Machine Learning (AI) Engineer (Hybrid)

Role : Machine Learning (AI) Engineer (Hybrid)

• Location : Remote
• Job Type : Full-Time
• Payout : $200K - $500K/yr

Role Overview: We are hiring for one of our clients, seeking an AI/ML Engineer to develop and deploy machine learning models that power core product features. The role involves collaborating with cross-functional teams to design scalable AI solutions that enhance user experience and operational efficiency.

Key Responsibilities: • Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch frameworks. • Develop and maintain data pipelines to ensure high-quality input for model training and evaluation. • Implement MLOps practices to streamline model deployment, monitoring, and version control. • Collaborate with data scientists and software engineers to integrate AI capabilities into production systems. • Conduct performance benchmarking and A/B testing to validate model accuracy and business impact.

Required Skills & Qualifications: • Proficiency in Python, TensorFlow, and PyTorch for model development and training. • Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for deployment and monitoring. • Strong background in data preprocessing, feature engineering, and model evaluation metrics. • Familiarity with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure. • Knowledge of software engineering best practices, including version control (Git) and CI/CD pipelines.

More About the Opportunity: This role offers a unique opportunity to work with a global leader in the Software Development industry, contributing to the advancement of AI-driven product solutions. The position involves solving complex technical challenges in a collaborative environment with access to cutting-edge tools and datasets.

Equal Opportunity Employer: We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.

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