Lead Data Science Engineer (Machine Learning)

TL;DR

Lead Data Science Engineer (ML/Data Engineering): Designing and implementing data pipelines and AI/ML solutions for a venture focused on reinventing the heavy machinery industry with an accent on rapid prototyping, scaling MVPs, and building data-driven decision-making systems. Focus on bridging the gap between raw business concepts and functional industrial software while mentoring early-stage venture teams.

Location: Remote or Santa Monica, CA (USA)

Company

hirify.global is a venture studio partnering with global market leaders to build and launch transformative software businesses in industrial domains.

What you will do

• Act as the primary subject matter expert for Data Science, Analytics, and Data Engineering.
• Build and lead data science teams across several venture start-ups.
• Create rapid proofs of concept and scale them into functional MVPs to turn concepts into reality.
• Mentor early-stage venture teams to handle high data density and system complexity.
• Standardize data science best practices and cross-pollinate insights between multiple ventures.

Requirements

• 7+ years of experience in Data Science, Data Engineering, and Machine Learning domains.
• Hands-on experience in startup environments; founding team experience is ideal.
• Expertise in ML algorithms (Random Forest, Gradient Boosting, Regressions) and full-cycle model deployment and monitoring.
• Experience with major cloud platforms (Azure, GCP, AWS) and cloud-native architectures.
• Proficiency with data warehouse solutions such as Databricks, Snowflake, Fivetran, and DBT.
• Must be based in the US.

Nice to have

• Experience in transportation, aviation, or digital simulation domains.
• Knowledge of containerization (Kubernetes, Docker) and Infrastructure as Code (Terraform, OpenTofu).
• Familiarity with A/B testing setup and Reinforcement Learning for practical use cases.

Culture & Benefits

• High level of autonomy to take bold ideas from 0 to 1.
• Diverse, dynamic, and inclusive environment where all opinions are valued.
• Opportunity to work shoulder-to-shoulder with a global market leader in heavy machinery.
• Collaborative and transparent culture focused on continuous improvement.