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Senior Manager - Senior AI Engineer

Maharashtra, India (On-site)

Senior Manager - Senior AI Engineer

2 Months ago • 4 Years + • DevOps • Undisclosed

About the job

15 skills required for this role

Add these skills to join the top 1% applicants for this job

github

python

ci-cd

azure

jira

algorithms

github-actions

helm

kubernetes

kibana

sonarqube

grafana

logstash

docker

terraform

Job Description

Senior AI Engineer required with 4+ years of experience in Python, Pyspark, data modeling, development, and deployment of Data & Analytics products. Expertise in operationalizing, integrating, and scaling algorithmic products is essential. Must have experience in MLOps, DevOps, and building ML pipelines.

Must have:

Python & Pyspark
Data Modeling
MLOps & DevOps
ML Pipelines

Good to have:

Azure ML
Databricks
Machine Learning
GitHub Actions

About the job

Job Location

Mumbai

Job Description

Job Description

Partners with data scientists, data managers, analysts, infrastructure engineers and peer AI Engineers to develop, operationalize, integrate, and scale new algorithmic products.

Engages in proof of concepts and experiments to evaluate new models and technology.

Develops high quality, standard-compliant and tested code. Refactors code of others as necessary.

Contributes code and tools to central re-usable libraries and repositories.

Develops data models, model features, data quality tests, ETL/ELT pipelines, and distributed compute architectures.

Deploys algorithmic products across the clouds, skilfully leveraging cloud-native services. Manages and automates cloud resources (IaC).

Implements DevOps, DataOps and MLOps principles in day-to-day work. Develops continuous integration, delivery, and training pipelines.

Leverages observability and automation tools to manage operations of algorithmic products across the stack.

Click here to hear from the Functional Leader!

Qualifications

Job Qualifications

A Bachelors or Master’s degree in Computer Science, Software Engineering or related field

4+ years of proven experience in Python & Pyspark, data modelling, design, development, and deployment of Data and Analytics products

Demonstrated engineering experience in operationalizing, integrating, and scaling up algorithmic products

Experience in writing python production-level code and code patterns

Experience in MLOps, DevOps, or software engineering, with a specialisation in machine learning

Demonstrated experience in building and managing machine learning pipelines

Strong background in containerization and orchestration technologies (Docker, Kubernetes)

Experience in Agile, CI/CD and DEVOPS methodologies – knowledge of using appropriate tools – e.g. Jira, GitHub Actions, unit testing & mocking, static code analysis (e.g. Sonarqube), source control management tools (e.g. GitHub)

GCP/Azure cloud computing knowledge and services related to machine learning and large-scale computing

Understand best practices for data security, privacy and compliance in the context of AI

Strong written and verbal communication in English

Preferred skills:

Experience with AI / ML products and deployment of products to production (such as Azure Machine Learning and Databricks)

Experience in monitoring and logging ML models

Knowledge and experience in machine learning algorithms development

Experience with source control management tools (GitHub)

Desire to write testable code, and the test coverage to go along with it

CI/CD tools knowledge and experience, familiar working in a DevOps environment

Strong problem-solving skills paired with experience in programming, such as Python

Ability to communicate technical concepts to teammates and non-technical colleagues

Nice to have:

K8 and connected technologies (Helm, Kustomize.io, etc.) knowledge

Infrastructure build tools and languages knowledge – Terraform, Ansible

Logging and monitoring technologies knowledge (depending on the needs, from Logstash to Grafana, Kibana, fluentd)

Job Schedule

Full time

Job Number

R000114606

Job Segmentation

Experienced Professionals (Job Segmentation)

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