Machine learning Engineer

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.

• 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.