AI/ML Data Engineer

2 weeks ago


Bengaluru, India ACCELON PREMIERE CONSULTANTS PRIVATE LIMITED Full time
Description:

Location: Bangalore (Hybrid)Shift: Afternoon Shift

Work Experience (Years) -: Overall 5-7 years of experience. 4+ years of relevant experience.Hiring Qualification- B.Tech/ BE

Job Responsibilities:

Developing AI/ML algorithms to analyze huge volumes of historical data to make predictions and recommendations.Implement and optimize deep learning models for generative tasks such as image synthesis, voice etc.Collaborate with software engineers to integrate Generative AI models into production systems.Should be able evaluate the application cases and problem-solving potential of AI/ML algorithms and rank them according to success likelihood.Should be able to comprehend data through exploration and visualization, spot discrepancies in data distribution.Should be able to work on structured as well as unstructured data.Should be able to develop various algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production.Should be able to leverage cloud platforms for training and deploying large scale solutions (AWS Preferred).Should have working knowledge on managing ModelOps framework.Should understand CI/CD processes in product deployment and used it in delivery.Should be able to collaborate with data engineers to build data and model pipelines and maintain accuracy.Should be able to take complete ownership of the assigned project.Experience of working in Agile environments.Well versed with JIRA or equivalent project tracking tool".

Competencies / Skills:

Understanding of AI/ML frameworks, LLM libraries, data structures, data modeling, and software architecture.Proficiency with a deep learning framework such as TensorFlow, Keras, NLP and text analytics and ML algorithms like clustering, regression, classification etc.Proficiency with Python and basic libraries for machine learning such as scikit-learn, pandas.

Experience working with recommendation engines, data pipelines and distributed machine learning.Ability to select hardware to run an ML model with the required latency.Knowledge of cloud platforms (AWS, Azure and GCP).Great communication and collaboration skills."


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