AIFT is hiring a Machine Learning Engineer, Vulcan

About the Role

Develop scalable machine learning systems, optimize model performance, and integrate AI capabilities into production workflows.

Compensation

Competitive salary and benefits package

Work Arrangement

Hybrid work model with flexible scheduling

Team

Collaborative team focused on AI-driven solutions

Responsibilities

• Design and implement machine learning algorithms for real-world applications
• Collaborate with data scientists to refine model inputs and outputs
• Optimize models for speed and accuracy
• Work with large-scale datasets to train and validate systems
• Integrate machine learning models into production environments
• Monitor model performance and implement updates as needed
• Support data pipeline development and maintenance
• Troubleshoot issues in model deployment and inference
• Contribute to architectural design of AI platforms
• Ensure models comply with ethical and performance standards
• Participate in code reviews and technical planning sessions
• Document model development processes and system designs
• Collaborate across engineering and research teams
• Stay current with advancements in machine learning techniques
• Assist in defining project requirements and timelines
• Evaluate new tools and frameworks for model development
• Support testing and validation of machine learning pipelines
• Improve model interpretability and explainability
• Work on model versioning and lifecycle management
• Contribute to scalable infrastructure for AI workloads
• Use statistical methods to assess model effectiveness
• Help align technical solutions with business objectives
• Support deployment automation and CI/CD practices
• Engage in problem-solving for edge cases in model behavior
• Contribute to knowledge sharing within the team

Qualifications

• Bachelor’s degree in computer science, engineering, or related field
• Proficiency in Python and machine learning libraries
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Strong understanding of data structures and algorithms
• Familiarity with cloud platforms like AWS, GCP, or Azure
• Experience with containerization tools like Docker
• Knowledge of distributed computing concepts
• Background in statistical modeling and data analysis
• Experience with version control systems like Git
• Ability to work with large, complex datasets
• Understanding of model evaluation metrics
• Experience deploying models in production settings
• Strong debugging and problem-solving skills
• Familiarity with MLOps practices
• Knowledge of natural language processing or computer vision is a plus
• Prior experience with big data tools such as Spark
• Understanding of software engineering best practices
• Ability to write clean, maintainable code
• Experience with A/B testing frameworks
• Strong written and verbal communication skills
• Ability to work independently and in teams
• Comfortable working in fast-paced environments
• Interest in continuous learning and skill development
• Experience with model monitoring tools
• Familiarity with data privacy principles

Preferred Qualifications

• Master’s degree in a technical field
• Prior work on large-scale machine learning systems
• Experience with reinforcement learning
• Background in high-performance computing
• Contributions to open-source machine learning projects
• Publications in AI or machine learning venues
• Experience with edge deployment of models
• Knowledge of model quantization and compression
• Familiarity with regulatory standards for AI
• Experience in agile development environments

Available for qualified candidates