Job Description

We are seeking a skilled AI/ML Engineer to design, build, and deploy scalable machine learning and AI solutions. The ideal candidate will have hands-on experience with LLMs, Retrieval-Augmented Generation (RAG), MLOps pipelines, and system integrations, while ensuring compliance and security standards are met. This role involves close collaboration with data scientists, engineers, and business stakeholders to deliver production-ready AI systems that drive business value.


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.