Solar
Proficient with programming languages (Python, Matlab, R, or similar), relational databases (SQL Server), data analysis and visualization software’s (preferably JMP, Power BI, SAS).
Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.
At least 5 years in building ML pipelines and prior experience with MLOps.
Take ownership of data quality improvement in First Solar’s field test sites. Assist in data analysis and state-of-the-art instrumentation and test equipment development. Forecast/Model long-term energy performance of First Solar modules in production/field environments, perform model vs actual analysis on a periodic basis. Identify areas of improvement in the models. Validate model predictions with measured data from plant monitoring systems and field test results.
Essential Responsibilities:
Develop Artificial Intelligence/Machine Learning based algorithms such as energy prediction model, solar irradiance (GHI, POA) model, spectral correction model, device metastability model, and module degradation model to enable fast learning of product performance.
Take ownership of data quality improvement in First Solar’s field test sites. Assist in data analysis and state-of-the-art instrumentation and test equipment development. Forecast/Model long-term energy performance of First Solar modules in production/field environments, perform model vs actual analysis on a periodic basis. Identify areas of improvement in the models. Validate model predictions with measured data from plant monitoring systems and field test results.
Familiarity with renewables energy prediction modeling (preferably solar) and processing meteorological data and understanding of power engineering is preferred.
Collaborate with data scientists and analytics team to deploy models, monitor performance and orchestrate continuous integration of model artifacts.
Automate end-to end ETL and ML pipelines, deploy and maintain existing on-prem and Azure storage.
Collaborate with data scientists and analytics team to deploy models, monitor performance and orchestrate continuous integration of model artifacts.
20/40 vision in each eye, with or without correction, is required
At least 5 years in building ML pipelines and prior experience with MLOps.
Bachelor’s degree in computer science, Computer Engineering, Data Science, Electrical Engineering, Applied Statistics, or Physics required. Advanced degree is a plus.
Will lift, push or pull up to 27 pounds on an occasional basis
Excellent communication, organization and interpersonal skills, comfortable to interpret data and modeling efforts to a large audience on a regular basis and publish results in reputed PV conference and journals.
US Physical Requirements:
Job description subject to change at any time.
The Machine Learning (ML) Engineer is responsible for leading the development, deployment, validation, and continuous improvement of models that accurately characterize the performance of First Solar photovoltaic products and systems. He/she will achieve results through leadership of cross-functional teams to identify research needs, develop and execute analysis and test plans, and ensure quality of data collection, analysis and reporting.
Demonstrated results in developing and delivering customer-facing technical collateral.
Conduct data cleaning, preprocessing, and analysis of massive datasets to identify significant trends, ensuring that the data used for model training is of the highest quality.
Develop Artificial Intelligence/Machine Learning based algorithms such as energy prediction model, solar irradiance (GHI, POA) model, spectral correction model, device metastability model, and module degradation model to enable fast learning of product performance.
Excellent communication, organization and interpersonal skills, comfortable to interpret data and modeling efforts to a large audience on a regular basis and publish results in reputed PV conference and journals.
Required Skills/Competencies:
Demonstrated results in developing and delivering customer-facing technical collateral.
May stoop, kneel, or bend, on an occasional basis
Conduct data cleaning, preprocessing, and analysis of massive datasets to identify significant trends, ensuring that the data used for model training is of the highest quality.
Bachelor’s degree in computer science, Computer Engineering, Data Science, Electrical Engineering, Applied Statistics, or Physics required. Advanced degree is a plus.
Proficient with programming languages (Python, Matlab, R, or similar), relational databases (SQL Server), data analysis and visualization software’s (preferably JMP, Power BI, SAS).
Bachelor’s degree in computer science, Computer Engineering, Data Science, Electrical Engineering, Applied Statistics, or Physics required. Advanced degree is a plus.
Proficient with solar simulation software (PVSyst, PlantPredict, PV Sol, PV Design Pro or similar).
Reporting Relationships:
Have solid understanding of the machine learning model stack (regression, classification, neural networks, time series) and ML Frameworks and libraries (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels)
First Solar reserves the right to offer you a role most applicable to your experience and skillset.
Will climb stairs on an occasional basis
The Machine Learning (ML) Engineer is responsible for leading the development, deployment, validation, and continuous improvement of models that accurately characterize the performance of First Solar photovoltaic products and systems. He/she will achieve results through leadership of cross-functional teams to identify research needs, develop and execute analysis and test plans, and ensure quality of data collection, analysis and reporting.
Support methods for verifying the capacity of installed solar PV systems and required customer reported performance metrics. Use standard root cause analysis techniques to identify areas of improvement and provide recommendations to support customer complaints.
At least 5 years in building ML pipelines and prior experience with MLOps.
Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check band any other tests that may be required.
$123,000 – $170,000 Estimated Annual Salary
No travel is required
Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check band any other tests that may be required.
No travel is required
Strong self-direction, initiative, and ability to prioritize multiple tasks from various requestors, demonstrated ability to manage multi-faceted projects.
