Note: The job is a remote job and is open to candidates in USA. NTT DATA’s client is seeking an AI/ML Engineer to design, develop, and deploy scalable AI and machine learning solutions. The role builds production-ready ML solutions and integrates AI capabilities into enterprise applications in collaboration with data scientists, data engineers, application developers, and business stakeholders.
Responsibilities
- Design, develop, train, and deploy Machine Learning models for enterprise use cases
- Develop data preprocessing, feature engineering, model training, and evaluation pipelines
- Build and integrate AI/ML services with enterprise applications using APIs and Microservices
- Evaluate ML algorithms and optimize models for accuracy, performance, and scalability
- Develop automated ML pipelines for model training, testing, deployment, and monitoring
- Collaborate with Data Scientists, Data Engineers, and business teams to translate requirements into AI/ML solutions
- Implement MLOps practices for model versioning, deployment, monitoring, and lifecycle management
- Work with structured and unstructured datasets from multiple sources
- Monitor production models and address model performance, drift, and data-quality issues
- Participate in code reviews, technical design discussions, and Agile delivery activities
Skills
- 5+ years of experience in Python development, Data Science, or Machine Learning engineering
- 3+ years of experience developing ML solutions using Scikit-learn, TensorFlow, PyTorch, or similar frameworks
- 3+ years of experience with data processing, feature engineering, SQL, and model development
- 2+ years of experience deploying AI/ML solutions on AWS, Azure, or Google Cloud Platform
- Experience with Generative AI, Large Language Models (LLMs), and Agentic AI
- Knowledge of RAG, embeddings, vector databases, and semantic search
- Experience with LLM frameworks such as LangChain, LlamaIndex, or similar technologies
- Experience with Azure OpenAI, Amazon Bedrock, Vertex AI, or similar AI platforms
- Knowledge of MLOps tools and model lifecycle management
- Experience with Docker, Kubernetes, and CI/CD pipelines
- Familiarity with Spark, Databricks, Snowflake, or other enterprise data platforms
- Understanding of responsible AI, model governance, security, and data privacy
- Experience developing AI solutions within Banking, Financial Services, Healthcare, Retail, or other enterprise domains
- Strong analytical, problem-solving, communication, and stakeholder management skills
Benefits
- Hybrid work arrangement
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