Machine Learning Engineer

Sterling Summit Inc.; Seattle (WA); On-site; USD 95,000 - 137,000; Full time

Benefits offered by this job

Health insurance

Retirement plan with employer match

Professional development opportunities

Job summary

Sterling Summit Inc. in Seattle, WA invites a Machine Learning Engineer to design, deploy, and optimize ML solutions that drive business growth. You will develop models, preprocess data, and collaborate with data scientists and product teams to translate requirements into scalable implementations.

Experience with Python, TensorFlow, PyTorch, and scikit-learn is required. This full-time role offers a salary range of $95,000–$136,749 per year, plus benefits including health insurance, retirement

Qualifications

• Master's degree in Computer Science, ML or related field.
• 3+ years of experience in machine learning engineering.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn.
• Experience with cloud platforms (AWS, Google Cloud, Azure).
• Knowledge of data pipelines and databases.

Responsibilities

• Develop and deploy machine learning models to solve business problems.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Perform data analysis and feature engineering to improve model performance.
• Monitor and maintain ML systems for optimal performance.
• Stay up-to-date with ML advances and document learnings for the team.
• 2

Skills

Python

data analysis

Education

Master's degree in Computer Science / ML

Bachelor's degree in CS/Math/Statistics

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Sterling Summit Inc. is hiring a Machine Learning Engineer in Seattle, WA. This full-time role involves creating and deploying machine learning solutions to boost business growth and innovation.

As a Machine Learning Engineer, you will be responsible for designing and implementing machine learning models, which may involve tasks such as data preprocessing, feature engineering, and model selection. You will also optimize algorithms to improve performance and efficiency, which could include techniques like hyperparameter tuning, model pruning, or using more efficient data structures. Additionally, you will collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to integrate machine learning into products. This may involve understanding business requirements, translating them into technical specifications, and ensuring that the machine learning models meet the desired performance metrics. Furthermore, you may be involved in deploying and monitoring machine learning models in production environments, which could include tasks like setting up CI/CD pipelines, logging model performance, and implementing feedback loops to continuously improve the models.

You will work in a collaborative environment with the Sterling Summit Inc. team in Seattle, WA. The company is known for its innovative approach to technology and data analytics.

The annual salary range for this position is between $95,000 and $136,749, providing a competitive compensation package.

• In addition to the base salary, employees are eligible for comprehensive health insurance coverage, which includes medical, dental, and vision plans.
• The company also offers a retirement plan with a generous employer match, allowing employees to save for their future.
• Furthermore, professional development opportunities are available, such as tuition reimbursement, workshops, and access to online learning platforms, ensuring employees can enhance their skills and advance their careers.

To be successful, you should have a Master's degree in Computer Science, Machine Learning, or a related field. Experience with Python, TensorFlow, and scikit-learn is required.

What you will do:

1. Develop and deploy machine learning models to solve business problems.
2. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
3. Conduct data analysis and feature engineering to improve model performance.
4. Monitor and maintain machine learning systems to ensure optimal performance.
5. Stay up-to-date with the latest advancements in machine learning and data science.
6. Document and share knowledge to support team learning and growth.

What we need:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
2. 3+ years of experience in machine learning engineering.
3. Strong programming skills in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and scikit-learn.
4. Experience with cloud platforms like AWS, Google Cloud, or Azure.
5. Knowledge of data pipelines and database systems.
6. Excellent problem-solving and analytical skills.