Job Description

Junior Machine Learning Engineer Role
Key Responsibilities:

• Machine Learning Development Support: Assist in designing, developing and deploying ML models and algorithms under the guidance of senior engineers, to tackle client challenges across banking, legal and related sectors.
• Cloud & MLOps Support: Help implement ML solutions on AWS (with emphasis on Amazon SageMaker). Contribute to building and maintaining CI/CD pipelines using infrastructure-as-code tools such as CloudFormation and Terraform to automate model training and deployment.
• Algorithm Implementation & Testing: Write clean, efficient Python code to implement ML algorithms and data pipelines. Conduct experiments, evaluate model performance (e.g. accuracy, precision, recall) and document results.
• Collaboration & Communication: Work closely with data scientists, ML engineers and DevOps teams to integrate models into production. Participate in sprint meetings and client calls, conveying technical updates in clear, concise terms.
• Quality, Documentation & Compliance: Maintain thorough documentation of data preprocessing steps, model parameters and deployment workflows. Follow data security best practices and ensure compliance with confidentiality requirements for financial and legal data.

• Education: Bachelor's degree in Computer Science, Engineering, Data Science or a closely related discipline.
• Experience: 0-2 years of practical exposure to machine learning or software development--this may include internships, academic projects or early professional roles.
• Programming & ML Skills: Proficiency in Python (including pandas, NumPy, scikit-learn). Basic understanding of ML concepts and model evaluation techniques.
• Cloud & DevOps Familiarity: Hands-on coursework or project experience with AWS (preferably SageMaker). Awareness of CI/CD principles and infrastructure-as-code tools (CloudFormation, Terraform).
• Hybrid Work Skills: Comfortable operating in a hybrid environment--able to collaborate effectively onsite in Chennai and maintain productivity when working remotely.
• Soft Skills: Strong analytical thinking, problem-solving aptitude and clear written/verbal communication. Demonstrated ability to learn quickly and work in a client-focused setting.