Techversant Infotech

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).