python, SQL, Kotlin, PyTorch, PySpark, MLflow, Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL, AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform, Claude Sonnet 4.5, and ChatGPT 5.2
Experience integrating LLM workflows into enterprise platforms is a plus
Contributions to open source ML infrastructure projects or research publications are a strong plus

Benefits

Comp & perks

Equity
Comprehensive benefits
Latest enterprise AI tools
Competitive pay
Equal access to opportunities, growth, and success
Reasonable accommodation throughout the recruitment process
Hybrid employees may work remotely up to 4 weeks per year