MLOps Engineer

2 weeks ago

PuneNoidaGurgaonGurugramBangalore, India Pathways Consultant Full time

Role : ML Ops Engineer

Job Location : Pune, Bangalore, Gurgaon, Noida

Shift Timing : 12:30PM IST - 10:30 PM IST

Experience : 8+ years

Salary : 20 - 22 LPA

Notice Period : Early joiners required only ( 0 - 10 Days)


Job Description :

Skills/ Qualifications Required :


- Relevant experience in ML Engineering & ML Ops role with an end-to-end understanding of ML based project's solution designing, development, implementation & deployment

- Should fulfill all the standard MLOps level 2 requirements for CI/CD + CT pipeline automation

- Strong grasp & hands on experience with production ready scalable code using SQL (advance) and Python, along with an in-depth knowledge of Machine Learning concepts

- Hands-on experience in working on AWS cloud stack

- Working experience Sagemaker, EC2, S3, EMR, Lambda Functions, Cloudwatch, etc.

- At least 2 years of experience in orchestrating ML Jobs on Airflow, Step Functions, Model registry etc.

- Knowledge of Jenkins for CI/CD tool

- Good communication skills

- Experience with version control tools such as MLFlow, DVC, Pachyderm etc.

Good to have : Experience with Google Analytics data, PySpark

Job Responsibilities :

- Actively own & manage client deliverables.

- Collaborate with data scientists, data engineers, and other MLOps Engineers to solve complex problems and create unique solutions for MLOps

- Create ML prototypes, design ML systems, research, and implement ML algorithms, and develop machine learning applications in accordance with client needs.

- Should have implementation experience of model evaluation and model + data validation tools/ techniques such as schema validation, valuation metrics etc.

- Responsible for developing and deploying CI/CD based automated ML application pipelines (collection, processing, cleaning, transformation etc.) along with the CT component for continuous feedback loop for re-training

- Strong skills in Feature store setup, Pipeline Integration, Automated triggering, Model Continuous Delivery, Model Serving (via APIs) & Model Monitoring

- Ensure output's thorough quality check & provide analytics driven insights and next steps

- To perform statistical analysis and fine-tune models using test results.

- Understand data and different platforms used by the client.

- Actively contribute towards problem solving & mentor juniors in the team

- Can work hands-on independently

(ref:hirist.tech)

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