Travel:
Proficiency in managing and analyzing extensive sets of data, coupled with expertise in data scrubbing, ETL, feature extraction, and data visualization.
Support methods for verifying the capacity of installed solar PV systems and required customer reported performance metrics. Use standard root cause analysis techniques to identify areas of improvement and provide recommendations to support customer complaints.
At least 10 years in Data Science, Artificial Intelligence or Machine Learning algorithm development.
Required to use hands to grasp, lift, handle, carry or feel objects on a frequent basis
Demonstrated results in developing and delivering customer-facing technical collateral.
Evaluate the feasibility of new products, model energy performance of new module technologies under various meteorological climates, improve model through successive iterations, ensemble results to develop a robust model and validate model prediction with testbed before production deployment.
Job description subject to change at any time.
The ideal candidate will build relationships with internal and external groups to research state of the art meteorological analysis, statistical analysis, energy prediction methods & tools, and recommendations for PV power plant design in support of their work. He/she will identify outstanding bottlenecks in the data infrastructure, support and enhance existing systems and productionize AI environments for modeling and forecasting.
Location: Perrysburg, OH (On-site)
Must be able to comply with all safety standards and procedures
The ideal candidate will build relationships with internal and external groups to research state of the art meteorological analysis, statistical analysis, energy prediction methods & tools, and recommendations for PV power plant design in support of their work. He/she will identify outstanding bottlenecks in the data infrastructure, support and enhance existing systems and productionize AI environments for modeling and forecasting.
All associates working on the production floor may be required to wear a respirator at any given time and thus, the ability to wear a respirator is a condition of employment and continued employment (requires little or no facial hair)
The successful candidate will be a subject matter expert in the Machine Learning space, who is able to adapt quickly to new data and analytical requests from across the First Solar organization. This may include engineering statistical analysis, contract analysis, policy analysis and project management tasks. The Machine Learning Engineer will also be responsible for orchestrating continuous integration of model artifacts to assist data scientists in generating detailed energy predictions for prospective and operating sites.
Document code, models, approaches, and experiments to ensure clarity and promote knowledge sharing among team members.
Develop Artificial Intelligence/Machine Learning based algorithms such as energy prediction model, solar irradiance (GHI, POA) model, spectral correction model, device metastability model, and module degradation model to enable fast learning of product performance.
The successful candidate will be a subject matter expert in the Machine Learning space, who is able to adapt quickly to new data and analytical requests from across the First Solar organization. This may include engineering statistical analysis, contract analysis, policy analysis and project management tasks. The Machine Learning Engineer will also be responsible for orchestrating continuous integration of model artifacts to assist data scientists in generating detailed energy predictions for prospective and operating sites.
Basic Job Functions:
Will sit, stand or walk short distances for up to the entire duration of a shift
About the job
Automate end-to end ETL and ML pipelines, deploy and maintain existing on-prem and Azure storage.
Document code, models, approaches, and experiments to ensure clarity and promote knowledge sharing among team members.
Proficient with solar simulation software (PVSyst, PlantPredict, PV Sol, PV Design Pro or similar).
$123,000 – $170,000 Estimated Annual Salary
Proficiency in managing and analyzing extensive sets of data, coupled with expertise in data scrubbing, ETL, feature extraction, and data visualization.
Have solid understanding of the machine learning model stack (regression, classification, neural networks, time series) and ML Frameworks and libraries (Scikit learn, Xgboost, Keras, Pytorch, Tensorflow, statsmodels)
Education/Experience:
Estimated Annual Salary Range:
Strong self-direction, initiative, and ability to prioritize multiple tasks from various requestors, demonstrated ability to manage multi-faceted projects.
Job Description
The Machine Learning (ML) Engineer is responsible for leading the development, deployment, validation, and continuous improvement of models that accurately characterize the performance of First Solar photovoltaic products and systems. He/she will achieve results through leadership of cross-functional teams to identify research needs, develop and execute analysis and test plans, and ensure quality of data collection, analysis and reporting.
Ability to wear personal protective equipment is required (including but not limited to; steel toed shoes, gloves, safety glasses, hearing protection, protective jacket or apron and arm guards)
May reach above shoulder heights and below the waist on a frequent basis
Reports toHead of Performance and Prediction Analytics
Proficient with programming languages (Python, Matlab, R, or similar), relational databases (SQL Server), data analysis and visualization software’s (preferably JMP, Power BI, SAS).
Evaluate the feasibility of new products, model energy performance of new module technologies under various meteorological climates, improve model through successive iterations, ensemble results to develop a robust model and validate model prediction with testbed before production deployment.
The ideal candidate will build relationships with internal and external groups to research state of the art meteorological analysis, statistical analysis, energy prediction methods & tools, and recommendations for PV power plant design in support of their work. He/she will identify outstanding bottlenecks in the data infrastructure, support and enhance existing systems and productionize AI environments for modeling and forecasting.
Job description subject to change at any time.
Familiarity with renewables energy prediction modeling (preferably solar) and processing meteorological data and understanding of power engineering is preferred.
At least 10 years in Data Science, Artificial Intelligence or Machine Learning algorithm development.
Solar
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