NTT DATA is seeking an AI ML Engineer/Architect to design, develop, and deploy machine learning models and AI-driven solutions that solve real-world problems and drive measurable business value.
Requirements
- 8+ years of experience in developing and deploying machine learning models and AI solutions in real-world environments.
- 5+ years of experience programming in Python, with expertise in ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
- 5+ years of experience working with core machine learning algorithms, data structures, and statistical modeling techniques.
- 3+ years of experience using cloud platforms (AWS, GCP, Azure) for building and deploying AI/ML solutions, including familiarity with ML Ops tools (e.g., SageMaker, Vertex AI, Azure ML).
- 2+ years of experience or exposure to data engineering tools such as Apache Spark, Airflow, or Kafka (preferred but not mandatory).
- Experience with deep learning, reinforcement learning, or generative AI (e.g., GANs, LLMs).
- Experience deploying models in real-time inference systems or on edge devices.
Responsibilities
- Design and implement machine learning models for classification, regression, clustering, recommendation, NLP, or computer vision tasks.
- Collaborate with data scientists, software engineers, and product teams to integrate ML models into production systems.
- Build and maintain scalable data pipelines and model training workflows.
- Conduct experiments, evaluate model performance, and iterate to improve accuracy, efficiency, and robustness.
- Stay up to date with the latest research and advancements in AI/ML and apply them to relevant projects.
- Optimize models for performance, scalability, and interpretability.
- Document processes, models, and systems to ensure reproducibility and knowledge sharing.
Other
- 6 months contract duration
- REMOTE position
- NO STEM OPT
- Strong problem-solving, analytical thinking, and communication skills with the ability to translate complex concepts into practical applications.
- Prior experience working with Health Plan applications and healthcare data architectures is a strong plus.
