Sr. Machine Learning Engineer

Job Summary

We are seeking a highly skilled Senior Machine Learning Engineer to join our innovative team. This role is crucial in driving AI/ML adoption and integration within our organization. The ideal candidate will have a strong background in machine learning, software engineering, and data science, with a passion for solving complex problems and building scalable systems. 

 

You will work in the development, deployment, and optimization of machine learning models, working closely with machine learning engineers, data engineers, software development engineers, and stakeholders. Your expertise in advanced analytics and AI/ML practices will enhance customer experience and business operations. Additionally, you will collaborate with business partners to explore innovation opportunities and shape cutting-edge applications.This role demands in-depth knowledge of AI/ML, business strategy, and change management, along with the ability to thrive in a multidisciplinary environment.

 

This position is required to report to the SHI Austin, TX or Somerset, NJ office location as determined by SHI management.

About Us

Since 1989, SHI International Corp. has helped organizations change the world through technology. We’ve grown every year since, and today we’re proud to be a $14 billion global provider of IT solutions and services.

 

Over 17,000 organizations worldwide rely on SHI’s concierge approach to help them solve what’s next. But the heartbeat of SHI is our employees – all 6,000 of them. If you join our team, you’ll enjoy:

• Our commitment to diversity, as the largest minority- and woman-owned enterprise in the U.S.
• Continuous professional growth and leadership opportunities.
• Health, wellness, and financial benefits to offer peace of mind to you and your family.
• World-class facilities and the technology you need to thrive – in our offices or yours. 

Responsibilities

Include but not limited to: 

• Lead initiatives to develop and execute a governance model for AI/ML and other analytics
• Design, develop, and implement ML solutions; ensure familiarity with SageMaker, AWS Glue, Copilot, Chat GPT, and Open AI, and/or Microsoft AI technologies
• Measure and communicate AI/ML impact on the business and drive continuous improvement
• Analyze data and translate recommendations into actionable items for end users
• Assess and monitor performance, ensuring systems remain compliant with standards and secure against cybersecurity threats
• Lead complex, data-driven research projects impacting SHI’s business
• Explore and execute analytical solutions for various problems
• Acquire, analyze, and act on complex data sets; create ETL jobs; explore, inspect, and clean data; engineer features
• Train, validate, test, deploy, and maintain machine learning models in production environments
• Organize and lead meetings with stakeholders; collaborate with internal groups to achieve project goal
• Stay updated on data science, statistics, machine learning, and AI developments
• Ensure ML models are scalable, reliable, and efficient; integrate models with systems and platforms; optimize model performance
• Document design specifications, processes, models, and systems for transparency and reproducibility

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Systems, Engineering, Mathematics, or a related field
• Minimum of 5 years of experience in machine learning, with exposure to software engineering best practices
• 2 years of direct experience using technologies like SageMaker, AWS Glue, Copilot, Chat GPT, or Open AI, and/or Microsoft AI technologies
• Demonstrated experience in developing and deploying machine learning models in production environments
• Deep understanding of machine learning algorithms, data structures, and software design principles

Required Skills

• Proficiency in programming languages such as Python, Java, or C++
• Extensive experience with machine learning frameworks and libraries like TensorFlow, PyTorch, and Scikit-learn
• Solid understanding of software engineering principles, including version control (Git), testing, and CI/CD pipelines
• Strong skills in data preprocessing, feature engineering, and data analysis using tools like Pandas and NumPy
• Proficiency with platforms such as SageMaker, AWS Glue, Copilot, Chat GPT, and Open AI, and/or Microsoft AI technologies
• Ability to learn and work with new ML models, and Large Language Models (LLMs)
• Experience with cloud platforms such as AWS, GCP, or Azure for deploying and managing machine learning models
• Expertise in