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AI, Data Engineering – Tech Lead III
Carelon Global Solutions PhilippinesTech Lead III - AI driving scalable AI/ML solutions for Carelon, a healthcare solutions company. Focusing on optimizing claims processing and operational efficiency through AI technologies.
Tech Stack
Tools & technologiesAWSAzureCloudGoGoogle Cloud PlatformJenkinsKubernetesMicroservicesNumpyPandasPythonPyTorchRustScikit-LearnSparkSQLTensorflowTerraform
About the role
Key responsibilities & impact- 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.
- 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.
- 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.
Requirements
What you’ll need- Minimum relevant experience - 5+ years in AI Engineering
- Advanced proficiency in Python with expertise in data science libraries (NumPy, Pandas, scikit-learn) and deep learning frameworks (PyTorch, TensorFlow)
- Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques
- Experience with big data processing using Spark for large-scale data analytics
- Version control and experiment tracking using Git and MLflow
- Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing.
- DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations.
- LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management.
- MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining.
- Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems.
- LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security.
- General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP.
- Experience in creating LLD for the provided architecture.
- Experience working in microservices-based architecture.
Benefits
Comp & perks- Extensive focus on learning and development
- An inspiring culture built on innovation, creativity, and freedom.
- Holistic well-being
- Comprehensive range of rewards and recognitions
- Competitive health and medical insurance coverage
- Best-in-class amenities and workspaces
- Policies designed with associates at the center.
ATS Keywords
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Hard Skills & Tools
Data Science Libraries (NumPy, Pandas, scikit-learn)Deep Learning Frameworks (PyTorch, TensorFlow)Model Quantization TechniquesVersion Control (Git, MLflow)Infrastructure as Code (Terraform, CloudFormation)CI/CD Pipelines (GitHub Actions, Jenkins)Microservices ArchitectureSQLTest-Driven DevelopmentConcurrency Processing
Soft Skills
CollaborationProblem-SolvingCommunication