Machine Learning Engineer

Job Description :

ServiceChannel is the leading cloud-based service automation platform for facilities management. We empower businesses to source, procure, manage, and pay for repair and maintenance services through a single, unified platform. Our mission is to simplify operations and deliver exceptional customer experiences through innovation and technology.

We are looking for a highly skilled and experienced Senior AI / ML Developer to join our dynamic team. In this role, you will design and deploy state-of-the-art machine learning (ML) models, develop scalable data pipelines, and collaborate with cross-functional teams to drive innovative solutions. You will work with large and complex datasets, implement cutting-edge technologies, and shape the future of our AI-driven initiatives.

Responsibilities :

Build and automate robust, scalable ML pipelines for training, validation, deployment, and monitoring in production environments.

Collaborate with data scientists, engineers, and product managers to understand business requirements and translate them into ML solutions.

Analyze and process large-scale datasets to develop efficient ML models and drive actionable insights.

Own the end-to-end ML model lifecycle , including versioning, deployment, performance monitoring (e.g., drift detection), recalibration, troubleshooting, and retraining.

Develop and manage CI / CD pipelines for ML workflows, including automated testing, containerization, and model registry integration.

Implement and manage scalable ML infrastructure for data processing, training, and inference in collaboration with DevOps and engineering teams.

Continuously improve engineering practices, code quality, and automation, while staying up to date with the latest trends in AI, ML, and MLOps.

Requirements :

Minimum 5 years of experience in ML engineering or a combination of ML engineering and data science, with a focus on data analysis, feature engineering, model development, deployment, and maintenance.

Strong hands-on experience with Databricks for ML model development and deployment.

Strong understanding of machine learning and data science fundamentals (e.g., supervised and unsupervised learning, feature selection, etc.).

Proficiency with popular ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

Experience implementing MLOps practices using tools such as MLflow and CI / CD platforms (e.g., GitHub).

Deep understanding of the ML model lifecycle and production workflows.

High proficiency in SQL and Python.

Familiarity with cloud-based data platforms such as Snowflake or similar technologies.

Excellent communication and interpersonal skills to collaborate across teams.

Robust problem-solving and analytical skills.