Senior MLOps Engineer in United State

Location: Remote

Salary: Based on experience

Type: Full-time

We're seeking a Senior MLOps Engineer to design and build our ML infrastructure from scratch. This is not a role for someone looking to maintain existing systems – we need an experienced engineer who thrives on creating foundational architecture in a startup environment. You'll be responsible for systems that enable our trading algorithms to operate reliably at scale.

• Design and implement cutting edge MLOps architecture
• Optimize systems for massively parallel operations
• Establish experiment management and model versioning frameworks (MLflow or similar)
• Design and implement feature store architecture for trading data
• Create automated drift detection and model monitoring systems

• Set up orchestration systems for complex trading workflows
• Implement containerized, multi-language pipelines
• Migrate legacy systems to production-ready infrastructure
• Establish CI/CD practices and deployment automation

• Make foundational technology stack decisions
• Design systems that can handle the unique requirements of financial trading
• Build monitoring and alerting systems for mission-critical trading operations
• Collaborate with trading team to understand business requirements and translate them into technical architecture

• 5+ years of MLOps/DevOps experience, with significant time building systems from scratch
• Proven track record establishing MLOps practices in startup or early-stage environments
• Strong experience with containerization (Docker, Kubernetes) and orchestration platforms
• Expertise in cloud infrastructure (AWS, GCP, or Azure) and infrastructure as code
• Experience with ML frameworks and experiment management tools (MLflow, Kubeflow, etc.)
• Proficiency in Python and SQL

• Experience building production systems 
• Comfortable with ambiguous requirements and making foundational technology decisions
• Track record of wearing multiple hats and adapting to changing business needs
• Experience working directly with business stakeholders to understand requirements

• Experience with parallel, big data processing
• Knowledge of Snowflake and data pipeline development
• Experience with quantitative trading or algorithmic trading systems

• Opportunity to build ML infrastructure from the ground up
• Direct impact on company success and trading performance
• Mentorship and collaboration with experienced trading professionals
• Clear growth path as the company scales

• Small, collaborative team where your code directly impacts business outcomes
• Fully remote company with flexible working arrangements
• Modern development practices with freedom to choose appropriate tools and frameworks
• Fast-paced environment with rapid feedback from actual trading operations

• Deep dive into energy markets and financial trading concepts
• Exposure to quantitative finance and algorithmic trading strategies
• Experience building mission-critical applications with real financial impact
• Opportunity to work with cutting-edge ML and data science applications