Python AI/ML Engineer

Siri InfoSolutions Inc

Charlotte, NC, United States

about 1 month ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience required

0 years minimum

Compensation

$80,000.0 - $100,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Agile Methodology Artificial Intelligence Automation of Tests Big Data Cloud Computing Profiling Continuous Integration Extract Transform Load (ETL) Relational Databases Database Queries

+26 more

Linux Python (Programming Language) PostgreSQL Machine Learning Apache Maven Node.Js NoSQL Query Optimization Role-Based Access Control Tensorflow Data Logging Data Processing Scripting Data Ingestion Large Language Models Spring-boot Git Pandas Pytest Git Flow Apache Kafka Virtual Agents Data Pipelines Docker Jenkins Microservices

Job description

Design and develop data processing pipelines and utilities using Python.
Java, API, Python, Cloud, Microservice based architecture, Spring boot, Vertex, Kafka, RDBMS, No SQL, Maven, GIT, Jenkins, CI/CD
Implement efficient data ingestion and transformation workflows using Pandas.
Model, implement, and optimize PostgreSQL schemas and queries for large datasets.
Develop and maintain automated test suites using PyTest (unit, integration, regression).
Ensure application observability through logging, metrics, and performance profiling.
Implement data security and compliance measures (RBAC, encryption, auditing).
Collaborate with cross-functional teams to deliver production-ready solutions.

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Requirements

Need to have hands-on experience in PostgreSQL, and PyTest,Gen AI
Python, AI/ML, Tensorflow, LLM, GenAI
Integrate data and service layers via REST/gRPC and enforce type safety.
Build and maintain CI/CD pipelines with quality gates and test automation.
The role involves building robust data processing solutions, optimizing relational databases, and implementing automated testing frameworks for enterprise-grade applications.
Expertise in Python and Pandas for data manipulation and analysis.
Strong SQL skills and hands-on experience with PostgreSQL (query tuning, schema design).
Proficiency in PyTest for automated testing and CI/CD integration.
Familiarity with ETL patterns and large-scale data processing.
Experience with Git-based workflows and CI/CD tools.
Knowledge of Linux, Docker, and scripting for automation.