Description:

The Machine Learning Engineer (The Model Innovator) will develop, deploy, and optimize machine learning models that transform data for decision-making.
This role involves working alongside data scientists, software engineers, and product managers to build machine learning solutions for intelligent applications and services.
Key responsibilities include designing and developing machine learning models using algorithms such as regression, classification, clustering, and deep learning.
The engineer will experiment with different model architectures and optimize hyperparameters to improve model accuracy and efficiency.
Collaboration with data engineers and scientists is essential for preprocessing, cleaning, and transforming large datasets into suitable formats for machine learning.
The role requires implementing machine learning models in production environments, ensuring scalability, reliability, and efficiency.
Continuous monitoring of model performance in production is necessary to detect issues and retrain models as needed.
The engineer will work closely with cross-functional teams to integrate machine learning models into products and services, ensuring alignment with business objectives.
Staying current with AI and machine learning trends is crucial for exploring new algorithms, tools, and techniques.

Requirements:

Strong knowledge of machine learning algorithms, including supervised and unsupervised learning techniques, is required.
Proficiency in programming languages such as Python, R, or Scala, with experience in writing production-level code is necessary.
Hands-on experience with data preprocessing, feature selection, and engineering is essential for handling large datasets.
Experience deploying machine learning models into production using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker is required.
Excellent collaboration skills are needed to work closely with cross-functional teams and communicate technical concepts to non-technical stakeholders.
A Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field is required, with equivalent experience in machine learning engineering being highly valued.
3+ years of experience in machine learning engineering, with a proven track record of building and deploying models in production environments, is necessary.
Experience with cloud-based AI services (AWS SageMaker, Google AI Platform, Azure ML) is highly desirable.

Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
Competitive vacation, sick leave, and 20 paid holidays per year are included in the paid time off policy.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs support professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources, is available.
Life insurance and short-term/long-term disability coverage are part of the benefits package.
Confidential counseling and support services for personal and professional challenges are offered through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is provided through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged.
Employee recognition programs celebrate achievements and milestones.