ML Engineer

This role is for one of our clients

Industry: Technology, Information and Media

Seniority level: Associate level

Min Experience: 3 years

Location: Gurugram, Delhi, Uttar Pradesh, NCR, NOIDA, Kanpur, Uttarakhand

JobType: full-time

We’re looking for a Machine Learning Engineer (3–5 years experience) who is passionate about turning complex data into intelligent, scalable solutions. In this role, you’ll design and deploy machine learning models, optimize algorithms for performance, and collaborate with cross-functional teams to bring AI-powered applications into production. If you thrive in solving challenging problems with real-world impact, this role is for you.

What You’ll Do

Model Design & Deployment
Build and deploy machine learning models that solve business-critical problems.

Implement and optimize classification, regression, clustering, and anomaly detection techniques.

Ensure models are scalable, efficient, and production-ready.

Data Preparation & Feature Engineering
Work with structured and unstructured datasets, ensuring quality and usability.

Apply feature engineering, dimensionality reduction, and transformation techniques.

Perform exploratory data analysis (EDA) to uncover patterns and insights.

Algorithm Optimization
Experiment with a range of ML techniques — from Support Vector Machines to ensemble methods and deep learning.

Fine-tune hyperparameters, validate models, and optimize performance.

Apply cross-validation, regularization, and advanced optimization strategies.

Collaboration & Integration
Work closely with data scientists, engineers, and product teams to embed ML models into real-world applications.

Develop APIs and reusable frameworks to simplify model deployment.

Communicate findings and translate model outputs into actionable insights.

Innovation & Growth
Stay ahead of the curve on ML, AI, and deep learning advancements.

Propose and implement new approaches to enhance system accuracy and efficiency.

Contribute to building a strong foundation of reusable ML tools and best practices.

What You’ll Bring

Education: Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field.

Experience: 3–5 years in ML engineering, with hands-on model development and deployment.

Core Skills:
Strong experience with Support Vector Machines (SVM) and other supervised/unsupervised methods.

Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).

Knowledge of statistics, probability, linear algebra, and optimization techniques.

Tools & Platforms:
Data visualization (Matplotlib, Seaborn, Plotly).

Version control (Git).

Cloud platforms (AWS, Azure, or GCP).

Soft Skills: Analytical mindset, problem-solving, clear communication, and team collaboration.

Bonus Points If You Have

Experience in deep learning (CNNs, RNNs, Transformers).

Exposure to NLP or computer vision projects.

Familiarity with large-scale data processing frameworks (Spark, Hadoop).