Boeing Australia is hiring an Experienced Machine Learning Developer (MLOps) in Bangalore, India. In this role, you will lead the design and implementation of scalable machine learning systems to empower data-driven decisions across the organization. You'll collaborate closely with cross-functional teams to translate business requirements into reliable, secure, and cost-effective ML architectures.

What You'll Do

Design and build highly reliable, scalable ML and AI solutions aligned with business goals.
Lead the creation of scalable, robust ML architectures including MLOps and AIOps using cloud-native services (AWS, Azure, GCP) and open-source frameworks.
Design, build, and optimize machine learning models for accuracy, efficiency, and scalability.
Collaborate with data engineers, data scientists, software developers, and DevOps teams to integrate models into production systems.
Assess and recommend ML tools, frameworks, and platforms to deliver business value.
Design and develop Generative AI use cases involving LLMs, RAG, Agentic workflows, multi-modal AI, fine-tuning, vector databases, and prompt engineering.
Build and optimize CI/CD pipelines for rapid, reliable software releases.
Automate repetitive tasks like provisioning, configuration, and monitoring using tools like Terraform or Ansible.
Integrate DevOps and MLOps practices into the software development lifecycle and support containerized applications (e.g., Docker, Kubernetes).
Own all communication and collaboration channels for assigned projects, providing updates to stakeholders, senior leadership, and cross-functional teams.
Establish and manage working relationships with vendors, partners, and cross-functional teams, holding them accountable.

What We're Looking For

A Bachelor’s degree.
5+ years of experience designing and deploying ML workloads in AWS, Azure, or GCP using Kubernetes, Docker, and Terraform.
3+ years of hands-on experience with MLFlow, Kubeflow, SageMaker, Vertex AI, or Databricks ML Runtime for model tracking and CI/CD.
5+ years of progressive experience in DevOps and cloud platform operations.
3+ years of hands-on experience designing and managing multi-cloud CI/CD pipelines (AWS, Azure, GCP, Databricks, Snowflake).
3+ years of experience with Infrastructure as Code (Terraform, CloudFormation, or Ansible) and containerization (Docker & Kubernetes).
3+ years of experience implementing observability, monitoring, and tracing frameworks (Prometheus, Grafana, ELK/EFK, Datadog).
3+ years of experience applying FinOps and cost optimization strategies in CI/CD pipelines and cloud operations.
3+ years of experience implementing security controls in CI/CD pipelines and cloud platforms (IAM, RBAC, secrets management, encryption).

Nice to Have

5+ years of strong scripting and automation skills (Bash, Python, PowerShell).
3+ years of experience in Manufacturing and Aviation domains.
3+ years of experience implementing event-driven, cloud-agnostic DevOps architectures for microservices, APIs, and serverless workloads.
3+ years of experience integrating DevOps, MLOps, and AI/ML-driven observability or anomaly detection into infrastructure and DevOps pipelines.

Technical Stack

Cloud Platforms: AWS, Azure, GCP
Orchestration & Containers: Kubernetes, Docker
Infrastructure as Code: Terraform, CloudFormation, Ansible
ML Tools & Platforms: MLFlow, Kubeflow, SageMaker, Vertex AI, Databricks ML Runtime, Snowflake
Observability & Monitoring: Prometheus, Grafana, ELK/EFK, Datadog
Scripting & Automation: Bash, Python, PowerShell