Description :
Whats important to us :
Techversant is seeking a highly skilled and experienced AI / ML Lead to lead the design and implementation of our artificial intelligence and machine learning solutions.
The successful candidate will work closely with cross-functional teams to understand business requirements and develop scalable, efficient, and robust AI / ML systems.
Job Description :
- As a AI / ML Lead, you will need to build Solutions based on Deep learning, Reinforcement learning, Computer vision, Expert system, Transfer Learning, NLP, and generative models.
- To Define, design, and deliver ML architecture patterns operable in native and hybrid cloud architectures.
- Implement machine learning algorithms in services and pipelines that can be used on a web scale.
- Create demos and proofs of concept, develop AI / ML based products and services.
- Creating Functional and technical specifications for AI & ML solutions.
- Follow SDLC process.
- Advanced analytical knowledge of data and data conditioning.
- Programming advanced computing and developing algorithms.
- Developing software, data models and executing predictive analysis.
- Design, develop, and implement generative AI models using state-of-the-art techniques.
- Collaborate with cross-functional teams to define project goals, research requirements and develop innovative solutions.
- Strong proficiency in Python / R / Scala (Python is a must and R, Scala is a plus).
- Strong proficiency in SQL, NO SQL Databases.
- Experience in implementing and deploying AI\ Machine Learning solutions (using various models, such as CNN, RNN, Fuzzy logic, Q learning, SVM, Ensemble, Logistic Regression, Random Forest etc.
- Specializes in at least one of the AI / ML stack, Frameworks, and tools like MxNET and Tensorflow.
- Hands-on experience with data analytics and classical machine learning, deep learning tools (e. Pandas, NumPy, Scikit-learn) and deep learning frameworks (e. Tensorflow, Pytorch).
What will make you stand out :
Experience in production software engineering routines in DevOps / MLOps (e. Continuous Code Integration and Deployment).Experiences in cloud-based solutions (e. AWS, Azure, GCP).(ref : hirist.tech)