Senior Software Engineer

Role

Experience

Location

Notice Period

Key Responsibilities:

• Model Development

  : Design, develop, and implement machine learning models for various applications, ensuring they are impactful and solve real-world business challenges.

• Algorithm Selection

  : Choose and optimize machine learning algorithms and libraries (e.g., TensorFlow, PyTorch) based on project needs.

• Model Integration

  : Seamlessly integrate machine learning models into existing production systems.

• ML Pipeline Development

  : Build and maintain scalable ML pipelines for training, deployment, and monitoring.

• Model Monitoring

  : Continuously monitor model performance and proactively address any issues or improvements.

• Collaboration

  : Work closely with data scientists, engineers, and other stakeholders to translate business requirements into technical solutions.

• Continuous Learning

  : Stay current on the latest advancements in machine learning, contributing to innovation and the overall success of the team.

• Production Deployment

  : Leverage experience in deploying machine learning models into production environments, ensuring high reliability and efficiency.

• Azure Expertise

  : Be proficient with the Azure ecosystem, ensuring smooth deployment and management of models.

Required Skills:

• Programming Languages

  : Strong proficiency in

  Python

  and

  SQL

  .

• ML Tools and Frameworks

  : Experience with

  Databricks

  ,

  TensorFlow

  , and

  PyTorch

  .

• Cloud Experience

  : In-depth knowledge of

  Azure

  and the Azure ML platform.

• Machine Learning

  : Expertise in machine learning models, pipelines, and deployment strategies.

• AI Techniques

  : Familiarity with

  NLP

  (Natural Language Processing) and

  Generative AI

  techniques (experience with these will be a plus).

• Collaboration

  : Ability to collaborate effectively with data scientists and software engineers.

Qualifications:

• A degree in a relevant field (Computer Science, Engineering, or related fields).

• Experience

  : Minimum 5-10 years of experience in machine learning engineering, with a proven track record in deploying models to production.

• Certifications

  : Relevant certifications (e.g., Azure, Machine Learning) are a plus.