Ml Engineer

Who are we
Fulcrum Digital is an agile and nextgeneration digital accelerating company providing digital transformation and technology services right from ideation to implementation. These services have applicability across a variety of industries including banking & financial services insurance retail higher education food healthcare and manufacturing.

The Role

Machine Learning engineers design implement and optimize algorithms enabling computers to learn from data. They collaborate with data scientists preprocess datasets and choose suitable algorithms. Proficient in programming languages and frameworks they validate models deploy them and optimize for efficiency. Staying updated on AI advancements ML engineers contribute to the evolving landscape of intelligent systems.

Skills Requirements

Mandatory Skillset

Python Java R and Vertex AI. Indepth knowledge of machine learning frameworks like Keras or PyTorch.

Familiarity with data structures data modelling and software architecture

Secondary Skillset

Familiarity with Linux

Requirements

• Able to design and develop machine learning algorithms and deep learning applications and systems
  
• Able to analyse the ML algorithms that could be used to solve a given problem and ranking them by their success probability
  
• Able to solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks
  
• Able to collaborate with data scientists administrators data analysts data engineers and data architects on production systems and applications
  
• Able to Identify differences in data distribution that could potentially affect model performance in realworld applications
  
• Ensure algorithms generate accurate user recommendations
  
• Stay up to date with developments in the machine learning industry
  
• Study and transform data science prototypes and apply appropriate machine learning algorithms and tools
  
• Able to run machine learning tests and experiments and document findings and results
  
• Able to train retrain and monitor machine learning systems and models as needed
  
• Able to construct optimised data pipelines to feed machine learning models
  
• Able to consult with managers to determine and refine machine learning objectives
  
• Able to extend existing machine learning libraries and frameworks
  
• Exploring and visualising data to gain an understanding of it then identifying differences in data distribution that could affect performance when deploying the model in the real world

Skills Requirements Mandatory Skillset Python, Java, R and Vertex AI. In-depth knowledge of machine learning frameworks, like Keras or PyTorch. Familiarity with data structures, data modeling, and software architecture Secondary Skillset Familiarity with Linux