Machine Learning Engineer

Redwood Advanced Solutions; Austin (TX); On-site; USD 110,000 - 153,000; Full time

Benefits offered by this job

Health insurance

Retirement match

Professional development

Job summary

Redwood Advanced Solutions is seeking a Machine Learning Engineer to join our team in Austin, TX. This full-time role offers a salary range of $110,000 to $153,147, with a comprehensive benefits package including health insurance and employer-matched retirement plans.

You will design, train, and deploy ML models to optimize energy production and consumption. You will preprocess data, evaluate model performance, and collaborate with data scientists and engineers to integrate models into existing

Qualifications

• Proven experience in machine learning.
• Each item ≤ 140 characters.
• Experience with model deployment and evaluation.

Responsibilities

• Develop and deploy machine learning models to optimize energy production and consumption.
• Collaborate with data scientists and engineers to improve technologies.
• Data preprocessing, model training, and performance evaluation.
• Stay up-to-date with advances in ML/AI and apply them to improve models.
• Work with software teams to deploy models, ensuring scalability and security.
• Collaborate on diverse renewable energy projects with cross-functional teams.

Skills

Machine learning

Data analysis

Deep learning

TensorFlow

PyTorch

scikit-learn

Pandas

NumPy

Matplotlib

Seaborn

AWS

Google Cloud

Problem solving

Team collaboration

Education

Bachelor's or Master's degree in CS/DS/Statistics

Tools

TensorFlow

PyTorch

scikit-learn

Pandas

NumPy

Matplotlib

Seaborn

Job description

Redwood Advanced Solutions is seeking a Machine Learning Engineer to join our team in Austin, TX. This full-time position offers a competitive salary range of $110,000 to $153,147. You will contribute to our cutting-edge projects in sustainable energy solutions.

In this role, you will develop and deploy machine learning models to optimize energy production and consumption. You will also collaborate with data scientists and engineers to improve our existing technologies. Your tasks will include data preprocessing, model training, and performance evaluation.

You will work in a collaborative environment with a dedicated team of professionals. Our office is located in Austin, TX, fostering a culture of innovation and sustainability. You will have the opportunity to work on diverse projects in the renewable energy sector.

The salary range for this position is $110,000 to $153,147, providing a competitive compensation package that reflects the responsibilities and value of the role. In addition to the base salary, the comprehensive benefits package includes health insurance, which covers a wide range of medical services, including doctor visits, hospital stays, and prescription medications. The retirement plans offer a generous employer match, encouraging employees to save for their future. Professional development opportunities are also available, allowing employees to enhance their skills and advance their careers. These benefits are designed to support your overall well-being and career growth, ensuring that you have the resources and support needed to succeed in your role.

• Develop and implement machine learning models to analyze and predict energy consumption patterns, enabling us to optimize our renewable energy solutions.
• Collaborate with cross-functional teams to integrate machine learning models into our existing systems, ensuring seamless functionality and performance.
• Conduct extensive data analysis to identify trends, patterns, and insights that can drive our decision-making processes and improve our energy solutions.
• Stay up-to-date with the latest advancements in machine learning and artificial intelligence, and apply this knowledge to enhance our existing models and develop new ones.
• Work closely with our software development team to deploy and maintain machine learning models, ensuring they are scalable, secure, and efficient.
• A Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• Proven experience in machine learning, with a strong understanding of algorithms, models, and frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with data analysis and visualization tools, such as Pandas, NumPy, Matplotlib, or Seaborn.
• Knowledge of cloud platforms, such as AWS or Google Cloud, is a plus.
• Excellent problem-solving skills and the ability to work independently and as part of a team.