3+ Serverless Jobs in Chennai | Serverless Job openings in Chennai

• Bachelors in Computer Science, Information Systems or equivalent.
• 6 years experience delivering highly available web/mobile applications including 1-3 years as Senior/Lead developer.
• Prior experience in retail domain is a plus.
• 3 years of experience working with distributed teams.
• Deep knowledge of UI Libraries / Frameworks, API (REST), API Management and building scalable and high performance Web APIs.
• Must have experience building websites using Javascript and Java technologies (e.g. Typescript, Spring Boot etc.). Search Engine and Native App development experience is a plus.
• AWS Serverless Cloud native services experience with Lambda functions, SNS, SQS, DynamoDB, API Gateway etc.
• Strong knowledge of Caching frameworks, data structures, algorithms, operating systems, and distributed systems.
• Strong understanding of databases, NoSQL data stores, storage and distributed persistence technologies.
• Strong communication and presentation skills.
• Passionate about enabling next generation experiences.
• Experience with automated testing, deployment pipelines and cloud based infrastructure

• Develop omni-channel digital solutions leveraging serverless and micro services in a cloud based platform to develop backend services.
• Design high/low level solutions, contribute towards architecture and technical roadmap.
• Lead technical implementation/delivery.
• Host/Lead technical discussions.
• Champion software development best practices, test driven development, CI and CD.
• Build cloud native and highly cost efficient solutions.
• Innovate, Unlearn and Disrupt. Research next generation frameworks and technologies.
• Embrace change. 

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.