AWS Sagemaker Consultant

at  Matrix Global

Data Scientist - AWS SageMaker
We are a forward-thinking company dedicated to leveraging cutting-edge technologies to drive innovation and efficiency. Our team is passionate about data science and machine learning, and we are looking for a talented Data Scientist to join us in our mission to harness the power of AWS SageMaker.
Job Description:

JOB DESCRIPTION:

As a Data Scientist & GenAI Developer specializing in AWS SageMaker, you will be crucial in developing, deploying, and optimizing machine learning models. You will collaborate with cross-functional teams to solve complex business problems and drive data-driven decision-making. Your expertise in AWS SageMaker will be instrumental in building scalable and efficient ML & GenAI models / solutions.

Key Responsibilities:

• Model Development: Design, develop, and deploy machine learning models using AWS SageMaker.
• Data Preparation: Collect, clean, and preprocess data to ensure high-quality inputs for model training.
• Model Training and Evaluation: Train, evaluate, and fine-tune models for optimal performance.
• Deployment: Implement and manage model deployment pipelines to ensure seamless integration with production systems.
• Monitoring and Maintenance: Monitor model performance and make necessary adjustments to maintain accuracy and efficiency.
• Collaboration: Work closely with data engineers, software developers, and business stakeholders to understand requirements and deliver impactful solutions.
• Documentation: Document processes, methodologies, and best practices to ensure knowledge sharing and reproducibility.

Qualifications:

• Education: Bachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or a related field.
• Experience: Proven experience in developing and deploying machine learning & GenAI models using AWS SageMaker.
• Technical Skills: Proficiency in Python, SQL, and ML & GenAI frameworks such as TensorFlow or PyTorch.
• AWS Expertise: Strong knowledge of AWS services, particularly SageMaker, S3, Lambda, and EC2.
• Analytical Skills: Excellent problem-solving skills and the ability to analyze complex data sets.
• Communication: Strong verbal and written communication skills to effectively convey technical concepts to non-technical stakeholders.
• Team Player: Ability to work collaboratively in a fast-paced, dynamic environment.

Preferred Qualifications:

• Certifications: AWS Certified Machine Learning – Specialty or similar certifications.
• Experience: Prior experience in a similar role within a tech-driven organization.
• Knowledge: Familiarity with big data technologies such as Hadoop or Spark.

Why Join Us:

• Innovative Environment: Work with cutting-edge technologies and a team of passionate professionals.
• Career Growth: Opportunities for professional development and career advancement.
• Impactful Work: Contribute to projects that drive significant business value and innovation.
• Collaborative Culture: A supportive and inclusive work environment that values diversity and teamwork.

Interested candidates are invited to submit their resumes and a cover letter detailing their relevant experience and why they are a great fit for this role.
Feel free to customize this template to better fit your specific needs and company culture! If you need any further adjustments or additional details, just let me know.
Matrix Global Services is a leading multinational corporation that provides innovative and comprehensive solutions in technology, consulting, and outsourcing. With a history of over 30 years, Matrix has established itself as a trusted partner for businesses across various industries, consistently delivering exceptional results.
We’re a network of firms in 10+ countries with over 13,000 people. At Matrix, we pride ourselves on our commitment to excellence and our ability to adapt to the ever-changing needs of our clients. Our team of highly skilled professionals is adept at understanding complex business challenges and tailoring solutions that drive sustainable growth and profitability.
Our wide range of services includes cutting-edge technology solution services, strategic consulting, digital transformation, cloud computing, cybersecurity, and managed services. Whether it’s developing customized software applications, streamlining business processes, implementing robust IT infrastructure, or managing complex projects, our expertise and industry knowledge enable us to deliver value-added solutions that meet each client’s unique requirements.
Come and join a winning team! You’ll be challenged, have fun, and be a part of a highly respected organization! Matrix offers a competitive base salary and a full benefit package. Benefits include medical, dental, 401K, STD, HSA, PTO, and more.
EQUAL OPPORTUNITY EMPLOYER: Matrix is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind. Matrix is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at Matrix are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, family or parental status, or any other status protected by the laws or regulations in our locations. Matrix will not tolerate discrimination or harassment based on any of these characteristics. Matrix encourages applicants of all ages

• Model Development: Design, develop, and deploy machine learning models using AWS SageMaker.
• Data Preparation: Collect, clean, and preprocess data to ensure high-quality inputs for model training.
• Model Training and Evaluation: Train, evaluate, and fine-tune models for optimal performance.
• Deployment: Implement and manage model deployment pipelines to ensure seamless integration with production systems.
• Monitoring and Maintenance: Monitor model performance and make necessary adjustments to maintain accuracy and efficiency.
• Collaboration: Work closely with data engineers, software developers, and business stakeholders to understand requirements and deliver impactful solutions.
• Documentation: Document processes, methodologies, and best practices to ensure knowledge sharing and reproducibility