Full-Time Machine Learning Engineer

Candidates for this position are ML engineers with strong programming skills who demonstrate curiosity, continuous learning, and an ability to adapt. Ideal candidates have a background in Artificial Intelligence, Machine Learning, and data science. Need to create functional prototypes to showcase capabilities to customers in the AI/ML space. The role will be in the ML Ops team, which is a subset of the Architecture team, with focus on developing AI/ML solutions.

Scope of Responsibilities / Expectations:

• Develop AI/ML Solutions to address business requirements.
• Perform feature engineering activities common to machine learning
• Display standard data science statistics for models
• Determine which features are relevant and contributing to the solution
• Work with functional and integration teams to help architect an end to end solution
• Be able to set up APIs to test the predictions
• Understand various algorithms and which are best for each use case
• Understanding and ability to handle regression, forecasting, categorical, and classification
• Develop and maintain artificial intelligence components
• Research, explore, and implement practical applications leveraging a wide range of Generative AI models.
• Gain hands-on experience in designing, building, and evaluating AI-powered solutions to address real-world challenges across diverse domains.
• Embrace and master new and emerging AI technologies through focused learning, experimentation, and practical implementation.
• Continuously expand the depth and breadth of AI knowledge and skills to stay at the forefront of technological advancements.
• Design, implement and support machine learning algorithms
• Rebuild and retrain production models regularly
• Experiment with new AI/ML services and evangelize the benefits.
• Develop standards and procedures for machine learning Platforms.
• Optimize models for performance, accuracy, and efficiency in line with organizational requirements.
• Ensure data quality, consistency, and ethical use, adhering to privacy regulations and best practices.
• Monitor and mitigate risks associated with bias, misuse, and unintended consequences of generative AI systems.
• Translate complex technical concepts into accessible language, ensuring effective communication and understanding among stakeholders at all levels.

Must Haves:

• Expertise in Python, Pandas, Numpy, etc.
• Experience with data science packages and machine learning frameworks
• Expertise in Machine Learning Techniques, Artificial intelligence,
• Experience with AI/ML frameworks
• Experience working in projects that have deployed AI/ML models in production
• Experience working with container technologies like Docker, Kubernetes
• Self-motivated team player who demonstrates initiative and flexibility
• Strong verbal and written communication skills