Software Engineer
Ihg- Location
- GA, United States
- Workplace
- —
- Employment
- Full Time
- Salary
- USD 119,000–145,000
Posted 2d ago
The Software Engineer will build, test, and maintain the models, agentic solutions and infrastructure that power our solutions.
The ideal candidate has a solid foundation in software development, a passionate interest in AI, and a relentless curiosity to learn. The Software Engineer is an experienced individual contributor within a project team.
Your Day to Day
- Contribute to the development of AI/ML models and agentic applications by writing, testing, and documenting code under the guidance of senior team members.
- Assist in preparing and processing data for model training and evaluation. Help build and maintain data pipelines to support our AI services.
- Participate in the testing and validation of AI models to ensure they are accurate and performant. Assist in monitoring and maintaining deployed applications.
- Work closely with other engineers, data scientists, and product managers in an agile environment to deliver on team goals.
- Actively learn from senior members of the team, participate in code reviews, and continuously develop your skills in AI, machine learning, and software engineering.
- Uphold high standards for code quality, testing, and documentation. Champion software engineering best practices within the team. Deliver code that is secure, reliable and supportable.
- Demonstrate a strong curiosity for leveraging AI to improve personal and team productivity. Actively find and implement AI-powered tools and workflows to make your own role and development processes more efficient. Effectively use AI code assistants to deliver code.
- Ensure application diagrams and documentation stay current and relevant.
- Adherence to agile development methodologies.
What You Will Bring
- Education
- Bachelors in a relevant field of work or an equivalent combination of education and work-related experience.
- Experience
- Typically, a minimum of 5+ years of software engineering experience, progressive work-related experience with demonstrated proficiency in multiple disciplines, technologies, or processes related to the position.
- Some professional or academic experience in software development, preferably using Python.
- Demonstrated interest in AI and machine learning through coursework, personal projects, or internships.
- Solid understanding of core computer science principles and software engineering fundamentals.
- A collaborative mindset and strong communication skills.
- Experience working with large datasets and complex data pipelines.
- Ability to work effectively in a collaborative, agile team environment.
- An innate curiosity and a portfolio or history that demonstrates a commitment to continually learning new technologies as they evolve.
- Technical Skill & Knowledge
- Strong programming skills in Python.
- Foundational knowledge of machine learning concepts and algorithms. Familiarity with common libraries like Scikit-learn, Pandas, or NumPy is a plus.
- Interest in learning deep learning frameworks such as TensorFlow or PyTorch.
- Good analytical and problem-solving skills with keen attention to detail.
- Familiarity with Git and version control workflows.
- Theoretical understanding of machine learning, deep learning, and natural language processing (NLP).
- Hands-on experience with at least one major cloud provider (GCP, AWS, Azure) and their associated AI/ML services.
- Experience with both SQL and NoSQL databases, and proficiency with data processing technologies like Spark is a plus.
- Understanding of microservices architecture, API design (e.g., REST, gRPC), and containerization technologies (e.g., Docker, Kubernetes).
Travel - 10%
Location - Our hybrid work structure is an expectation of three (3) days a week in office. This expectation may be adjusted to evolve with the changing needs of the business.
#LI-ZY1
Skills
- Azure AI Services
- Machine Learning
- Python
- scikit-learn
- Pandas
- NumPy
- Deep Learning
- TensorFlow
- PyTorch
- Git
- NLP
- GCP
- AWS
- Azure
- SQL
- Spark
- gRPC
- Docker
- Kubernetes
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