Backend Engineer

4 weeks ago

Bangalore, India SPG CONSULTING AND SOLUTIONS SERVICES PVT LTD Full time

Must to have skills :

Programming language : Python, Javascript, RESTFul Web Services, Microservices.

Databases : SQL, Cloud : GCP( Google App Engine, GKE).

Methodology : Agile Methodology.

Communication skills : Good.

Other Skills - Minimal Knowledge Required.

DevOps - Git, Bitbucket, Docker, Jira, Quay, Open Shift Platform, Kubernetes, Grafana, Splunk,.

Frameworks - Flask, Sanic, FastAPI, Angular, RabbitMQ Message Queues, Kubeflow, MLFlow, Django,.

ML Libraries - Pandas, scikit-learn, Data Transformation, Enrichment, Classification, GBDT, EDA, Feature Engineering, Data Cleaning, SMOTE, NN, NLP, OpenCV.

Others - JWT-RBAC, WebSockets, TDD, gRPC, HTML, CSS, SCSS, Distributed caching.

Must to have skills :

Programming language : Python, Javascript, RESTFul Web Services, Microservices.

Databases : SQL, Cloud : GCP( Google App Engine, GKE).

Methodology : Agile Methodology.

Communication skills : Good.

Other Skills - Minimal Knowledge Required.

DevOps - Git, Bitbucket, Docker, Jira, Quay, Open Shift Platform, Kubernetes, Grafana, Splunk,.

Frameworks - Flask, Sanic, FastAPI, Angular, RabbitMQ Message Queues, Kubeflow, MLFlow, Django,.

ML Libraries - Pandas, scikit-learn, Data Transformation, Enrichment, Classification, GBDT, EDA, Feature Engineering, Data Cleaning, SMOTE, NN, NLP, OpenCV.

Others - JWT-RBAC, WebSockets, TDD, gRPC, HTML, CSS, SCSS, Distributed caching.

Skills : Artificial intelligence, agile, angular ,css, bitbucket, CI/CD


Exp : 6-10yrs


Key Responsibilities :


- Designing, developing, and deploying AI models and algorithms.


- Collaborating with cross-functional teams to gather requirements and define project objectives.


- Implementing RESTful web services and microservices architecture.


- Utilizing various databases such as SQL, MySQL, MongoDB, PostgreSQL, and Minio for data storage and retrieval.


- Leveraging cloud platforms, specifically Google Cloud Platform (GCP), including Google App Engine and Google Kubernetes Engine (GKE), for scalable and efficient AI solutions.


- Following Agile methodology to deliver high-quality software solutions in a timely manner.


- Demonstrating strong communication skills to effectively communicate with team members and stakeholders.


- Utilizing DevOps tools and practices such as Git, Bitbucket, Docker, Jira, Quay, OpenShift Platform, Kubernetes, Grafana, and Splunk for continuous integration and delivery.


- Working with frameworks like Flask, Sanic, FastAPI, Angular, RabbitMQ Message Queues, Kubeflow, MLFlow, and Django to develop and deploy AI applications.


- Applying machine learning libraries and techniques including Pandas, scikit-learn, GBDT, EDA, feature engineering, data cleaning, SMOTE, neural networks (NN), natural language processing (NLP), and OpenCV.


- Implementing security measures such as JWT-RBAC for authentication and authorization.


- Utilizing technologies like WebSockets for real-time communication and TDD for test-driven development.


- Demonstrating proficiency in HTML, CSS, and SCSS for front-end development.


- Implementing distributed caching for improved performance and scalability.

(ref:hirist.tech)

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