Data Science & Engineering Manager (AI/ML)

TL;DR

Data Science & Engineering Manager (AI/ML): Leading the data engineering and applied data science function that builds scalable data platforms, production ML systems, and algorithmic solutions for internal operations and member-facing outdoor experiences with an accent on data infrastructure, governance, reliability, and personalization. Focus on designing batch and streaming pipelines, productionizing machine learning, improving platform performance, and guiding a team of senior data and engineering professionals.

Location: Remote within the United States. Preference for candidates based in or near San Francisco, Portland, Seattle, Denver, or New York; San Francisco employees are highly encouraged to work from the office one day per week.

Company

hirify.global is an outdoor exploration platform connecting a global community with trails and outdoor adventures through its mobile apps and website.

What you will do

• Lead, hire, coach, and develop data engineers and applied data scientists while maintaining a high-performing and inclusive team.
• Partner with business and product leaders to translate needs into technical requirements and prioritize platform and applied data initiatives.
• Guide the architecture and delivery of scalable batch and streaming pipelines, ML platforms, and algorithmic systems.
• Oversee orchestration, data transformation, monitoring, alerting, troubleshooting, and reliability across the data ecosystem.
• Establish data governance, quality, privacy, compliance, cataloging, documentation, and self-service capabilities.
• Improve time-to-insight, debugging speed, deployment velocity, and the use of AI and automation across the business.

Requirements

• 5+ years of data engineering experience and 3+ years managing data engineering, machine learning, or data science teams.
• Hands-on experience with GCP data infrastructure, governance, data access, storage, caching, and optimization.
• Strong experience with BigQuery or Snowflake, SQL, Python, Dataform or dbt, and Apache Airflow.
• Experience designing complex pipelines with Dataflow, Spark, or similar parallelized processing frameworks, plus dimensional and star-schema modeling.
• Deep familiarity with Docker, Kubernetes, CI/CD, observability, code reviews, and on-call operations.
• Track record guiding teams through MLOps and applied use cases such as recommendations, ranking, personalization, and classification.

Nice to have

• Experience with geospatial data, maps, tiling, graph databases, or routing.
• Experience in multi-cloud environments using GCP and AWS.
• Experience at a B2C company or managing infrastructure as code with Terraform.

Culture & Benefits

• Remote work with a stipend for a comfortable and productive home office.
• Health, dental, and vision coverage, 401(k) matching, and financial wellness resources.
• Unlimited paid time off, company holidays, and fully paid parental leave.
• Annual learning stipend and monthly company-wide no-meeting days for product improvement.
• Equity, performance-based bonuses, subscription and merchandise discounts, and an inclusive workplace.