Machine Learning Engineer / Data Scientist

Machine Learning Engineer / Data Scientist – AI/ML Innovation and Governance Alpharetta, GA (5 days onsite)

Duration: Long term Contract / CTH

Target Start Date: ASAP


Job Description:

We are seeking a highly skilled and motivated Machine Learning Engineer/Data Scientist with expertise in data science, machine learning, and AI/ML model optimization. The ideal candidate will have a strong foundation in improving model efficiencies, a passion for innovation in MLOps (Machine Learning Operations), and a deep understanding of AI/ML governance frameworks.



This role requires someone who is not only technically proficient but also eager to learn new skills, embrace challenges, and thrive in a fast-paced, collaborative environment. You will be part of a global team, working on projects that push the boundaries of AI/ML capabilities while ensuring robust governance and ethical practices.



Key Responsibilities:.

• Design, develop, and optimize machine learning models to improve efficiency, scalability, and performance.

• Implement innovative MLOps practices to streamline model deployment, monitoring, and maintenance.

• Collaborate with cross-functional teams to integrate AI/ML solutions into business processes.

• Develop and enforce governance frameworks for AI/ML systems, ensuring compliance with ethical and regulatory standards.

• Stay updated on the latest advancements in AI/ML technologies and incorporate them into existing workflows.

• Conduct research and experimentation to identify new approaches for improving model performance and efficiency.

• Document and communicate technical concepts and solutions to both technical and non-technical stakeholders.

• Mentor and guide junior team members, fostering a culture of continuous learning and innovation.



Required Skills and Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

• Proven experience in data science, machine learning, and AI model development.

• Strong knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, TensorFlow Extended).

• Proficiency in programming languages such as Python, R, or Java.

• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

• Familiarity with AI/ML governance frameworks and ethical AI practices.

• Excellent problem-solving skills and the ability to handle complex, ambiguous challenges.

• Strong communication and collaboration skills, with the ability to work in a global team environment.



Desired Attributes:

• A growth mindset with a willingness to learn new skills and adapt to evolving technologies.

• Ability to handle steep learning curves and thrive in dynamic, fast-paced environments.

• Passion for innovation and a proactive approach to identifying and solving problems.

• Experience working in a global or distributed team is a plus.