 
						Machine learning Engineer
4 weeks ago
This role is for one of the Weekday's clients
Min Experience: 3 years  
Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand
JobType: full-time
We are seeking a highly skilled and motivated Machine Learning Engineer   with 3–5 years of hands-on experience to join our growing team. The ideal candidate will have strong expertise in designing, developing, and deploying machine learning models, with a particular focus on Support Vector Machines (SVM)   and other supervised and unsupervised learning techniques. This role involves working on large-scale datasets, building predictive models, optimizing algorithms, and collaborating with cross-functional teams to deliver cutting-edge AI-driven solutions.  
Requirements
Key Responsibilities-  Model Development & Deployment:     - Design, build, and deploy machine learning models tailored to real-world business problems.
- Implement and optimize Support Vector Machine (SVM) algorithms for classification, regression, and anomaly detection tasks.
- Ensure scalability and performance of deployed models in production environments.
 
-  Data Management & Preprocessing:     - Work with structured and unstructured datasets to prepare clean, usable data for training.
- Apply feature engineering, dimensionality reduction, and data transformation techniques to improve model accuracy and efficiency.
- Conduct exploratory data analysis (EDA) to identify patterns, trends, and data insights.
 
-  Algorithm Optimization:     - Experiment with various machine learning algorithms beyond SVM, including decision trees, ensemble methods, clustering, and neural networks.
- Fine-tune hyperparameters, optimize model performance, and validate results using rigorous statistical methods.
- Leverage techniques such as cross-validation, regularization, and kernel methods to enhance accuracy.
 
-  Collaboration & Integration:     - Partner with data scientists, software engineers, and product teams to integrate machine learning solutions into business applications.
- Translate complex machine learning outputs into actionable insights for stakeholders.
- Support the creation of APIs and frameworks for easy deployment of ML models.
 
-  Continuous Improvement:     - Stay updated with the latest advancements in machine learning, deep learning, and AI research .
- Explore novel approaches to enhance existing systems and processes.
- Contribute to building reusable ML components and maintaining best practices.
 
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
- Experience: 3–5 years of professional experience in machine learning engineering.
-  Core Expertise:     - Strong understanding and practical experience with Support Vector Machines (SVM) .
- Solid knowledge of supervised and unsupervised learning techniques, classification, regression, and clustering.
 
-  Programming & Tools:     - Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.).
- Experience with data visualization tools (Matplotlib, Seaborn, Plotly).
- Familiarity with version control systems (Git) and cloud platforms (AWS, Azure, or GCP).
 
- Analytical Skills: Strong background in statistics, linear algebra, probability, and optimization techniques.
- Soft Skills: Excellent problem-solving abilities, analytical thinking, communication, and teamwork.
- Experience with deep learning frameworks.
- Exposure to natural language processing (NLP) or computer vision projects.
- Familiarity with large-scale data processing frameworks like Spark or Hadoop.
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