Software Engineer / MLOps / Hybrid in Chicago
Chicago, Illinois
Hybrid
Full Time
A venture-backed firm is hiring a Software Engineer to support its internal machine learning team. The team builds infrastructure and data platforms used to drive investment decisions across high-growth, deep tech companies. This is a full-time role focused on MLOps, data engineering, and platform development.
You will be part of a small and highly technical team. The work will focus on building and scaling infrastructure that enables real-time insights. Projects include managing Kubernetes clusters, building Spark pipelines, designing internal ML tooling, and supporting data workflows. This role is ideal for an engineer looking for a fast paced and collaborative opportunity.
Required Skills & Experience
• 4+ years in software engineering and machine learning
• Hands-on Kubernetes and Docker experience
• Experience building infrastructure from scratch
• Experience supporting ML models or ML teams in production
• Familiarity with GCP or other cloud platforms
• Terraform or infrastructure-as-code tools
• CI/CD pipelines
Desired Skills & Experience
• Spark, Airflow, or Prefect
• MLflow, DVC, or other ML tools
• Data pipeline experience (dbt is a plus)
• High-performance or low-latency systems experience
• GitHub portfolio or examples of backend/API work
What You’ll Be Doing
Tech Breakdown
• 60% MLOps
• 25% Platform Engineering
• 15% Data Engineering
Daily Responsibilities
• 80% Hands-on Development
• 20% Cross-Team Collaboration
The Offer
• Competitive salary aligned with candidate's expectations
• Bonus eligible
• Medical, Dental, and Vision Insurance
• Paid Vacation
• Stock Options
Applicants must be authorized to work in the U.S. on a full-time basis now and in the future.
#LT-1
You will be part of a small and highly technical team. The work will focus on building and scaling infrastructure that enables real-time insights. Projects include managing Kubernetes clusters, building Spark pipelines, designing internal ML tooling, and supporting data workflows. This role is ideal for an engineer looking for a fast paced and collaborative opportunity.
Required Skills & Experience
• 4+ years in software engineering and machine learning
• Hands-on Kubernetes and Docker experience
• Experience building infrastructure from scratch
• Experience supporting ML models or ML teams in production
• Familiarity with GCP or other cloud platforms
• Terraform or infrastructure-as-code tools
• CI/CD pipelines
Desired Skills & Experience
• Spark, Airflow, or Prefect
• MLflow, DVC, or other ML tools
• Data pipeline experience (dbt is a plus)
• High-performance or low-latency systems experience
• GitHub portfolio or examples of backend/API work
What You’ll Be Doing
Tech Breakdown
• 60% MLOps
• 25% Platform Engineering
• 15% Data Engineering
Daily Responsibilities
• 80% Hands-on Development
• 20% Cross-Team Collaboration
The Offer
• Competitive salary aligned with candidate's expectations
• Bonus eligible
• Medical, Dental, and Vision Insurance
• Paid Vacation
• Stock Options
Applicants must be authorized to work in the U.S. on a full-time basis now and in the future.
#LT-1