We are seeking a Machine Learning Engineer to design, build, deploy, and scale complex machine learning and AI solutions. This role will focus on developing production-ready ML systems, scalable cloud infrastructure, machine learning pipelines, Knowledge Graph solutions, and GenAI/LLM applications. The ideal candidate will have strong software engineering skills in Python and Java, hands-on experience with GCP and Vertex AI, and experience working with AI/ML, data pipelines, graph technologies, and MLOps.
Responsibilities
- Design and develop innovative machine learning models and software algorithms to solve complex business problems.
- Build, maintain, and optimize scalable ML pipelines, architecture, and infrastructure.
- Train, retrain, deploy, and manage ML models in production environments.
- Automate ML model deployment and training using CI/CD/CT and MLOps practices.
- Develop solutions involving computer vision, object detection, classification, tracking, and other ML applications.
- Build and deploy Knowledge Graph solutions using cloud-native data pipelines.
- Design and maintain graph entities, relationships, and data models.
- Develop and operate MCP services that expose graph and event-store data to AI agents.
- Build LLM and agent-based solutions using tools such as RAG, grounding, and enterprise AI APIs.
- Develop monitoring, observability, dashboards, alerting, and tracing for AI/data systems.
- Partner with data engineers and application teams to onboard and validate enterprise data.
- Establish data contracts, schema validation, quality checks, governance, and data lineage.
Experience Required
- 7+ years of IT experience, 3+ years of software development experience.
- 2+ years of AI and Graph Engineering experience.
- Strong Python and Java development skills.
- Experience with GCP and cloud-native AI/data platforms.
- Hands-on experience with Vertex AI and BigQuery.
- Experience with Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, and Cloud Storage.
- Experience with graph data modeling and querying, including GQL, Neo4j, Spanner Graph, or similar technologies.
- Experience building LLM/AI agent systems, RAG, grounding, and model integrations.
- Familiarity with MCP or similar agent tool protocols.
- Experience with MLOps, CI/CD, and production deployments.
- Experience with Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting.
- Experience with Terraform, IAM, security, and secrets management.
- Ability to work with data producers to model and validate enterprise data.
Experience Preferred
- Dataplex or Data Catalog.
- Streaming/CDC and event-driven architectures.
- Event-sourced data modeling.
- User-facing applications and dashboards using Knowledge Graph data.
- Experience with product development, manufacturing, quality, or supply-chain data.
- Data quality frameworks and schema evolution.
- Blue-green or zero-downtime deployments.
Education Required
- Bachelor's Degree