Senior Software Engineer - Artificial Intelligence / Machine Learning

Description :

Primary Skills : AI, AI - SciKit / Deep Learning, Computer Vision, AI Engineering, Django, Flask, FastAPI Microservices Framework, Microservices, MongoDB, Python.

• Develop and maintain microservice architecture and API management solutions using REST and gRPC for seamless deployment of AI solutions.
• Collaborate with cross-functional teams, including data scientists and product managers, to acquire, process, and manage data for AI / ML model integration and optimization.
• Design and implement robust, scalable, and enterprise-grade data pipelines to support state-of-the-art AI / ML models.
• Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements.
• Familiarity with tools like Terraform, CloudFormation, and Pulumi for efficient infrastructure management.
• Create and manage CI / CD pipelines using Git-based platforms (e.g., GitHub Actions, Jenkins) to ensure streamlined development workflows.
• Operate container orchestration platforms like Kubernetes, with advanced configurations and service mesh implementations, for scalable ML workload deployments.
• Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment.
• Engage in advanced prompt engineering and fine-tuning of large language models (LLMs), focusing on semantic retrieval and chatbot development.
• Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC.
• Research and implement cutting-edge LLM optimization techniques, such as quantization and knowledge distillation, ensuring efficient model performance and reduced computational costs.
• Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modeling.
• Design and execute rigorous A / B tests for machine learning models, analyzing results to drive strategic improvements and decisions.
• Stay up-to-date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function.
• Contribute to creating specialized AI solutions in healthcare, leveraging domain-specific knowledge for task adaptation and deployment.

(ref : hirist.tech)