Machine Learning Engineer Jobs for 0 to 10 years experience

Machine Learning Engineer (Fresher / Experienced)

Job Location

Bangalore / Hyderabad / Pune / Chennai / Noida / Gurugram (Hybrid / Work From Office / Remote)

Employment Type

• Full-Time
• Permanent

Experience

• Fresher (0 Years)
• 1–8 Years (Experienced)

Salary

• Fresher: ₹4 – ₹8 LPA
• 1–3 Years: ₹8 – ₹15 LPA
• 3–5 Years: ₹15 – ₹25 LPA
• 5–8 Years: ₹25 – ₹40 LPA

Job Summary

We are seeking passionate Machine Learning Engineers to design, build, deploy, and optimize intelligent machine learning solutions for real-world business problems. The ideal candidate should have strong programming skills, a solid understanding of machine learning algorithms, data processing, and model deployment. Fresh graduates with strong academic projects and experienced professionals are both encouraged to apply.

Key Responsibilities

• Design, develop, and deploy Machine Learning models.
• Analyze structured and unstructured datasets.
• Build predictive analytics and recommendation systems.
• Train, evaluate, and optimize ML models.
• Perform feature engineering and data preprocessing.
• Develop classification, regression, and clustering models.
• Deploy ML models using REST APIs.
• Monitor model performance and retrain when required.
• Collaborate with Data Scientists and Software Engineers.
• Build scalable ML pipelines.
• Optimize algorithms for speed and accuracy.
• Work on AI-powered automation solutions.
• Document ML workflows and model performance.
• Stay updated with the latest Machine Learning research and technologies.

Required Skills

Programming Languages

• Python
• SQL
• Java (Preferred)
• Scala (Optional)

Machine Learning

• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning (Preferred)
• Deep Learning
• Transfer Learning
• Ensemble Learning
• Feature Engineering
• Model Evaluation
• Hyperparameter Tuning

Libraries & Frameworks

• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM
• Keras
• NumPy
• Pandas

Data Engineering

• Data Cleaning
• Data Transformation
• ETL Basics
• Feature Selection
• Data Visualization

Databases

• MySQL
• PostgreSQL
• MongoDB
• Redis

Big Data (Preferred)

• Apache Spark
• Hadoop
• Kafka

Cloud Platforms

• AWS SageMaker
• Microsoft Azure ML
• Google Vertex AI

DevOps

• Git
• Docker
• Kubernetes
• CI/CD

Preferred Skills

• Natural Language Processing (NLP)
• Computer Vision
• Time Series Forecasting
• Recommendation Systems
• Anomaly Detection
• MLOps
• Model Monitoring
• Model Explainability
• ML Pipelines
• API Development
• FastAPI
• Flask

Educational Qualification

• B.E. / B.Tech
• M.Tech
• MCA
• M.Sc (Computer Science / AI / Data Science / Statistics)
• BCA
• B.Sc Computer Science
• Mathematics / Statistics Graduates with ML knowledge

Freshers with Machine Learning projects are encouraged to apply.

Freshers Should Have

• Strong Python Programming
• Data Structures & Algorithms
• Mathematics & Statistics
• Machine Learning Fundamentals
• SQL Knowledge
• Data Visualization
• Git & GitHub
• Kaggle Projects (Preferred)
• Internship in AI/ML (Preferred)

Experience Requirements

Candidates should have experience in one or more of the following:

• Machine Learning model development
• Predictive Analytics
• Recommendation Engines
• Fraud Detection Systems
• Demand Forecasting
• Computer Vision applications
• NLP solutions
• MLOps
• Cloud ML deployment
• Model optimization

Good to Have

• Generative AI
• Large Language Models (LLMs)
• LangChain
• Hugging Face Transformers
• OpenAI API
• Vector Databases
• Pinecone
• ChromaDB
• MLflow
• Airflow
• Streamlit
• Gradio

Soft Skills

• Analytical Thinking
• Problem Solving
• Communication Skills
• Team Collaboration
• Attention to Detail
• Continuous Learning
• Innovation
• Time Management

Interview Process

1. Resume Screening
2. Online Aptitude & Coding Assessment
3. Machine Learning Technical Test
4. Python Coding Round
5. Technical Interview
6. Managerial Discussion
7. HR Discussion
8. Offer Release

Key Skills

Machine Learning, Machine Learning Engineer, Python, TensorFlow, PyTorch, Scikit-learn, Deep Learning, Artificial Intelligence, Predictive Analytics, NLP, Computer Vision, Feature Engineering, Model Deployment, MLOps, SQL, Data Science, AWS SageMaker, Azure ML, Google Vertex AI, Docker, Kubernetes, Git, MLflow, FastAPI, Flask, XGBoost, Pandas, NumPy.