Machine Learning Expert
hace 7 días
We are looking for an experienced and highly skilled professional to lead our machine learning efforts. The ideal candidate will have a robust background in machine learning, with a particular focus on AWS SageMaker, AWS Bedrock, and generative AI solutions.
Key Responsibilities:
- Lead the design, development, and deployment of machine learning models and algorithms to solve complex business problems.
- Oversee the end-to-end machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
- Utilize AWS SageMaker to build, train, and deploy machine learning models.
- Leverage AWS Bedrock to develop robust and scalable generative AI solutions for various applications.
- Develop and implement generative AI solutions to enhance business processes and customer experiences.
- Implement MLOps practices, including model monitoring, and automation of the training and deployment pipeline.
- Collaborate with cross-functional teams to integrate ML models into production environments and applications.
- Provide technical leadership and mentorship to a team of data scientists and machine learning engineers.
- Communicate complex machine learning concepts and insights to non-technical stakeholders.
- Ensure the integrity and quality of data throughout the machine learning pipeline.
- Stay current with the latest advancements in machine learning, AI, and AWS technologies to continuously improve capabilities.
Requirements:
- Minimum of 7 years of hands-on experience in machine learning and data science roles, with significant experience in leading and managing ML projects.
- Proven track record of successfully delivering end-to-end machine learning solutions from concept to production deployment.
- Extensive expertise in AWS services such as SageMaker, AWS Bedrock, and other AI/ML tools.
- Strong proficiency in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn.
- Experience with MLOps practices, including model monitoring, deployment automation, and CI/CD pipelines.
- Demonstrated ability to design and implement scalable and efficient machine learning architectures in cloud environments.
- Deep understanding of data engineering, feature engineering, and data preprocessing techniques.
- Experience with AutoML, hyperparameter tuning, and model optimization techniques.
- Leadership skills with the ability to lead and mentor a team of data scientists and machine learning engineers effectively.
Skills:
Aws Sagemaker, Aws Bedrock, PyTorch, TensorFlow, scikit-learn, statsmodels, pandas, numpy, prophet, darts, optuna, hyperopt, MLOps, AutoML, SQL.
Personal Traits:
- Strong portfolio and excellent attitude.
- Ability to work with teams across organizational boundaries, different cultures, and different time zones in a virtual environment.
- Delivery oriented and able to work under strict deadlines.
- Must be self-confident to work in a Team and to handle the responsibilities individually as well.
- Should be a good listener, can articulate well, and possess good communication skills.
What's in it for you:
- $4000 USD monthly salary.
- Full-time remote work flexibility.
- Opportunity for professional growth.
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