Renewables Software Engineering Leader - Dallas, United States - ThinkBAC Consulting

Description

Energy Storage Software Engineering Leader (Manager to Sr. Manager level) - Energy Trading
Location: FULLY REMOTE (Anywhere in the USA)
This is an opportunity to join an industry leading renewable energy venture with strong private equity backing that is focused on the development, execution, and operations of dynamic utility-scale energy storage projects. They are at the forefront of the industry, have accumulated over 9GW of projects in a relatively short period of time, and are currently in an accelerated expansion phase which includes key additions to their Software, Data, and Technology Team.
The Energy Storage Software Engineering Leader is an innovative team leadership role focused on ML / AI energy predictive pricing and quantitative forecasting models that will drive the algorithmic decision making process of next generation utility-scale renewable energy projects across all ISO / RTO markets in the United States. It will be part of a creative team focused on energy storage / battery storage energy trading strategies, asset management, and real-time energy pricing.

They are committed to creating more renewable infrastructure solutions for the grid and are offering comprehensive compensation packages to their employees leading the drive to meet company goals. Other perks included a competitive base salary, open PTO policy, flex work hours, benefits, the opportunity to work with a transparent Executive Leadership more.

RESPONSIBILITIES:

• Renewables Software Engineering Leader (Manager - Sr. Manager) - Develops and implements software development growth strategy driven by machine learning optimization and predictive models for energy trading wholesale electricity markets with a key focus on energy storage initiatives
  
• Renewables Software Engineering Leader (Manager - Sr. Manager) - Takes ownership of Software Engineering operations programs to monitor performance and streamline processes including real-time troubleshooting
  
• Renewables Software Engineering Leader (Manager - Sr. Manager) - Create short-term and long-term roadmaps based on organizational goals as well as team based assessments
  
• Renewables Software Engineering Leader (Manager - Sr. Manager) - Develops and implements a framework of testings machine learning models and taking them into production
  
• Renewables Software Engineering Leader (Manager - Sr. Manager) - Utilize forward thinking techniques such as optimal control, deep learning, machine learning (AI/ML), and reinforcement learning to evaluate and update current protocols
  

QUALIFICATIONS:

• 8-10+ yrs of software development engineering, programming, or coding experience; at least 2 years in Team Leadership roles with direct reports
  
• Software engineering machine learning development experience in production ready coding environments focused on complex projects
  
• Solid exposure to cybersecurity best practices for software development and distributed architecture systems
  
• Expert in machine learning model deployment and machine learning operations MLOps; Well versed in agile based software development methodology
  
• Expertise in the Amazon Web Services (AWS) Sagemaker Machine Learning platform or similar cloud based solutions
  
• Understanding convex optimization techniques (Linear/Mixed Integer programming) and time-series forecasting (PostgreSQL, TimescaleDB, InfluxDB)
  
• Understanding Python-based optimization toolkits such as Pyomo, CVXPY GurobiPy, etc.
  
• Understanding of machine learning concepts such as classification, deep learning, deep neural networks (DNN), reinforcement learning, and regression problem solving techniques
  
• HUGE PLUS - experience working in production ready coding environments in the energy trading or financial trading sector
  
• HUGE PLUS - solid understanding of national energy markets and renewable energy portfolios - PJM, ERCOT, SPP, MISO, NYISO, ISO-NE, and CAISO; capacity prices, regional energy pricing, congestion and curtailment analysis, transmission constraints, interconnection assessments, LMPs (locational marginal pricing), and/or regional supply and demand curves)
  
• Ideal candidates for this role will have experience working in Senior, Lead, Principal, Manager, and Director level roles as Software Engineering Manager, Principal Software Architect, ML/AI Engineering Leader, AI Software Engineering Leader, ML Software Development Leader, ML/AI Engineering