Integration Engineers (Contract 3-6 Months) at SoluGrowth Pty Ltd

Key Responsibilities

• Develop and optimize AI/ML models with LLMs, RAG, vector databases, and modern ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Implement MLOps practices, including CI/CD for ML, model deployment, monitoring, and retraining workflows.
• Design and integrate systems using REST, GraphQL, and gRPC APIs, as well as microservices architecture.
• Utilize Docker, Kubernetes, and orchestration tools for containerization and scaling AI workloads.
• Build and maintain ETL/ELT pipelines to process structured and unstructured data across SQL/NoSQL databases.
• Deploy and manage AI workloads on cloud platforms (AWS, Azure, or GCP).
• Ensure compliance with security and regulatory standards (OAuth, JWT, data encryption, GDPR, HIPAA).
• Write clean, efficient code in Python, with additional integrations in Java, Go, or Node.js.
• Leverage Terraform, Ansible, and automation scripts for cloud infrastructure and deployment automation.
• Collaborate with cross-functional teams to ensure seamless integration of AI solutions into business applications.

Requirements

• Strong experience with AI/ML engineering, particularly LLMs, RAG, and vector databases.
• Hands-on expertise in PyTorch, TensorFlow, Hugging Face, and other ML frameworks.
• Knowledge of MLOps workflows, CI/CD for ML, and monitoring/retraining models in production.
• Proven background in system integration with APIs, microservices, Docker, and Kubernetes.
• Data engineering skills, including SQL/NoSQL, ETL/ELT, and handling large datasets.
• Proficiency in at least one cloud platform (AWS, Azure, or GCP).
• Understanding of security and compliance requirements, including OAuth, JWT, GDPR, HIPAA.
• Strong programming skills in Python; working knowledge of Java, Go, or Node.js.
• Familiarity with Terraform, Ansible, and DevOps tools for automation.
• Excellent problem-solving, communication, and collaboration skills.

Qualifications

• Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or a related field (Master’s preferred).
• Relevant certifications in AI/ML, cloud platforms, or DevOps are advantageous.