Overview
On Site
0.00k - 0.00k
Full Time
Skills
Recruiting
FOCUS
Real-time
Management
Workflow
Software Engineering
Kubernetes
Docker
Scratch
Google Cloud
Google Cloud Platform
Cloud Computing
Terraform
Continuous Integration
Continuous Delivery
Apache Spark
Machine Learning (ML)
Extract
Transform
Load
GitHub
API
Machine Learning Operations (ML Ops)
Data Engineering
Collaboration
Insurance
SAP BASIS
Job Details
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 Google Cloud Platform 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 Google Cloud Platform 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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.