Description:

The Machine Learning Engineer (The Model Innovator) will develop, deploy, and optimize machine learning models that transform data into intelligent systems for decision-making.
This role involves working alongside data scientists, software engineers, and product managers to create scalable algorithms and refine model performance.
Key responsibilities include designing and developing machine learning models using various algorithms, training models, and optimizing hyperparameters for accuracy and efficiency.
The engineer will collaborate with data engineers to preprocess and transform large datasets, perform feature engineering, and deploy models into production environments.
Continuous monitoring of model performance is essential, with responsibilities for detecting issues and retraining models as necessary.
The position requires collaboration with cross-functional teams to integrate machine learning models into products and services, ensuring they meet business objectives.
Staying current with AI and machine learning trends is crucial for exploring new algorithms and improving solutions.

Requirements:

Strong knowledge of machine learning algorithms, including supervised and unsupervised learning techniques, with experience using tools like TensorFlow, PyTorch, Scikit-learn, and Keras.
Proficiency in programming languages such as Python, R, or Scala, with experience in writing production-level code for machine learning solutions.
Hands-on experience with data preprocessing, feature selection, and engineering, with an understanding of handling large datasets for machine learning workflows.
Experience deploying machine learning models into production using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker.
Excellent collaboration skills 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, with equivalent experience in machine learning engineering being highly valued.
At least 3 years of experience in machine learning engineering, with a proven track record of building and deploying models in production environments.
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.
Competitive vacation, sick leave, and 20 paid holidays per year.
Flexible work schedules and telecommuting options to promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs.
Access to wellness programs, including gym memberships, health screenings, and mental health resources.
Life insurance and short-term/long-term disability coverage.
Confidential counseling and support services through an Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development through tuition reimbursement.
Opportunities to participate in community service and volunteer activities.
Employee recognition programs to celebrate achievements and milestones.