Machine Learning Engineer
hace 6 meses
At Stellar Elements, we're good people against bad experiences.
Whether it's customer, employee, or brand experience—we focus on closing the gap between business needs and what people actually desire. This takes passionate problem-solvers, brilliant minds, and deep wells of empathy.
Our clients love working with us because we understand their challenges, understand their customers, and we do great work while making each step of the process inspiring and energizing. We are a global force of nearly 1,000 experience experts** **and a collection of curious minds** **with a vibrant array of talents and backgrounds—united in creating better experiences for all.
**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**:
- 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
- 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
**#LI-Hybrid**
If this sounds like you, let's talk
**We are an equal opportunity employer**
Stellar Elements and its subsidiaries complies with all applicable federal, state, and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable federal, state, or local laws.
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