Machine Learning Engineer / Data Scientist

Role: Machine Learning Engineer / Data Scientist AI/ML
Location: Alpharetta, GA(In-Person interview must)- Need locals with DL
Job Type: CTH

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, Google Cloud Platform) 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.