Full Stack Engineer - Python/MLOps (6-13 yrs)

Job Title : Full Stack + MLOps Engineering

Experience Range : 6+ Years

Location : Bangalore (Hybrid - 2 Days Work From Office in a Week)

Job Summary :

We are seeking a talented and experienced Full Stack Engineer with expertise in either Java or Python, strong skills in modern frameworks, and a solid understanding of ML/MLOps. The ideal candidate should be able to build and manage scalable applications, develop and maintain high-quality code, and effectively integrate ML solutions into production environments. This is not a Data Scientist role but requires a deep understanding of the engineering and deployment aspects of ML systems.

Key Responsibilities :

- Develop and maintain full-stack web applications using Java or Python and relevant front-end frameworks (e.g., React, Angular, Vue.js).

- Design, implement, and manage back-end services and APIs, ensuring performance, scalability, and reliability.

- Architect and integrate ML pipelines into scalable systems using MLOps best practices, including model deployment, monitoring, and versioning.

- Collaborate with Data Scientists to understand ML requirements and ensure proper integration into the product.

- Implement CI/CD pipelines for seamless deployment of applications and ML models.

- Ensure high-quality code through unit tests, code reviews, and adherence to best practices in software development.

- Develop and manage cloud-based or on-premises infrastructure for application and ML workflows.

- Monitor and troubleshoot production issues, ensuring application uptime and performance.

- Stay updated with industry trends, new technologies, and best practices in Full Stack Development and MLOps.

Required Skills and Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 6+ years of experience in full-stack development using Java or Python.

- Proficiency in frameworks such as Spring Boot (Java) or Django/Flask (Python).

- Strong experience with front-end technologies like HTML, CSS, JavaScript, and frameworks like React, Angular, or Vue.js.

- Hands-on experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Airflow, SageMaker, TensorFlow Serving, etc.).

- Proficiency in containerization (Docker) and orchestration tools (Kubernetes).

- Experience with cloud platforms like AWS, Azure, or GCP for deployment and management of applications and ML services.

- Strong understanding of software engineering best practices, including code versioning (Git), continuous integration, and continuous delivery.

- Experience with databases (SQL and NoSQL) and ORM frameworks.

- Solid understanding of RESTful API design and development.

- Excellent problem-solving, debugging, and analytical skills.

- Strong communication and collaboration skills, with a team-oriented mindset.

Nice-to-Have Skills :

- Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack).

- Knowledge of security best practices for web and cloud applications.

- Familiarity with Agile methodologies and DevOps practices.

- Exposure to other ML frameworks or tools like PyTorch, Apache Spark, or DataBricks.