- Company Name
- Accenture
- Job Title
- AI ML Specialist
- Job Description
-
Job Title: AI ML Specialist
Role Summary: Design, implement, and support scalable AI/ML solutions on AWS, leveraging SageMaker and related services (Comprehend, Rekognition, Forecast, etc.). Serve as a technical liaison between clients and AWS product teams, delivering end‑to‑end architecture, data strategy, MLOps, and performance optimization.
Expectations: Deliver architecture and solutions that meet client business needs, provide actionable feedback to AWS, and actively participate in cross‑functional teams to drive innovation and efficiency in complex AI/ML projects.
Key Responsibilities:
- Collaborate with client development and data science teams to capture requirements and translate them into AWS‑based AI/ML solutions.
- Design and architect end‑to‑end workflows, including data ingestion, preprocessing, model training, deployment, monitoring, and governance.
- Build and optimize machine learning pipelines using SageMaker, Redshift, S3, EMR, Kinesis, and other AWS services.
- Develop production‑grade code in Python or R, integrating RESTful APIs and adhering to coding best practices.
- Implement MLOps practices: CI/CD, automated testing, model monitoring, and rollback strategies.
- Provide technical counsel on best practices for security, compliance, and cost‑efficiency.
- Capture and relay customer feedback to AWS SageMaker teams to influence product improvement.
Required Skills:
- 3+ years designing/implementing AI/ML solutions on AWS.
- 3+ years professional programming in Python or R for ML workloads.
- Proficiency with at least one deep‑learning framework (TensorFlow, PyTorch, MXNet, Keras).
- Experience with SparkML, scikit‑learn, and other ML libraries.
- Strong knowledge of AWS services: SageMaker, Redshift, S3, EC2, Data Pipeline, Kinesis, EMR, Kinesis Firehose, Glue.
- Ability to handle terabyte‑scale datasets, GPU‑based training, and hyper‑parameter tuning.
- Familiarity with SQL tuning, data visualization tools, and API design.
- Demonstrated understanding of MLOps principles, model deployment, monitoring, and lifecycle management.
- Excellent communication skills for technical liaison roles.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Machine Learning, Statistics, Operations Research, Mathematics, or related quantitative field.
- AWS Certified Machine Learning – Specialty or equivalent certification preferred.