Oppizi

We are looking for an innovative and passionate Machine Learning Engineer to join our fast-paced, dynamic team. As a key member of our technology division, you will play a vital role in developing, deploying, and optimizing end-to-end machine learning models. This role demands expertise in MLOps (Machine Learning Operations) and the ability to handle the entire machine learning lifecycle—from data ingestion to model deployment and beyond.As a Machine Learning Engineer at Oppizi, you will have the opportunity to collaborate with cross-functional teams, including software engineers and product managers, to deliver high-quality ML solutions that directly impact business outcomes. You will also be responsible for ensuring that our models are scalable, efficient, and aligned with the company’s goals.<h3>Key Responsibilities:</h3><ul> <li> Model Development and Deployment: Design, implement, and deploy machine learning models that address business needs, ensuring high availability and performance in production environments.</li> <li> 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.</li> <li> Performance Monitoring and Optimization: Monitor deployed models to ensure they meet performance metrics, and continuously improve them for accuracy and scalability.</li> <li> Collaboration and Communication: Work closely with software engineers, product managers, and other stakeholders to develop and communicate ML solutions effectively.</li> </ul>Requirements<h3>What are you bringing to the team:</h3><ul> <li> Education: Bachelor's or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.</li> <li> Experience: Minimum of 4 years of experience as a Machine Learning Engineer or in a similar role.</li> <li> MLOps Expertise: Proven experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow Extended).</li> <li> Programming Skills: Strong proficiency in Python and experience with libraries such as Pandas, NumPy, and Scikit-learn.</li> <li> Cloud &amp; Containerization: Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud, and familiarity with containerization technologies like Docker and Kubernetes.</li> <li> Data &amp; API Proficiency: Experience with data manipulation and building APIs using frameworks such as FastAPI, Flask, or Django.</li> <li> Communication Skills: Ability to explain complex technical concepts to both technical and non-technical stakeholders.</li> </ul><h3>Nice to have:</h3><ul> <li>Experience with big data technologies (e.g., Hadoop, Spark).</li> <li>Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).</li> <li>Knowledge of DevOps practices and tools.</li> </ul>BenefitsCompetitive salary (open to negotiation) with performance-based bonuses.Professional growth opportunities in a fast-growing startup.Flexible working hours and remote work options.