Description:

The Machine Learning Engineer (The Model Innovator) will develop, deploy, and optimize machine learning models that enhance data-driven decision-making.
This role involves collaborating with data scientists, software engineers, and product managers to create machine learning solutions for intelligent applications and services.
Key responsibilities include designing and developing machine learning models using various algorithms, training models, and tuning hyperparameters for improved accuracy.
The engineer will preprocess and transform large datasets, perform feature engineering, and deploy models into production environments.
Continuous monitoring and improvement of model performance is essential, including addressing issues like model drift.
The position requires collaboration with cross-functional teams to ensure AI solutions meet business objectives and provide measurable value.
Staying current with AI and machine learning trends is crucial for exploring new algorithms 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 in 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 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.
A minimum of 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 benefits package.
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.
Confidential counseling and support services are offered through an 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 within the organization.