Job Title: Senior AI/ML Engineer

Location: Hybrid

Job Type: Full-time

About ServiceChannel

ServiceChannel is the leading cloud-based service automation platform for facilities management, trusted by over 500 enterprise clients worldwide. With over 20 years of innovation driving our success, we provide a dynamic environment where engineers can leverage cutting-edge technology to revolutionize how businesses manage repair and maintenance services.

As an engineer at ServiceChannel, you'll have the opportunity to work on a platform that processes millions of service requests annually and supports thousands of service providers globally. You'll contribute to developing sophisticated products that empower businesses with actionable insights and the tools to scale their business.

Join a team committed to pushing the boundaries of technology and delivering exceptional user experiences. Collaborate with a diverse group of talented professionals who are passionate about problem-solving and creating impactful solutions. ServiceChannel offers a unique opportunity to work on complex challenges, innovate at scale, and make a tangible difference in the facilities management landscape.

We are looking for a highly skilled and experienced Senior AI/ML Engineer to join our team. In this role, you will design and implement intelligent systems leveraging both Artificial Intelligence (AI) and Machine Learning (ML) techniques. You will work on building scalable AI-driven solutions, including predictive models, intelligent automation, and data-driven decision systems that enhance product capabilities and user experiences.

Key Responsibilities

• Design, develop, and deploy AI/ML solutions, including predictive models, recommendation systems, and intelligent automation capabilities.
• Build and automate robust, scalable pipelines for data processing, model training, validation, deployment, and monitoring in production environments.
• Collaborate with data scientists, engineers, and product teams to translate business problems into AI-driven solutions.
• Analyse large and complex datasets to extract insights and develop data-driven intelligent systems.
• Own the end-to-end AI/ML lifecycle, including experimentation, model development, deployment, monitoring (e.g., drift detection), retraining, and optimization.
• Develop and integrate AI capabilities such as natural language processing (NLP), anomaly detection, or decision intelligence into applications.
• Implement and manage CI/CD pipelines and MLOps practices for AI/ML workflows, including testing, versioning, and model governance.
• Work closely with engineering and DevOps teams to build scalable infrastructure for training and inference (batch and real-time).
• Stay current with advancements in AI, ML, and Generative AI, and proactively identify opportunities to apply them within the platform.
• Continuously improve engineering practices, automation, and system performance.

Required Skills and Experience

• 5+ years of experience in AI/ML engineering, data science, or a related field.
• Strong foundation in both Artificial Intelligence and Machine Learning concepts, including supervised/unsupervised learning and statistical modelling.
• Hands-on experience in building and deploying AI/ML solutions in production environments.
• Proficiency in Python and SQL for data processing and model development.
• Experience with ML frameworks/libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with Databricks or similar data platforms for building and deploying models.
• Familiarity with AI techniques (e.g., NLP, recommendation systems, or generative AI applications).
• Experience implementing MLOps practices using tools such as MLflow and CI/CD platforms (e.g., GitHub).
• Strong understanding of the full AI/ML lifecycle and production workflows.
• Familiarity with cloud-based data platforms such as Snowflake, AWS, or Azure.
• Strong problem-solving, analytical, and communication skills.

Preferred Skills & Experience

• Experience with Generative AI / LLMs (e.g., OpenAI, LangChain, prompt engineering).
• Experience with real-time inference systems and event-driven architectures.
• Exposure to big data technologies (Spark, Kafka, etc.).