Hybrid ML Engineer

at Egen

• Job title: ML Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Google Cloud Platform, Numpy, Pandas, Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Hyderabad, India

About the role

• ML Engineer designing and building AI applications for customers in production environments. Collaborating with data scientists and engineers to operationalize ML models with a hybrid work environment.

Responsibilities

• Design, develop, and operationalize existing ML models by fine tuning, personalizing it.
• Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.
• Experience working with the end-to-end steps involving data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.
• Evaluate machine learning models and perform necessary tuning.
• Develop prompts that instruct LLM to generate relevant and accurate responses.
• Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.
• Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.
• Hands on customer experience with RAG solution or fine tuning of LLM model.

Requirements

• At least 5 years of experience in designing & building AI applications for customer and deploying them into production.
• Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.
• Design, develop, and operationalize existing ML models by fine tuning, personalizing it.
• Evaluate machine learning models and perform necessary tuning.
• Develop prompts that instruct LLM to generate relevant and accurate responses.
• Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.
• Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.
• Hands on customer experience with RAG solution or fine tuning of LLM model.
• Proven experience building and deploying machine learning models in production environments for real life applications.
• Good understanding of natural language processing, computer vision or other deep learning techniques.
• Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).
• Familiarity with Google Cloud or any other Cloud Platform and its machine learning services.
• Excellent communication, collaboration, and problem-solving skills.
• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent (Good to Have).
• Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure (Good to Have).
• Experience with AutoML and vision techniques (Good to Have).
• Master’s degree in statistics, machine learning or related fields (Good to Have).