Machine Learning Engineer

Job Summary

We are looking for a skilled Machine Learning Engineer to design, develop, and deploy scalable machine learning models and AI-driven solutions. The ideal candidate will have experience in building end-to-end ML pipelines, working with large datasets, deploying models into production, and collaborating with cross-functional teams to solve real-world business problems.

Key Responsibilities

• Design, develop, and deploy machine learning models for predictive analytics and intelligent automation.
• Build and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Work closely with data scientists, software engineers, and business stakeholders to understand requirements and translate them into ML solutions.
• Develop and optimize supervised, unsupervised, and deep learning models.
• Deploy machine learning models using cloud platforms and MLOps best practices.
• Monitor model performance, retrain models as needed, and ensure production reliability.
• Build REST APIs or microservices to serve machine learning models.
• Perform data analysis and feature engineering to improve model accuracy.
• Document technical designs, model performance metrics, and deployment processes.
• Stay updated with the latest advancements in Machine Learning, AI, and Generative AI technologies.

Required Skills

• Strong programming experience in Python.
• Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Experience with data manipulation using Pandas, NumPy, and SQL.
• Knowledge of supervised and unsupervised learning algorithms.
• Experience in feature engineering, model evaluation, and hyperparameter tuning.
• Familiarity with deep learning concepts and neural networks.
• Experience deploying ML models using FastAPI, Flask, or similar frameworks.
• Understanding of MLOps concepts, including model versioning, monitoring, and CI/CD.
• Experience with Git and version control.
• Strong analytical, problem-solving, and communication skills.

Preferred Skills

• Experience with Generative AI, Large Language Models (LLMs), or Retrieval-Augmented Generation (RAG).
• Knowledge of LangChain, LlamaIndex, or similar AI orchestration frameworks.
• Experience with vector databases such as Pinecone, FAISS, Milvus, or ChromaDB.
• Familiarity with NLP, Computer Vision, or Time Series forecasting.
• Experience with Docker and Kubernetes.
• Exposure to Apache Spark or distributed data processing frameworks.
• Experience with MLflow, Kubeflow, or similar MLOps tools.

Cloud & Tools

• Python
• SQL
• Scikit-learn
• TensorFlow / PyTorch
• Pandas
• NumPy
• FastAPI / Flask
• Git
• Docker
• Kubernetes
• MLflow
• Azure ML / AWS SageMaker / Google Vertex AI
• Databricks (Preferred)

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
• Relevant certifications in Machine Learning or Cloud platforms are a plus.

Preferred Experience

• 4-8 years of experience in Machine Learning or AI application development.
• Experience building and deploying production-grade ML models.
• Hands-on experience with cloud-based ML services.
• Experience working in Agile/Scrum development environments.

Nice to Have

• Experience with recommendation systems, fraud detection, forecasting, or predictive analytics.
• Knowledge of data engineering concepts and ETL pipelines.
• Experience integrating ML models with enterprise applications through REST APIs.
• Contributions to open-source ML projects or published research in AI/ML.

What We Offer

• Opportunity to work on cutting-edge AI and Machine Learning projects.
• Collaborative and innovative work environment.
• Career growth and learning opportunities.
• Competitive salary and comprehensive benefits.
• Flexible work arrangements (Remote/Hybrid, based on business needs).