AI/ML Lead
5 days ago
What's 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.g. Pandas, NumPy, Scikit-learn) and deep learning frameworks (e.g. Tensorflow, Pytorch).
What will make you stand out
• Experience in production software engineering routines in DevOps/MLOps (e.g.Continuous Code Integration and Deployment).
• Experiences in cloud-based solutions (e.g. AWS, Azure, GCP).
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