MLOps Engineer

3 weeks ago


Pune, Maharashtra, India TWise Full time

Responsibilities :

1. Lead Machine Learning Projects: Take ownership of end-to-end machine learning projects, from problem definition and data collection to model development and deployment.

2. Team Leadership: Mentor and guide a team of machine learning engineers, providing technical expertise and leadership to ensure project success.

3. Algorithm Development: Develop and optimize machine learning algorithms and models, leveraging techniques such as deep learning, natural language processing, computer vision, and reinforcement learning.

4. Data Preparation: Clean, pre-process, and transform large datasets to create high-quality training data for machine learning models.

5. Model Evaluation: Implement rigorous testing and validation procedures to ensure the performance, accuracy, and scalability of machine learning models.

6. Deployment and Integration: Collaborate with cross-functional teams to deploy machine learning models into production environments and integrate them with existing systems.

7. Research and Innovation: Stay up-to-date with the latest advancements in machine learning and AI research, and apply innovative solutions to business problems.

8. Documentation: Maintain detailed documentation of models, algorithms, and processes to facilitate knowledge sharing within the team and organization.

9. Collaboration: Collaborate with data scientists, data engineers, and other stakeholders to drive the adoption of machine learning across the organization.

Qualifications :

1. Minimum of 4 years of hands-on experience in machine learning, deep learning, and artificial intelligence.

2. Strong programming skills in languages such as Advanced Python

3. Proficiency in data pre-processing, feature engineering, and model evaluation.

4. Proven experience ML Flow, CICD, Docker, Kubernetes, Continuous Integration, Deployment, Git actions, ML Studio, Pipeline Azure Databricks, Azure ML Studio, DevOps, Terraform

5. Statistics and machine learning knowledge

6. Azure ML is must and good to go

7. Standardize and streamline prototype machine learning code

8. Building MLOps pipelines. Building to serve data and models

If you are a seasoned machine learning engineer with a passion dashboard for solving complex problems using cutting-edge technologies, we encourage you to apply. Join our dynamic team and play a pivotal role in advancing our AI and ML initiatives.

(ref:hirist.tech)

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