Senior Software Engineer

Key Responsibilities

Design and develop AI/ML based software production enhance data transformation, cleaning, and validation for improved data quality and insights.
Perform data modeling, application development, technical product assistance, and tuning to meet customer performance and functional requirements.
Perform requirement assessment, information gathering, and recommend appropriate business solutions to the company’s customers.
Work on solution-crafting pre-defined business problems that require Data Science approaches.
Formulate innovative solutions that best bridge any gaps between a client’s requirements and standard system functionality.  
Create polished, high-quality deliverables on time.  
Effectively communicate with subordinates, peers, superiors, and clients in a way that drives deliverables forward and maintains open communication lines.  
Provide technical assistance and cross-training to other team members.
Collaborate with the team to create data conversion scripts/integrations and test it ensuring data quality and acceptable system performance.

Bachelor’s degree in computer science or engineering or related field(s).
4+ years of experience in data engineering, with at least 2-3 years specifically working with AI/ML based technologies.
Strong problem-solving skills with an emphasis on product development, demonstrates curiosity.
Experience using languages such as Python and SQL to manipulate data and draw insights from large data sets.
Knowledge of a variety of machine learning algorithms (clustering, decision tree learning, artificial neural networks, LLM etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques
Experience with data pre-processing and feature engineering.
Experience working with and creating data architectures and data lake management.
Prior knowledge/experience of Pandas, Numpy, Matlab, Matplotlib, ggplot, Pytorch /Tensorflow, Apache Spark, Keras, Go.
Knowledge in version control system like GIT, SVN, and Mercurial.

Experience in natural language processing (NLP), computer vision, or other specialized AI fields is a plus.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for deploying AI models.
Familiarity with MLOps tools and frameworks for model management and deployment (e.g., MLflow, Kubeflow, Docker).
Experience of programming languages like C++, Java and Scripting Language (JavaScript).

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