Machine Learning Ops

About Us
At SILVARE, we’re a dynamic team achieving remarkable results. We’ve built a reputation for delivering fast, impactful results that keep our clients coming back, many of whom are some of the biggest names in tech.

What Μakes Us Different
We’re easy to talk to, we get straight to the point and we’re all about making things happen. We’re proud of the strong relationships we build, both with our team and our clients. We believe in keeping our people happy, whether it’s through improving benefits, having open conversations about their projects or just being there when they need us. It’s a supportive environment and culture that helps both us and our people thrive. If you’re ready to work on exciting projects, grow alongside industry leaders and make a real impact, we’d love to have you join us at SILVARE.

Role Overview
We are looking for a Machine Learning Ops Engineer for our client. In this role, you will be responsible for designing, implementing, and scaling end-to-end machine learning and AI infrastructure on Databricks. You will contribute to building a unified ML platform that supports multiple business domains, ensuring robust, automated, and scalable ML workflows across the entire lifecycle — from data ingestion and feature engineering to deployment and real-time model serving. You will collaborate closely with data science, platform, and software engineering teams to ensure secure, compliant, and efficient ML operations.

What You’ll Be Doing

• Architect, deploy, and maintain ML pipelines for training, evaluation, deployment, and continuous monitoring using Databricks, MLflow, and related tools.
• Build and manage CI/CD workflows for ML model versioning, testing, and controlled releases.
• Design and operationalize feature pipelines using Databricks Feature Store or similar technologies.
• Implement observability and drift detection for both model and data performance using tools such as Evidently AI, Prometheus, and Grafana.
• Collaborate with platform teams to optimize GPU/CPU clusters, Delta Live Tables, and Unity Catalog for scalability, reproducibility, and compliance.
• Automate infrastructure provisioning using Terraform and Databricks APIs.
• Champion best practices in MLOps, AIOps, and ML governance, ensuring secure and efficient model lifecycle management.
• Partner with data scientists to transition research models into production with minimal friction.
• Evaluate and implement real-time model serving architectures (batch, streaming, or online inference).
  
  

What You’ll Bring

• 4+ years of experience in MLOps, ML Platform Engineering, or similar production-focused ML roles.
• Strong background in containerization and orchestration (Docker, Kubernetes).
• Proven experience building ML pipelines on Databricks, including MLflow, Delta Lake, Unity Catalog, and Feature Store.
• Proficiency in Python, shell scripting, and Git-based development workflows.
• Experience with monitoring and observability tools such as Prometheus and Grafana.
• Familiarity with streaming data technologies (Kafka, Spark Structured Streaming).
• Experience with IaC (Terraform) and workflow orchestration tools (Airflow, Prefect).
• Excellent problem-solving, communication, and cross-functional collaboration skills.
  
  

Nice to Haves

• Experience designing multi-model architectures and scalable model serving systems.
• Exposure to LLMOps and generative AI deployment patterns on Databricks or similar platforms.
• Knowledge of AIOps tools for intelligent alerting, anomaly detection, and system optimization.
• Relevant certifications such as Databricks Certified Machine Learning Professional, Azure AI Engineer Associate, or Azure DevOps Engineer Expert.
  
  

Why Join Them?

💸 Competitive salary package.

💻 Career coaching and mentorship to support your professional growth.

🌈 Diverse and multicultural teams that promote inclusivity.

🦄 Outstanding working environment.

🚀 Continuous training and development opportunities.

Excited to Make an Impact? Apply today and be part of what we’re building together 🙂

At SILVARE, we are committed to diversity, equity, and inclusion in all aspects of our workplace. We welcome applicants from all backgrounds and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or any other characteristic protected by law.