Machine Learning Engineer

3 weeks ago

Gurgaon, Haryana, India TWise Full time

We are seeking a talented and accomplished Machine Learning Engineer with expertise in Azure and Databricks.

The ideal candidate will have a strong foundation in machine learning, deep learning, and artificial intelligence, with a proven track record of developing and deploying models in real-world applications.

This role requires hands-on experience with machine learning frameworks, cloud platforms, and DevOps practices.

Key Responsibilities :

1. Lead Machine Learning Projects :

Take full ownership of machine learning projects from start to finish, including problem definition, data collection, model development, and deployment.

2. Algorithm Development :

Develop and optimize machine learning algorithms using techniques such as deep learning, natural language processing, computer vision, and reinforcement learning.

3. Data Preparation:

Pre-process and transform large datasets to create high-quality training data for model development.

4. Model Evaluation:

Implement testing and validation procedures to ensure the performance, accuracy, and scalability of machine learning models.

BIZ-METRIC

5. Deployment and Integration :

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

6. Collaboration with DevOps Team :

Work closely with the DevOps team, having a basic understanding of version control systems (Git), CI/CD pipelines, and tools like Terraform.

Required Skills :

- Python DS | DE | ETL: Minimum of 2 years of hands-on experience.

- Advanced Python: Proven hands-on experience in advanced Python coding and libraries.

- Machine Learning: Experience in developing machine learning models and deploying them in production.

- ML Frameworks: Familiarity with tools like Scikit-learn, TensorFlow, or PyTorch.

- Azure Cloud: Strong experience working on Azure cloud services and tools.

- Databricks: Experience with Databricks for big data processing and machine learning pipelines.

- DevOps Knowledge: Basic understanding of DevOps practices, CI/CD pipelines, and version control.

- Deep Learning: Understanding of deep learning principles and techniques.

- NLP & Computer Vision: Basic understanding of Natural Language Processing (NLP) and Computer Vision.

- Python for Image Processing: Experience or understanding of image processing libraries like OpenCV.

(ref:hirist.tech)

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