Junior Machine Learning Engineer

Overview

Junior Machine Learning Engineer role within an Applied AI and Machine Learning delivery team, developing, testing, deploying and supporting AI and machine learning solutions under the guidance of senior engineers, data scientists and technical leads.

What you'll do

• Assist in collecting, cleaning, transforming, profiling and validating structured and unstructured data.
• Perform exploratory data analysis to identify patterns, anomalies, trends, data quality issues and potential features.
• Develop and evaluate baseline machine learning models under guidance using appropriate algorithms and metrics.
• Support use cases involving classification, regression, clustering, anomaly detection, forecasting, natural language processing and Generative AI.
• Write reusable, readable, secure and testable Python code aligned with team coding standards.
• Help convert notebooks and experiments into modular code, repeatable pipelines, APIs or scheduled workloads.
• Assist with feature engineering, model comparison, hyperparameter tuning, error analysis and experiment tracking.
• Support deployment of models through APIs, containers, batch jobs or approved cloud services.
• Help monitor model quality, data drift, model drift, latency, failures and operational performance.
• Participate in code reviews, pair programming, Agile ceremonies, technical discussions and knowledge-sharing sessions.
• Document datasets, experiments, assumptions, model results, dependencies, limitations and implementation decisions.
• Identify and escalate data privacy, security, compliance, responsible AI and model-performance risks.
• Write unit tests and data validation checks.
• Support logging, monitoring, troubleshooting and incident documentation.

What you'll need

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering or a related area.
• 0 to 2 years of relevant experience, including internships, academic projects, research, hackathons or personal projects.
• Working knowledge of Python and SQL.
• Understanding of statistics, probability, linear algebra, supervised learning and unsupervised learning.
• Ability to communicate technical findings clearly and work effectively in a collaborative Agile environment.
• Strong analytical, problem-solving, documentation and continuous-learning abilities.

Nice to have

• Exposure to Azure Machine Learning, Azure AI services or Azure AI Foundry.
• Familiarity with PyTorch, TensorFlow or similar frameworks.
• Exposure to Large Language Models, prompt engineering, embeddings, vector databases or retrieval-augmented generation.
• Familiarity with Claude Code, Codex or similar agents, used to speed up your own development and to deliver AI-native solutions, with the judgment to review and own what they produce.
• Familiarity with Docker, Kubernetes, REST APIs, Linux, GitHub and MLflow or similar experiment tracking.
• Awareness of responsible AI, privacy, explainability and AI governance.

Details

• Location: Hyderabad, Telangana, India.
• Selected candidates must complete the assigned role-specific learning plan, hands-on exercises, knowledge checks and readiness assessment before joining or deployment.
• Pre-joining capstone: build and demonstrate an end-to-end machine learning solution covering data preparation, model development, evaluation, packaging, documentation and basic deployment or inference.