About the role:
At Cognizant, we're not just at the forefront of technological innovation - we're actively shaping the future of the digital landscape. As a rapidly expanding global leader in IT services, we're seeking a Senior Machine Learning/AI Engineer to join our growing Data & AI practice. In this role, you'll combine deep technical expertise with consulting skills to deliver cutting-edge AI solutions while also contributing to presales activities and architectural decisions.
The Senior Consulting Data & AI Engineer is responsible for:
- Lead complex machine learning projects, including those involving large-scale datasets, complex models, and distributed computing environments.
- Develop and deploy state-of-the-art machine learning models, incorporating techniques like deep learning, reinforcement learning, and generative AI to address challenging business problems.
- Conduct comprehensive data analysis to identify patterns, trends, and insights that inform model development, ensuring that the models are built on a solid foundation of data understanding.
- Implement robust data pipelines to ensure data quality, consistency, and efficiency, optimizing data flow and reducing errors.
- Optimise model performance through techniques like hyperparameter tuning, feature engineering, and model selection, ensuring that the models achieve the highest possible accuracy and efficiency.
- Deploy machine learning models into production environments and monitor their performance to identify and address any issues that may arise.
- Develop and maintain machine learning infrastructure and tools, providing a scalable and efficient environment for model development and deployment.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions, ensuring that the machine learning models align with business objectives.
- Communicate technical concepts effectively to both technical and non-technical audiences, facilitating collaboration and understanding.
- Stay up-to-date with the latest advancements in machine learning, data engineering, and generative AI to ensure that you are at the forefront of the field.
- Mentor junior engineers and foster a culture of knowledge sharing, contributing to the development of the next generation of data scientists.
Base capability requirements include:
- Master's degree in Computer Science, Data Science, or related field
- 5+ years of experience in machine learning and AI development
- Strong foundation in machine learning algorithms and statistical modeling
- Expert-level proficiency in Python and related ML libraries (scikit-learn, TensorFlow, PyTorch)
- Experience with deep learning frameworks and architectures (CNNs, RNNs, Transformers)
- Practical experience with MLOps tools and practices
- Strong knowledge of data engineering principles and practices
- Experience with distributed computing platforms (Spark, Databricks)
- Proficiency in SQL and experience with both relational and NoSQL databases
- Experience with cloud platforms (AWS, Azure, or GCP) for ML workloads
- Strong software engineering practices and version control (Git)
- Excellent communication skills and ability to explain complex technical concepts
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Familiarity with modern AI tools and frameworks (Hugging Face, OpenAI, etc.)
Nice to have:
- Experience with generative AI and large language models
- Contributions to open-source ML projects
- Published research papers or technical blog posts
- Experience with real-time ML systems
- Knowledge of AI ethics and responsible AI practices
