Machine Learning Engineer

Job Title: Machine Learning Engineer

Location: Mumbai

Experience Level: 3-5 years

Job Type: Full-time

Company Overview:

Siclarity is a leading technology company specializing in AI/ML-based software solutions for semiconductor chip design industry. We develop cutting-edge products that leverage artificial intelligence and machine learning to solve complex problems across the Electronic Design Automation (EDA) space. Our team is passionate about innovation and committed to delivering high-quality solutions to our clients.

Job Description:

We are looking for a skilled and motivated Machine Learning Engineer to join our team. The ideal candidate will have experience in building, deploying, and optimizing machine learning models, particularly for classification and regression tasks. You should be well-versed in a range of machine learning and deep learning algorithms, including Mixture of Experts, Graph Neural Networks (GNNs), Autoencoders, Random Forests, Support Vector Machines (SVMs), and Gradient Boosting techniques.

As a Machine Learning Engineer, you will work closely with data scientists, software engineers, and product teams to develop solutions that drive impactful business outcomes. You should be comfortable working in a fast-paced environment, with a passion for innovation and a keen interest in solving complex problems using state-of-the-art ML and DL techniques.

Responsibilities

- Develop, train, and deploy machine learning models for classification and regression projects.

- Implement and optimize advanced algorithms, including Mixture of Experts, Graph Neural Networks (GNNs), Autoencoders, SVMs, Random Forests, and Gradient Boosting models.

- Perform data preprocessing, feature engineering, and model tuning to improve model performance and robustness.

- Collaborate with cross-functional teams to understand business requirements and deliver ML-driven solutions.

- Evaluate and monitor model performance and maintain scalability of deployed models.

- Contribute to the development of ML pipelines, ensuring efficiency, scalability, and reliability.

- Stay up-to-date with the latest advancements in machine learning and deep learning, and apply best practices to ongoing projects.

Requirements

- 3-5 years of experience in machine learning and deep learning, with a track record of successful classification and regression projects.

- Proficiency in Python and popular ML/DL libraries (e.g., TensorFlow, PyTorch, scikit-learn).

- Strong knowledge of machine learning algorithms, including Autoencoders, Mixture of Experts, GNNs, Random Forests, SVMs, and Gradient Boosting.

- Hands-on experience in data preprocessing, feature engineering, and model evaluation techniques.

- Experience in building and deploying MLOps pipelines using tools like MLflow, Kubeflow, Airflow, or similar frameworks.

- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (e.g., Docker) is a plus.

- Strong analytical and problem-solving skills, with the ability to translate complex requirements into practical ML solutions.

- Effective communication and collaboration skills.

Preferred Qualifications

- Bachelors / masters degree in computer science, Engineering, Machine Learning, Statistics, or a related field.

- Experience in model deployment and monitoring in production environments.

- Knowledge of big data tools and frameworks (e.g., Hadoop, Spark) is a plus.

- Familiarity with modern tools for experiment tracking and model versioning (e.g., MLflow, DVC).

Why Join Us?

- Be part of a dynamic team that fosters innovation and cutting-edge research in machine learning.

- Opportunity to work on challenging ML projects and contribute to impactful solutions.

- Collaborative work culture with opportunities for growth and professional development.

If youre passionate about machine learning, eager to work with advanced models like Mixture of Experts, GNNs, and Autoencoders, and want to make a real impact, we’d love to hear from you!