Machine learning Engineer

This role is for one of the Weekday's clientsMin 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.