Machine Learning Engineer

Job Title: Machine Learning Engineer

Location: Mohali

About the Role:

We are looking for a Machine Learning Engineer who can design, build, and deploy scalable machine learning models and solutions. The ideal candidate should have strong programming skills, experience with ML frameworks, and a solid understanding of data science concepts.

Key Responsibilities:

• Design, develop, and implement machine learning models and algorithms.
• Work with large datasets to clean, preprocess, and analyze data.
• Optimize and fine-tune models for performance and scalability.
• Collaborate with data scientists, engineers, and product teams to integrate ML models into production.
• Monitor, maintain, and improve deployed models.
• Research and experiment with new machine learning techniques and tools.
• Build pipelines for automated data processing and model training.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field.
• Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn, etc.).
• Solid understanding of machine learning, deep learning, and statistical modeling.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Knowledge of SQL and working with large datasets.
• Experience with cloud platforms (AWS, GCP, Azure) is a plus.
• Strong problem-solving and analytical skills.

Preferred Qualifications (Good to Have):

• Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).
• Familiarity with natural language processing (NLP) or computer vision.
• Contributions to open-source ML projects or research publications.

Benefits:

• Competitive salary and performance-based incentives.
• Opportunity to work on cutting-edge AI/ML projects.
• Professional development and continuous learning support.
• Friendly and collaborative work culture.

Job Types: Full-time, Permanent

Education:

• Bachelor's (Preferred)

Experience:

• ML: 1 year (Preferred)

Location:

• Mohali, Punjab (Preferred)

Work Location: In person