Python ML Enginner
Found in: Talent IN C2 - 2 weeks ago
Exp Range 4 to 6 years
Role Summary:
We are seeking a skilled Python Full Stack Developer with a strong foundation in SQL and NoSQL databases, coupled with basic knowledge of machine learning, data analytics, and predictive analysis.
He will be responsible for designing, developing, and maintaining scalable web applications and services.
Hands-on experience with ML libraries such as TensorFlow, PyTorch, or scikit-learn. Should have experience in ML any library
Familiarity with DevOps practices and deployment tools. Basic Knowledge
Hands-on experience with Python libraries such as Pandas, NumPy, Matplotlib etc. Must have worked on any libraries
Proficient in using version control systems such as Git. Basic knowledge
Experience with containerization tools like Docker, Cloud- Good to have (Basic knowledge) Workflow
Familiarity with continuous integration and deployment tools like Jenkins, and GitLab CI.-
Responsibilities:
Design, develop, and maintain robust and scalable web applications using Python frameworks such as Django or Flask for backend development.
Develop frontend components using modern JavaScript frameworks such as React.js or Angular. Must have
Integrate user-facing elements with server-side logic for maximum efficiency.
Build and maintain relational and non-relational databases using SQL and NoSQL technologies like PostgreSQL, MySQL, MongoDB, or Redis. SQL or NoSQL
Ensure the responsiveness and performance of applications by optimizing code and implementing best practices.
Collaborate with cross-functional teams to define, design, and ship new features.
Stay updated with emerging technologies and trends in web development, machine learning, data analytics, and predictive analysis.
Troubleshoot and debug issues reported by users and provide timely resolutions.
Conduct code reviews and mentor junior developers to maintain code quality and standards.
Implement continuous integration and deployment processes using tools such as Jenkins, and GitLab CI.
Collaborate with DevOps teams to ensure smooth deployment and maintenance of applications.
Conduct code reviews and implement optimizations for code quality, maintainability, and efficiency.
Work closely with cross-functional teams, including data scientists, and product managers, to deliver integrated solutions.
Communicate effectively with team members and stakeholders to gather requirements and provide updates on project progress.
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