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ML Solutions team is seeking a highly skilled and experienced Data Analytics/Machine Learning Engineer with a strong background in developing and deploying AI/ML models and Gen AI based solutions. In this hands-on role, you will be responsible for taking AI models from concept to production, utilizing traditional AI, generative AI and Large Language Models. You will collaborate closely with business partners and stakeholders to introduce and embrace these advanced technologies, elevating client experiences, delivering value to our customers, and ensuring regulatory compliance through cutting-edge technology solutions.
Job Responsibility:
Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks
Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation
Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field
Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services
Requirements:
Strong hands-on experience in Machine Learning, delivering complex solutions to production
Experience with Generative AI technologies essential
Knowledge of NLP, Name Entity Recognition
In-depth knowledge of deep learning and Generative AI frameworks such as, Langchain, Lang Graph, Crew AI or similar
Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas, scikit-learn, NumPy
Experience in using Machine Learning/Deep Learning: XGBoost, LightGBM, TensorFlow, PyTorch
Proficiency in Python Software Development, following Object-Oriented design patterns and best practices
Strong background in mathematics: linear algebra, probability, statistics, and optimization
Experience with evaluation, scoring with framework like ML Flow
Experience of Docker container and edited a Docker file, experience with K8s is a plus
Experience with Postgres and Vector DBs a plus
Excellent problem-solving skills and the ability to think creatively
Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
Publications and contributions to the AI research community are a plus
Bachelor’s/Master’s degree or equivalent experience in Computer Science, Data Science, Statistics, or a related field
Nice to have:
Publications and contributions to the AI research community
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