AI/ML Engineer

Company Description

HMG Technologies is a leading provider of cutting-edge technologies and services, offering scalable solutions for companies of all sizes. We build our solutions by listening to our clients and understanding their needs, ensuring our products exceed expectations. Our expertise lies in analyzing information and customizing offerings to adapt to changing market demands. We are dedicated to designing and providing tailored solutions to meet any requirements.

Role Description

This is a full-time role for an AI/ML Engineer, with expertise in LLM, Azure, Python & PySpark, located on-site in Bengaluru. The AI/ML Engineer will be responsible for designing and implementing machine learning models, deploying solutions using Azure, writing efficient code in Python and PySpark, and conducting regular evaluations of model performance. The engineer will collaborate with data scientists and other team members to apply machine learning techniques to solve complex problems in various domains.

Key Responsibilities:

Artificial Intelligence (AI) & Machine Learning (ML):

Design, develop, and optimize machine learning and AI models to solve business problems.

Perform exploratory data analysis and feature engineering for model development.

Use supervised, unsupervised, and reinforcement learning techniques where appropriate.

Build AI pipelines and integrate models into production systems.

Large Language Models (LLM):

Fine-tune and deploy LLMs (e.g., OpenAI, Hugging Face, or custom-trained models).

Develop prompt engineering strategies for LLM applications.

Implement RAG (Retrieval-Augmented Generation) systems or LLMOps workflows.

Evaluate LLM outputs for accuracy, bias, and performance.

Python Programming:

Write efficient, reusable, and testable Python code for data processing, modeling, and API services.

Build automation scripts for data pipelines and model training workflows.

Use popular libraries such as Scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy.

PySpark and Big Data:

Work with large datasets using PySpark for data wrangling, transformation, and feature extraction.

Optimize Spark jobs for performance and scalability.

Collaborate with data engineering teams to implement end-to-end data pipelines.

Microsoft Azure:

Deploy models and applications using Azure ML, Azure Databricks, Azure Functions, and Azure Synapse.

Manage compute resources, storage, and data security on Azure.

Use Azure DevOps for CI/CD of ML pipelines and automation.

Cross-Functional Collaboration & Documentation:

Collaborate with data engineers, product managers, and business stakeholders to align technical solutions with business needs.

Maintain clear documentation of models, code, and workflows.

Present technical findings and model outcomes to both technical and non-technical audiences.

Required Skills & Qualifications:

Bachelor's or Masters degree in Computer Science, Data Science, Engineering, or a related field.

3+ years of experience in AI/ML and data engineering roles.

Proficient in Python and PySpark.

Experience with cloud platforms, especially Microsoft Azure.

Hands-on experience with LLMs (e.g., GPT, BERT, Claude, etc.).

Familiarity with ML frameworks like Scikit-learn, TensorFlow, or PyTorch.

Solid understanding of ML lifecycle, MLOps, and deployment strategies.

Nice to Have:

Experience with LLMOps and vector databases (e.g., FAISS, Pinecone).

Knowledge of data governance and responsible AI practices.

Azure certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate).

• Experience with REST APIs and containerization (Docker, Kubernetes).