Machine Learning Engineer

As a Machine Learning Engineer at Smart Data Solutions (SDS), you will play a pivotal role in our mission to leverage data and intelligent automation to transform healthcare operations. You will be responsible for building, deploying, maintaining, troubleshooting, and improving machine learning models, as well as designing and implementing new applications that leverage machine learning technology. Additionally, you will work on developing and enhancing machine learning infrastructure, analyzing and automating existing processes using machine learning, and investigating and remedying issues with machine learning processes.

Key Responsibilities:

• Build, deploy, maintain, troubleshoot, and enhance machine learning models.
• Design and implement new applications that leverage machine learning and related technology.
• Develop and improve machine learning infrastructure.
• Analyze and automate existing processes using machine learning.
• Investigate and remediate issues with machine learning processes.

Qualifications and Required Skills:

• Bachelor’s degree in computer science or an equivalent degree.
• 1+ year of experience working with machine learning, natural language processing (NLP), or deep learning concepts.
• Proficiency in at least one modern high-level programming language (Python, Java, C#, C++, etc.).
• Knowledge of common machine learning, NLP, computer vision, and data science libraries.
• Basic knowledge of relational databases (MySQL).
• Basic knowledge of Unix-like operating systems.
• Experience with Git/Version Control.
• Highly organized and disciplined.
• Strong business analysis skills.
• Proficiency in Microsoft Excel, Word, and Windows.
• Ability to understand processes, analyze them, and identify opportunities for improvement.
• Strong writing skills, particularly for process documentation and communication.
• Ability to comprehend and follow written policies, procedures, and directions.
• Disciplined in prompt communication responsiveness.
• Effective communication and reporting style that emphasizes simplicity and elimination of noise in favor of substantive and actionable data.
• Action-oriented with the ability to consistently complete assigned tasks on time.

Preferred Skills (Not Mandatory but a Plus):

• Advanced degree in computer science, machine learning, or related field.
• Experience with healthcare data and regulations.
• Experience with cloud-based machine learning platforms (e.g., AWS SageMaker, Google AI Platform).
• Knowledge of big data technologies (e.g., Hadoop, Spark).
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).