AI/ML Engineer & MLOps 80-100%

In this role, you design, build, and operate production-grade ML and GenAI solutions at Sunrise. You collaborate with business pods to translate roadmaps into scalable pipelines, from experimentation to automated deployment, with governance and observability. You will shape reusable platform components and standards within the ADAO hub, delivering measurable business value across units. This is an opportunity to influence AI outcomes at scale in a cross-functional, innovation-driven environment.

• Design and industrialize ML/GenAI solutions with robust training/inference pipelines and production services
• Co-design architectures with Data Scientists and Domain Pods (batch/real-time, APIs, RAG patterns)
• Industrialize prototypes with automated tests, secure packaging, deployment/rollback, and performance/cost tuning
• Own and evolve MLOps/LLMOps pipelines including CI/CD workflows and model promotion
• Maintain standard CI/CD/CT templates, including model/prompt packaging and validation gates
• Operate model registry/versioning and automated retraining triggers aligned to governance
• Manage experimentation and feature management with reproducible datasets and feature stores
• Run evaluation harnesses for ML/GenAI (including multilingual checks) and share reusable assets
• Produce governance documents, model cards, and audit-ready artefacts for compliance and safety
• Implement AI guardrails, HITL approvals, audit logs, and governance reviews
• Establish observability, runbooks, incident response, and reliability improvements
• Provide reusable ML/GenAI components and coach teams on MLOps/LLMOps best practices
• Build reference implementations and contribute to ADAO AI Academy materials
• Develop deliverables such as ML/LLMOps pipelines, model registry, monitoring dashboards, evaluation suites
• Collaborate across Hub and Pods to ensure consistent engineering standards

• 3+ years in ML engineering, MLOps, software/data engineering or related roles
• Hands-on CI/CD for ML workloads and IaC (Terraform/Pulumi)
• Experience with ML frameworks (scikit-learn, PyTorch, TensorFlow) and serving patterns (REST/gRPC)
• MLOps tooling experience (MLflow, Kubeflow, Azure ML, Vertex AI, SageMaker)
• Strong Python software engineering, APIs, containers (Docker) and cloud deployment patterns
• Familiarity with feature stores, experiment tracking, data quality testing, orchestration tools (Airflow/Dagster/Prefect)
• Cross-functional collaboration in Hub/Pod setups
• Strong communication, stakeholder management, ownership mindset and reliability
• Ability to influence across teams and adapt to evolving AI/ML tech
• Telecommunications experience is a plus

• strong communication
• stakeholder management
• ownership mindset
• CI/CD for ML
• IaC (Terraform/Pulumi)
• ML frameworks (scikit-learn, PyTorch, TensorFlow)