• We are seeking a Software Engineer – Machine Learning to design, develop, and deploy machine learning solutions that drive innovation and improve business processes.
• The ideal candidate will work closely with data scientists, engineers, and product teams to build scalable ML models, optimize performance, and integrate AI-driven solutions into production systems.

• Design, implement, and optimize machine learning models for real-world applications.
• Develop and maintain scalable ML pipelines for data preprocessing, model training, and deployment.
• Integrate machine learning models into production environments using APIs, cloud services, or edge devices.
• Collaborate with data scientists and engineers to improve model accuracy and efficiency.
• Work with big data technologies to process and analyze large-scale datasets.
• Monitor, debug, and optimize machine learning workflows for performance and reliability.
• Stay up to date with the latest advancements in AI/ML technologies and research.

Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3+ years of experience in software engineering, with at least 1+ year in machine learning development.

Technical Skills:

• Programming Languages: Proficiency in Python, Java, or C++ for ML development.
• Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Scikit-Learn, or XGBoost.
• Data Processing & Storage: Strong knowledge of SQL, Pandas, NumPy, and experience with big data tools like Apache Spark or Hadoop.
• Cloud Platforms: Experience with AWS, Google Cloud, or Azure for deploying ML models.
• MLOps & Deployment: Familiarity with Docker, Kubernetes, MLflow, or TensorFlow Serving.
• Software Engineering Best Practices: Knowledge of version control (Git), CI/CD pipelines, and API development (REST, GraphQL).

Soft Skills:

• Strong problem-solving skills and ability to optimize ML models for production.
• Ability to work in cross-functional teams and collaborate with researchers, engineers, and stakeholders.
• Excellent communication skills to explain ML concepts to both technical and non-technical teams.
• Self-motivated and eager to stay updated with emerging ML trends and technologies.

Preferred Qualifications:

• Experience with edge AI, reinforcement learning, or deep learning architectures.
• Knowledge of automated machine learning (AutoML) and hyperparameter tuning.
• Background in A/B testing, statistical modeling, and data-driven decision-making.
• Experience with Natural Language Processing (NLP) or Computer Vision applications.