Lead-ML Engineer

Egen; Hyderabad; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Egen is seeking a highly motivated and experienced Lead ML Engineer to join our growing ML/GenAI team in Hyderabad, India. You will take ownership of designing, developing, and productionalizing ML applications, focusing on collaboration with engineers and stakeholders for successful project delivery.

The ideal candidate must have at least 5 years of experience in ML/AI applications, and 8 years in software engineering. Proficiency in cloud platforms like Google Cloud is essential, along with strong skills in Python and ML libraries.

Qualifications

• At least 5 years of experience in ML/AI application design & development.
• 8 years of experience in software engineering for secure and scalable applications.
• Leadership experience with ML/data science teams.

Responsibilities

• Design and develop ML/GenAI applications.
• Lead project ownership from conception to deployment.
• Collaborate with engineers and stakeholders.

Skills

Machine Learning

Software Engineering

Leadership and Mentoring

Python

Natural Language Processing

Computer Vision

Cloud Platforms

Education

Master’s degree in Statistics, Machine Learning or related fields

Tools

Google Cloud

TensorFlow

PyTorch

Scikit-learn

XGboost

LangChain

Numpy

Pandas

Job description

Job Description :

We are seeking a highly motivated and experienced Lead ML Engineer to join our growing ML/GenAI team.

You will play a key role in designing, developing and productionalizing ML/GenAI applications by evaluating models, training and/or fine tuning them. As a lead, you require a deep understanding of both machine learning algorithms and software architecture. You need to take ownership of projects from conception to deployment, collaborating with engineers and stakeholders to ensure successful project delivery.

What we’re looking for

• At least 5 years of experience in designing & building ML/AI applications for customer and deploying them into production
• At least 8 years of Software engineering experience in building Secure, scalable and performant applications for customers.
• At least 2 years of experience leading and mentoring ML/data science teams( 4+ team members)
• 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.
• Lead the end-to-end design and architecture of scalable, reliable, and cost-effective Generative AI solutions. This includes designing RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and model fine-tuning strategies.
• Hands on customer experience with RAG solution or fine tuning of LLM model.
• Build and deploy scalable machine learning pipelines on Google Cloud or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.
• Experience working with the end-to-end steps involving but not limited to 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.
• Act as the senior-most developer, writing clean, high-quality, and scalable code. This includes building core components for prompt engineering, vector search, data processing, model evaluation, and inference serving.
• 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

Good to Have

• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.
• Experience of working with one or more public cloud platforms - namely Google Cloud, AWS or Azure.
• Experience with AutoML and vision techniques.
• Master’s degree in statistics, machine learning or related fields.