ML Engineer

What you'll do

• As an ML Engineer, you will develop solutions to interesting technical problems, explore exciting growth opportunities, and have a real impact on our product.
• To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.

Responsibilities:

• Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
• Transforming data science prototypes and applying appropriate ML algorithms and tools.
• Solving complex problems with multi-layered data sets and optimizing existing machine learning libraries and frameworks.
• Developing ML algorithms to analyze huge volumes of historical data to make predictions.
• Running tests, performing statistical analysis, and interpreting test results.
• Exposure to generative AI (LLM) based ML architectures
• Experienced in working with CNN.
• Knows how to train and fine-tune CNN-based models.
• Documenting machine learning processes.

Requirements:

• 1+ years of relevant experience in Machine Learning Engineering.
• Advanced proficiency with Python.
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• Superb analytical and problem-solving abilities.
• Great communication and collaboration skills.

Preferences:

• Start-up experience is good to have.
• Willing to join immediately, ideally.
• Female candidates are preferred

Interview Process -

• Technical Round 1 - ML Fundamentals, NLP models
• Assessment
• Technical Round 2 - Discussion on the assignment submitted modify it according to the requirements
• Round 3 - with the Tech Lead - Tech Managerial - Past projects in-depth knowledge of ML