- Company Name
- Node.Digital LLC
- Job Title
- AI/ML Engineer
- Job Description
-
**Job title**
AI/ML Engineer
**Role Summary**
Architect, develop, and maintain intelligent automation solutions using generative AI and machine learning technologies on AWS. Lead design and deployment of scalable models, APIs, and document‑processing bots, ensuring continuous improvement and operational excellence in a cloud‑native, serverless environment.
**Expectations**
- Deliver high‑quality AI/ML solutions within an Agile framework.
- Communicate technical concepts clearly to cross‑functional teams.
- Work remotely with discipline and adaptability.
- Demonstrate strong problem‑solving skills for complex AI challenges.
**Key Responsibilities**
1. Design and implement generative AI solutions with Amazon Bedrock, foundation models, and RAG architectures.
2. Build repeatable intelligent bots for document processing and data cleansing.
3. Develop and deploy scalable ML/AI models on AWS (SageMaker, Lambda, CDK).
4. Create REST/GraphQL API endpoints and integrate AI services across systems.
5. Monitor model performance, conduct evaluation, and drive continuous improvement.
6. Collaborate with engineering, product, and business stakeholders to embed AI capabilities.
**Required Skills**
- 6–10 yrs overall application/framework development experience; ≥5 yrs in AI/ML solution development with a focus on generative AI.
- Hands‑on AWS services: Bedrock, SageMaker, Lambda, CDK, S3, and related AI/ML services.
- Expertise in OCR/ICR/OMR, NLP, Deep Learning, and generative AI (LLMs, RAG, prompt engineering, fine‑tuning).
- Strong programming in Python; proficiency with TensorFlow, PyTorch, LangChain.
- Web API development (REST, SOAP, JSON, XML) and asynchronous/multi‑threaded programming.
- Deep understanding of algorithms, data structures, optimization, caching, security.
- Experience with SQL Server, PostgreSQL, and NoSQL/vector databases for RAG.
- Knowledge of AWS cloud architecture patterns, serverless computing, CI/CD, DevSecOps, and Agile methodologies.
- Version control: Git (TFS, SVN) and familiarity with SDLC phases.
- (Optional) Front‑end frameworks (React/Angular/Vue), UiPath RPA, chatbot development, Bedrock Agents, model distillation, responsible AI practices.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Engineering, or related field.
- Minimum 5 yrs of automation engineering experience with AI/ML integration.
- Preferred certifications: AWS Certified Machine Learning – Specialty, AWS Certified Solutions Architect.
- (Nice to have) TensorFlow Developer, Azure AI Engineer, UiPath AI Center.