Senior Machine Learning Engineer

Description :

Job description :

Hiring for Product Based & US Based Company

Location : Mumbai {remote option for out station otherwise Hybrid}

KEY ACCOUNTABILITIES :

Establish and Implement MLOps practices :

- Development of end-to-end MLOps framework and Machine Learning Pipeline using GCP, Vertex AI and Software tools

- Management of data pipelines including config, ingestion and transformation from multiple data source like Big Query, Dbt & Google cloud storage etc

- Meta Data and statistics Data pipeline setup using GCP Bucket and MLMD

- Re-Training and Monitoring Pipeline setup with multiple criteria Vertex AI

- Serving Pipeline with multiple creation Vertex AI and GCP services

- Resource and Infra Monitoring configuration and pipeline development using GCP

- Automated pipeline Development for Continuous Integration (CI)/Continuous Deployment (CD) Continuous Monitoring (CM)/Continuous Training (CT) using GCP-native tool

- Branching strategies and Version Control using GitHub

- ML Pipeline orchestration and configuration using

- DAG and Workflow orchestration using airflow/cloud

- Code refactorization & coding best practices implementation as per industry standard

- Technology-Stack suggestion based on 360 Deg

- Implementing MLOps practices on project and follow the set MLOps

- Support the ML models throughout the E2E MLOps lifecycle from development to maintenance

Architecture :

- Micro Services Architecture and framework Development concept

- Agile software Development concept

- Architecture Design for HLD, LLD and Solution design

Team Mentoring :

- Programming language Pattern Design implementation

- Review projects PR and PBIs and suggestion for improvement

- Knowledge sharing session with team for specific ML Ops

- Guide/Mentor team members for MLOps framework development

Research, Evolve and Publish best practices :

- Research and operationalize technology and processes necessary to scale ML Ops

- Ability to research and recommend MLOps best practices on new technologies, platforms, and

- MLOps pipeline improvement plan and suggestion

Communication and Collaboration :

- Collaborate with technical teams like Data Science Lead, Data Scientist, Data Engineer and Platform

- Knowledge sharing with the broader analytics team and stakeholders is

- Communicate on the on-goings to embrace the remote and cross geography

- Align on the key priorities and focus

- Ability to communicate the accomplishments, failures, and risks in timely manner.

- Continually invest in your own knowledge and skillset through formal training, reading, and attending conferences and meetup

- Document MLOps Process, Development, Architecture & Innovation etc and be instrumental in reviewing the same for other team members

MINIMUM QUALIFICATIONS :

- Total experience required 10-12+ yrs

- Min qualification - Bachelor's degree (full time)

- Expertise and at least 5yrs of professional experience in MLOps E2E framework

- Expertise in Data Transformation and Manipulation through Big-Query/SQL

- Professional experience Vertex AI and GCP Services

- Expertise in one of the programming Language Python/R

- Airflow/Cloud composer Experience

- Kubernetes/Kubeflow Experience

- MLflow Professional experience

- TFX Professional experience

- Docker -container Experience

- At least 5yrs of professional experience in the related field of Data Science

- Strong communication skills both verbal and written including the ability to interacteffectively with colleagues of varying technical and non-technical

- Passionate about agile software processes, data-driven development, reliability, and systematic

Expert level :

- ML Ops E2E framework

- Big Query/SQL

- Python / R

- Vertex AI and GCP Services

- Docker-Container

- Kubeflow/Kubernetes

- TFX

- Airflow

- MLflow

- GitHub

- Strong communication skills

Intermediate level :

- Machine Learning and Deep Learning algorithms

- Agile techniques

- Demonstrates teamworking skills.

- Mentor others and lead best practices.

- Micro Services concept

- Power BI, Tableau, Looker

Basic Level :

- Good to have domain knowledge : Consumer Packed Goods industry and data sources

- Analytic toolset- dbt, atscale, neo4j, Atlassian

PREFERRED QUALIFICATIONS :

- GCP certification

- Understanding of CPG industry

- Bcsic understanding of dbt

- AutoML Concept

- Machine Learning -Concept of Algorithms

- Deep Learning- Concept of Algorithms

- Time Series Analysis- Concept of Algorithms