Machine Learning Engineer

Company Overview:

At Stellar Elements, we solve our clients’ business challenges by creating experiences that engage, innovate, disrupt, and delight. Our team is passionate about human-centric experience strategy, design and development and enjoys delivering amazing concepts and digital solutions for our clients. We have fun and enjoy hanging out with each other in a culture that supports and celebrates our diverse talents, backgrounds, and skills.

Position Overview:

We are seeking a talented and experienced Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will be responsible for developing, deploying, and maintaining machine learning models using Python and AWS SageMaker. You will collaborate with cross-functional teams to design and implement scalable and efficient machine learning solutions to address complex business problems.

Responsibilities:

• Develop machine learning models for various applications, including but not limited to natural language processing, computer vision, and recommendation systems
• Preprocess and analyze large datasets to extract meaningful insights and features for model training
• Design and implement machine learning pipelines using Python libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras
• Utilize AWS SageMaker for model development, training, deployment, and monitoring
• Optimize machine learning models for performance, scalability, and cost-effectiveness on AWS infrastructure
• Collaborate with software engineers to integrate machine learning models into production systems and applications
• Stay updated on the latest advancements and best practices in machine learning, cloud computing, and AWS services
• Mentor junior team members and contribute to a culture of continuous learning and innovation

Requirements:

• Bachelor's or master's degree in Computer Science, Engineering, Mathematics, Statistics, or related field
• 3+ Years of experience working as a Machine Learning Engineer or Data Scientist
• Proficiency in Python programming language and experience with relevant libraries and frameworks for machine learning
• Hands-on experience with AWS services, particularly AWS SageMaker, EC2, S3, IAM, and CloudWatch
• Strong understanding of machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning
• Experience with data preprocessing, feature engineering, model evaluation, and hyperparameter tuning
• Solid knowledge of OOP programing end experience
• Excellent problem-solving skills and ability to translate business requirements into machine learning solutions
• Effective communication skills and ability to collaborate with cross-functional teams
• Strong attention to detail and commitment to delivering high-quality work
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes
• Strong communication and collaboration skills, with the ability to work effectively across cross-functional teams

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