• 상세 내용은 첨부된 JD 참조

[채용일정]

m  서류접수: ~1/31(금)

m  서류합격: ~2/14(금)  *합격자 개별연락

m  1차면접(실무면접): ~2/28(금),  *스케줄 별도 협의

m  1차합격: ~3/10(월)  *합격자 개별연락

m  2차면접(임원면접): ~3/21(금),  *스케줄 별도 협의

m  최종발표: ~3/31(월)

 

* 세부일정은 상황에 따라 조정 가능하며, 필요시 추가 면접 진행이 있을 수 있습니다.

** 합격자는 4월말~5월초까지 휴스턴 이동 및 업무가능한 자를 선호합니다. 다만, 개별상황에 따른 일정협의 가능합니다.

 

채용관련 문의: thomaskim@sk.com (GridFlex 전력트레이딩그룹 김태욱 PL)

Job Title:
Junior Machine Learning Engineer - Power Trading Algorithm Development

Location: Houston, US (On-Site)

About the Role
We are seeking a motivated Junior Machine Learning Engineer to join our trading team and develop
data-driven predictive models for power trading in the North American electricity market, focusing on
ERCOT (Electric Reliability Council of Texas). In this role, you will design advanced machine learning
models, support trading strategies, and manage outsourced software projects to ensure quality and
timely delivery. This role will provide opportunities to expand expertise as we aim to grow into
additional markets like MISO and SPP

Key Responsibilities
• Develop and Deploy Machine Learning Models: Assist in the creation and deployment of
machine learning models to support predictive analytics and data-driven decision-making,
focusing on scalable algorithm design and implementation.
• Trend Analysis and Anomaly Detection: Build and refine advanced models for trend analysis
and anomaly detection, ensuring optimal performance, scalability, and operational efficiency.
• Data Pipeline and Architecture Design: Design and implement robust data pipelines,
leveraging machine learning models for predictive insights, power trading strategies, and
innovative solutions within a unified software architecture.
• Vendor Management and Quality Assurance: Coordinate with external software vendors to
manage development projects, ensuring quality through effective validation and alignment with
organizational goals.

Qualifications
Required Skills and Experience:
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and programming
languages (e.g., Python, R).

• Hands-on experience with data engineering tools (e.g., SQL, Pandas, Spark) and cloud platforms
(e.g., AWS, Azure, GCP).
• Strong expertise in predictive analytics, including trend analysis and anomaly detection.
• Proven ability to manage large datasets and develop scalable, efficient data pipelines and
operational systems.
• Solid understanding of machine learning algorithms, statistical methods, and their practical
applications.
• Strong analytical and problem-solving skills with a results-oriented mindset.

Minimum Requirements
• Bachelor’s degree in Electrical Engineering, Computer Science, Economics, or related fields.

Preferred Requirements
• Master’s degree in Analytics, Applied Mathematics, or Statistics is a strong plus.
• Familiarity with energy markets, particularly ERCOT, and experience in energy price forecasting.
• Knowledge of statistical and mathematical modeling techniques applied to energy systems.

Benefits and Perks
• Competitive Compensation: Salary and performance-based bonus (To be determined)
• Health Insurance: Comprehensive medical, dental, and vision coverage
• Paid Time Off : 16 days of paid vacation, and 10+ paid holidays annually
• Relocation Assistance: Financial support for moving expenses
• STEM OPT Support: Assistance with employment verification and training plans (Form I-983)

Why Join Us?
GridFlex Inc. is a U.S.-based energy company established by SK Gas, a leading South Korean energy
corporation, to drive its battery energy storage system (BESS) business in North America. Currently
focused on the Texas market (ERCOT), but GridFlex aims to expand its operations into other key
markets, including SPP and MISO, as part of its growth strategy. Joining GridFlex means being part of a
forward-thinking team shaping the future of energy innovation.

How to Apply
Please submit your resume and a cover letter detailing your relevant experience and interest in the
role. Applications without a cover letter will not be considered.
(Email: gridflex_trading@sk.com / thomaskim@sk.com)