Machine Learning Engineer

Summary

We are seeking an innovative and passionate Machine Learning Engineer to join our fast-paced team at Oppizi. The role involves developing, deploying, and optimizing end-to-end machine learning models using MLOps, collaborating with cross-functional teams, and ensuring scalability and efficiency of the models.

Requirements

• Education: Bachelor's or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field
• Experience: Minimum of 4 years of experience as a Machine Learning Engineer or in a similar role
• MLOps Expertise: Proven experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow Extended)
• Programming Skills: Strong proficiency in Python and experience with libraries such as Pandas, NumPy, and Scikit-learn
• Cloud & Containerization: Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud, and familiarity with containerization technologies like Docker and Kubernetes
• Data & API Proficiency: Experience with data manipulation and building APIs using frameworks such as FastAPI, Flask, or Django
• Communication Skills: Ability to explain complex technical concepts to both technical and non-technical stakeholders

Responsibilities

• Model Development and Deployment: Design, implement, and deploy machine learning models that address business needs, ensuring high availability and performance in production environments
• MLOps and Automation: Apply MLOps best practices to automate the ML lifecycle, including data ingestion, training, and deployment pipelines. Build and maintain CI/CD pipelines for continuous integration and delivery
• Performance Monitoring and Optimization: Monitor deployed models to ensure they meet performance metrics, and continuously improve them for accuracy and scalability
• Collaboration and Communication: Work closely with software engineers, product managers, and other stakeholders to develop and communicate ML solutions effectively

Preferred Qualifications

• Experience with big data technologies (e.g., Hadoop, Spark)
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch)
• Knowledge of DevOps practices and tools

Benefits

• Competitive salary (open to negotiation) with performance-based bonuses
• Professional growth opportunities in a fast-growing startup
• Flexible working hours and remote work options