Contribute to the design, development, and maintenance of software components across the AI product stack.
Implement clean, efficient, and well-tested code following team best practices.
Collaborate with UI/UX designers and product stakeholders to build user-friendly interfaces and features.
Support data ingestion, preprocessing and transformation tasks to prepare data for models.
Assist in building and integrating APIs and services consumed by ML and frontend components.
Participate in CI/CD pipeline activities and help automate build, test and deployment steps.
Work within a DevOps/Agile team to operate and improve platform services and tooling.
Help troubleshoot production issues, monitor service health, and respond to incidents as required.
Collaborate with data scientists and ML engineers to integrate model artifacts into applications.
Learn and apply cloud-native patterns and infrastructure-as-code practices under guidance.
Contribute to documentation, runbooks, and knowledge sharing for team and users.
Participate in code reviews, pair programming, and continuous learning initiatives.
Minimum Requirements:
Qualifications/Experience:
Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience).
1–2 years’ experience in software development with demonstrable projects or internships.
Strong fundamentals in programming (Python preferred), algorithms, and problem solving.
Essential Skills Requirements:
Proficient programming skills in Python for backend and scripting tasks.
Basic frontend development knowledge (HTML, CSS, JavaScript/TypeScript, Angular or similar).
Understanding of core software engineering principles and clean, maintainable code practices.
Familiarity with version control using Git and collaborative workflows (e.g., GitHub).
Experience or basic knowledge of containerization and Linux/Unix environments.
Exposure to cloud services (AWS or Azure) and common services like S3, Lambda, or equivalents.
Basic understanding of RESTful APIs and asynchronous communication patterns.
Awareness of unit testing and test frameworks (e.g., pytest, Jest).
Familiarity with data preprocessing/ETL concepts for ML workloads.
Good communication skills and ability to work in an Agile team.
Advantageous Skills Requirements:
Experience with machine learning frameworks such as TensorFlow or PyTorch.
Knowledge of Infrastructure as Code tools (e.g., Terraform).
Familiarity with AWS services relevant to ML (SageMaker, DynamoDB, Glue, Kinesis).
Understanding of prompt engineering and generative AI concepts.
Experience with CI/CD pipelines and automation (e.g., GitHub Actions).
Exposure to state management patterns in frontend frameworks (NgRx, RxJS) or equivalent.
Experience with data visualization tools or libraries for analytics.
Knowledge of distributed computing basics (Spark, Hadoop) or batch processing.
Prior experience working with Jupyter notebooks and managed notebook platforms.
Practical experience or coursework in algorithms, statistics, or applied mathematics.
Desired Skills:
- Python
- Frontend Development
- Software Engineering Principles