- As an AI/ML Engineer, you will be responsible for developing AI/ML Solutions based on Deep learning, Reinforcement learning, Computer vision, Expert system, Transfer Learning, NLP, and Generative AI models.
- Design, and deliver ML architecture patterns operable in native and hybrid cloud architectures.
- Create Functional and technical specifications for AI/ML solutions.
- Implement machine learning algorithms in services and pipelines that can be used on a web scale.
- Develop proofs of concept AI/ML based solutions and services and demonstrate it to Business.
- 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.
- Experience in implementing and deploying AI/ML 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.
- Strong proficiency in Python/R/Scala (Python is a must and R, Scala is a plus).
- 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).
- Experience in RDBMS, NoSQL, Big Data stores like Elastic, Cassandra, Hbase, Hive, HDFS and Big Data technologies like Kafka, Apache Spark is a plus.
- Strong knowledge of statistical concepts and techniques.
- Knowledge in data visualization tools (Tableau, Power BI, etc.) and SQL.
- Excellent understanding of object-oriented concepts and Python.
- Experience in NLP models like BERT, Transformer architectures, etc.
- Experience in leveraging Computer Vision and OCR in document extraction use cases.
- Excellent problem-solving and analytical skills.
- Strong communication and presentation skills.
What will make you stand out
- Experience in production software engineering routines (e.g.Continuous Integration/Continuous Deployment).
- Experiences in cloud-based solutions (e.g. AWS, Azure, GCP).
- Experience working using Agile-based principles and tools.
- Familiarity with working on large data sets and distributed computing (e.g. Hive, Spark, Kafka, Airflow,Scala).
- Certification in any of the available cloud-based AI/ML technologies is a plus.
Experience and Qualification:
- B Tech/M.Tech/Ph.D CS/IS/IT or Msc Statistics, MCA
- 5+ years of relevant experience in AI/ML projects.
