Machine Learning Engineer – AI/ML

Title: Machine Learning Engineer

Location: Gurgaon, Haryana (Onsite/Hybrid)

Experience

• 4-6 years of hands-on experience in Machine Learning Engineering, Applied Machine Learning, or related roles.
• Experience with Pandas, NumPy, Scikit-learn, and related Python libraries.
• Hands-on experience with Large Language Models (LLMs).
• Strong proficiency in Python.

About the Role

We are seeking a highly motivated

Machine Learning Engineer

with 4–6 years of experience to design, build, deploy, and optimize scalable machine learning solutions that solve real-world business problems. The ideal candidate has hands-on experience in developing production-grade ML models, implementing MLOps best practices, and collaborating with cross-functional teams to deliver AI-driven products.

Key Responsibilities

Machine Learning Development

• Design, develop, train, and optimize Machine Learning and Deep Learning models for classification, regression, forecasting, NLP, and computer vision applications.
• Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
• Conduct experiments and improve model accuracy, scalability, and reliability.

Model Deployment & MLOps

• Deploy, monitor, and maintain ML models in production environments.
• Build and manage end-to-end ML pipelines using MLOps best practices.
• Implement CI/CD workflows for machine learning applications.
• Containerize applications using Docker and orchestrate deployments with Kubernetes.

Data Engineering & Processing

• Work with structured and unstructured datasets to build scalable data pipelines.
• Process and analyze large datasets using SQL and distributed data processing tools.
• Collaborate with data engineering teams to ensure high-quality data availability.

Cross-functional Collaboration

• Partner with Data Scientists, Product Managers, Backend Engineers, and Business stakeholders to understand requirements and deliver ML-powered solutions.
• Translate business challenges into scalable machine learning applications.

Model Monitoring & Optimization

• Monitor model performance, latency, drift, and reliability in production.
• Continuously improve deployed models through retraining and optimization.
• Implement logging, monitoring, and alerting mechanisms for ML systems.

Research & Innovation

• Stay updated with the latest advancements in Machine Learning, Deep Learning, Generative AI, and MLOps.
• Evaluate and integrate new frameworks, tools, and best practices into existing workflows.

Required Skills & Experience

• 4-6 years of hands-on experience in Machine Learning Engineering, Applied Machine Learning, or related roles.
• Strong proficiency in

Python

.

• experience with

Pandas, NumPy, Scikit-learn

, and related Python libraries.

• Hands-on experience with: TensorFlow, PyTorch, Keras, XGBoost.
• Practical experience with one or more cloud platforms: AWS, Google Cloud Platform (GCP), Microsoft Azure
• Experience with

Amazon SageMaker

,

Vertex AI

, or

Azure Machine Learning

is an added advantage.

• Experience with: Docker, Kubernetes, FastAPI or Flask, CI/CD pipelines for ML applications, Model versioning and deployment strategies.
• Strong knowledge of SQL and NoSQL databases.
• Familiarity with Apache Spark and Hadoop is preferred.
• Experience processing large-scale datasets.

Preferred Skills

• Hands-on experience with Large Language Models (LLMs).
• Experience using

LangChain

,

LlamaIndex

, or similar orchestration frameworks.

• Knowledge of Vector Databases such as

Pinecone

,

Weaviate

, or

Milvus

.

• Experience in NLP, Computer Vision, Recommendation Systems, or Generative AI applications.
• Familiarity with experimentation frameworks, A/B testing, and model evaluation methodologies.

Educational Qualification

• Bachelor's or Master's degree (B.Tech/M.Tech) in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.